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Understanding perceptions of college students on the operation of automated shuttle for persons with disabilities on campus walkways

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  • Persons with disabilities have difficulties traveling from one point to the other due to the limited options of travel modes for the first and last mile. Western Michigan University tested using an autonomous shuttle on the main campus's sidewalks for persons with disabilities. This study's objectives are to understand the empathy college students without disabilities had on the need for suitable transportation services for students with disabilities and the perceived risks of the services' operation on sidewalks. The Bayesian ordered logit model and text mining analyzed 396 survey responses. The Bayesian ordered logistic regression results revealed that age, gender, and ethnicity are important factors that contribute to different opinions concerning perceived risks and sympathy brought by an autonomous shuttle operating on pedestrians' sidewalks. The text mining results revealed several patterns. While respondents who were against the operation focused on potential safety hazards and the crowdedness of the sidewalks, supporters focused on the expected improved mobility for people with disabilities. The findings from this study are expected to assist policymakers and vehicle manufacturers with pedestrian expectations and considerations related to risk and safety when sharing their walkways with the autonomous shuttle.
  • Wastewater generated by chemical, petrochemical, textile, resins, paper, leather, and glue, pharmaceutical and steel industries frequently contain high concentrations of xenobiotic compounds that represent a serious ecological problem due to their toxicity and widespread occurrence in the environment.

    A xenobiotic compound is a chemical substance whose structure is rare or non-existent in nature as they are synthesized by humans in the laboratory. Xenobiotic compounds are also defined as substances that are present in concentrations much higher than usual and that would not be expected to be present within organisms. The discharge of wastewater containing different kinds of xenobiotics, into receiving water bodies endanger aquatic life, even at relatively low contaminant concentrations. Therefore, the removal of these xenobiotics from industrial wastewater is of great practical significance for environmental protection.

    Several physicochemical and biological methods have been adapted for the treatment of different kinds of xenobiotics. In recent years, biological processes for xenobiotic degradation and wastewater reutilization have been developed including aerobic and anaerobic bacteria as well as fungi. There are many reports about the potential of filamentous fungi for sludge treatment which have been well described and reviewed by More et al.[1]. Aspergillus niger showed biodegradation and bioflocculation activities, arsenic bioremediation and bioconversion of olive mill waste. Phanerochaete chrysosporium showed biodegradation and bioflocculation activities, bioremediation of lignin, PCB's, PCP's and azo dyes. Penicillium (in particular P. chrysogenum) and Paecilomyces species showed pathogen removal, bioflocculation and biodegradation activities, and the removal of arsenic compounds and insecticides, among others.

    In general, filamentous fungi have shown to be more tolerant to high concentrations of pollutants and they are less sensitive than bacteria and yeast to changes in their environment[1, 2]. Some fungi tolerate extreme environmental conditions (temperatures of –5 to +60 °C; pH of 1 to 9) and grow at a water activity of only 0.65, or with 0.2% oxygen[3]. They are able to grow on low nitrogen medium, at low pH and low temperature[1]. In addition, they are easy to grow in fermenters and be separated by mechanical methods, due to their filamentous structure[2, 4]. All these characteristics make them a promising alternative among various wastewater treatment technologies.

    Among fungi, the most widely studied are the ligninolytic fungi or white rot basidiomycota fungi. However, these types of fungi often have two major limiting factors that hinder their applicability in industry: 1) they have high nutritional requirements (lignocellulosic substrate), and 2) many species have slow growth kinetics[5]. This encourages the study of other types of fungi[46]. Many non-basidiomycota fungi are also able to degrade aromatic compounds and other complex structures[2, 612]. A good example of this kind of non-basidiomycota fungi is Penicillium sp., which belongs to the phylum Ascomycota.

    Penicillium species are able to adapt their metabolism to many different environments, and are considered ubiquitous in nature, commonly found in food, indoor air and soil. In addition, they are among the most common fungi that spoil food and contaminate indoor environments[2, 13, 14]. Diversity and adaptable metabolism of Penicillium species allows them to survive in some of the most extreme environments on earth including deep-sea sediments[15], polar regions[16, 17] to the Himalayas[18], regions of extreme acidic pH[19] and in extreme temperatures[20]. Although, primarily categorized as decomposers, Penicillium are good hydrocarbon assimilators with low co-substrate requirements, and they can synthesize a of wide variety of biomolecules[2, 13, 14]. The use of various carbon sources demonstrates their capability to adapt to changing nutritional environments and their potential to decompose diverse materials.

    There are many reports showing the ability of Penicillium to degrade various materials, including food waste, cellulose- and lignin-containing residues, and hydrocarbons[9, 11, 21, 22] and to transform xenobiotic compounds into less mutagenic substances[68, 23, 24]. The occurrence of Penicillium spp. in sewage sludge has been reported[25]. In addition, Penicillium corylophilum was more efficient compared to Aspergillus niger for biodegradation of the domestic activated sludge, enhancing the sludge degradation rate by decreasing chemical oxygen demand (COD).

    Filamentous fungi can grow on different matrices. In submerged culture, fungi can either grow in dispersed form or as spherical pellets consisting of aggregated hypha structures. Pellet morphology, process control and productivity are highly interlinked. The control process in a bioreactor usually requires compact and small pellets due to rheological issues[26]. For example, within P. chrysogenum pellets, problems with internal transport of substrates and products may occur, depending on size and compactness of pellets[27]. Cronenberg et al.[28], reported the formation of pellets with a diameter of less than 400 μm by P. chrysogenum, where the mass transfer resistance will be very low in these pellets, being an advantage for the wastewater treatment process. Moreover, the immobilization of P. chrysogenum on loofah showed a significant increase of azo dye degradation rate, with respect to the free cells[4]. Both, the immobilization and the pellet formation, leads to the possibility of biomass reuse and simplifies the operation for downstream processes.

    All the features mentioned above make Penicillium particularly suitable to be used in wastewater treatment and degradation of organic pollutants. In this review, a summary of the capabilities of some species of Penicillium to degrade different toxic compounds are described and the analysis of its potential use for wastewater treatment is discussed.

    Phenol and its derivatives are widely distributed as environmental pollutants due to their presence in the effluents of many industrial processes like chemical, petrochemical, steel, pulp and paper mill industries[2]. These effluents frequently contain high concentrations of phenolics compounds that represents a serious ecological problem due to their widespread use, toxicity and occurrence throughout the environment. Many phenolic compounds are hazardous, toxic, endocrine disrupting, mutagenic, teratogenic, and/or carcinogenic[29]. Therefore, the removal of phenol and its derivatives from industrial wastewater is of great practical significance for environmental protection. Moreover, chlorophenols have been introduced into the environment through their use as biocides, for example penta chlorophenol (PCP), trichlorophenol (TCP) and tectrachloro phenol (TeCP) were used historically as fungicides in wood-preservative formulations[30, 31].

    The biodegradation of phenols and chlorophenols by Penicillium species has been reported since the 90's and several works have continued studys in this regard (Table 1). In 1993, Hofrichter et al.[32] reported a Penicillium strain (Bi 7/2) able to grow on phenol (1,000 mg·l−1) as sole source of carbon and energy, and metabolized the phenol by the ortho-pathway. This strain also metabolizes 4-, 3- and 2-chlorophenol (50 mg·l−1) and 4-, 3- and 2-nitrophenol (50 mg·l−1), with phenol or glucose as co-substrate. The fact that an external carbon source, such as glucose, is needed implies an additional cost for the process. However, many Penicillium species can use phenol as a carbon source. This facilitates the development of a treatment process, since most of the effluents that contain chlorophenols, for example effluents from pulp and paper mill industries, contains phenol that can be utilized as a carbon source. Later, Marr et al.[33] found a Penicllium simplicissimum SK9117 strain able to degrade 3-chlorophenol, 4-chlorophenol, 4-bromophenol, 3-fluorophenol and 4-fluorophenol. However, monobromophenols and monochlorophenols were transformed to other intermediates (chlorohydroquinone, 4-chlorocatechol, 4-chloro-1,2,3-trihydroxybenzene, and 5-chloro-1,2,3-trihydroxybenzene) and could not support the fungus growth as the sole carbon and energy source, while monofluorophenols were mineralized completely without a co-substrate. In addition, difluorophenols were transformed by P. frequentans strain Bi 7/2, using phenol as a sole source of carbon and energy[35]. From the 90’s onwards, even up to 2021, more species of Penicillium were described with the ability to degrade phenol and chlorophenols (Table 1).

    Table 1.  Degradation of phenol and its derivatives by Penicillium spp.
    Chemical compoundExternal
    carbon source
    Penicillium spp.Reference
    PhenolNoneP. frequentans Bi 7/2[32]
    P. chrysogenum var. halophenolicum[23]
    P. chrysogenum ERK1[8, 37]
    P. notatum[41]
    ResorcinolNoneP. chrysogenum var. halophenolicum[24, 36]
    Catechol,
    Hydroquinone
    NoneP. chrysogenum var. halophenolicum[36]
    2-chlorophenolPhenolP. frequentans Bi 7/2[32]
    AcetateP. camemberti[39]
    3-chlorophenolPhenolP. frequentans Bi 7/2[32]
    P. simplicissimum[33]
    4-chlorophenolPhenolP. frequentans Bi 7/2[32]
    P. simplicissimum[33]
    2-nitrophenolPhenolP. frequentans Bi 7/2[32]
    3-nitrophenolPhenolP. frequentans Bi 7/2[32]
    4-nitrophenolPhenolP. frequentans Bi 7/2[32]
    4-bromophenolPhenolP. simplicissimum[33]
    3-fluorophenolNoneP. simplicissimum[33]
    4-fluorophenolNoneP. simplicissimum[33]
    2,3- difluorophenolPhenolP. frequentans Bi 7/2[35]
    2,4- difluorophenolPhenolP. frequentans Bi 7/2[35]
    2,5- difluorophenolPhenolP. frequentans Bi 7/2[35]
    3,4- difluorophenolPhenolP. frequentans Bi 7/2[35]
    2,4,6-trichlorophenolAcetateP. chrysogenum ERK1[7]
    PentachlorophenolAcetateP. camemberti[39]
    3,5-dimethyl-2,4-dichlorophenolNonePenicillium spp[40]
     | Show Table
    DownLoad: CSV

    A case worth mentioning is that described by Leitão et al.[23], where a Penicillium chrysogenum var. halophenolicum was able to mineralize phenol completely at 5.8% NaCl, since this fungus was found to be halotolerant. This condition increases the chances to use this strain in biological treatments of phenol-containing wastewater, since some of them contain high concentrations of salts. The same strain degraded up to 250 mg·l−1 of resorcinol, as the sole carbon source in batch experiments in the presence of 58.5 g·l−1 of sodium chloride[24]. In addition, the authors showed the decrease of the acute toxicity of phenol and resorcinol, on Artemia franciscana larvae, after the bioremediation process with P. chrysogenum var. halophenolicum. Ferreira-Guedes & Leitão[36], described the removal efficiency of hydroquinone, catechol and resorcinol in binary substrate systems under saline conditions by the same P. chrysogenum var. halophenolicum strain. Catechol, resorcinol and hydroquinone are dihydroxybenzene isomers. The simultaneous presence of two or three isomers in a mixture will be defined as binary or ternary mixtures. The results of Ferreira-Guedes & Leitão[36] showed that the efficiency to remove dihydroxybenzene in binary substrate systems was higher than in mono substrate systems, except for hydroquinone. In the binary substrate systems, dihydroxybenzenes were removed not only simultaneously, but also preferentially. At high dihydroxybenzene concentration, fungal strain preferentially degraded hydroquinone followed by catechol and resorcinol.

    Most of the results reported in Table 1, were obtained in batch culture in shaking conditions between 80 to 160 rpm. However, some studies showed that Penicillium frequentans Bi 7/2 and Penicillium chrysogeunm ERK1 could degrade dichlorophenols and phenol, respectively in resting mycelium conditions[35,37]. This may be convenient in terms of reducing the costs of wastewater treatment processes.

    Furthermore, Aranciaga et al.[7] studied the biodegradation of 2,4,6-trichlorophenol, demonstrating that Penicillium chrysogenum ERK1 was able to degrade 85% of TCP in batch cultures in the presence of sodium acetate. In their study, hydroquinone and benzo quinone were identified as degradation intermediates, and although the complete mineralization of the TCP did not occur, a reduction on the phytotoxicity (50% approximately) was observed. The extent of degradation depends on the structure of the compound, the number of chlorine substituents, and the position of chlorine in the compound[38]. This directly influences the toxicity of the compound, which generally increases as the chlorinated substituents number increases. That is why it is equally important to reduce the toxicity of the effluent, even when the compound cannot be completely mineralized.

    In the case of pentachlorophenol (PCP), Taseli & Gokcay[39] showed that Penicillium camemberti was able to remove 56% of PCP in batch experiments with acetate as a carbon source. In other experiments, without acetate but in the presence of Tween 80, P. camemberti removed 86% of the PCP. Moreover, an up-flow column reactor was operated with this fungus in the laboratory[39] and 77% of PCP removal was achieved in 4 d of contact without aeration and with minimum amount of carbon supplement. The percentages of PCP removal continued decreasing to 18.8% until the 18th day. These results agree with the results mentioned above, and show almost ideal conditions with respect to operating costs, without aeration and a reduced concentration of external carbon source.

    In another study, Yan et al.[40] studied the performance of a Penicillium sp. strain to remove a 3,5-dimethyl-2,4-dichlorophenol (DCMX) from saline industrial wastewater. The results of batch experiments showed that biodegradation of DCMX was affected by pH value, salinity and DCMX concentration. The maximum DCMX removal efficiency was obtained at salinity 2.6%, temperature 32 °C and pH 5.87.

    The term colorant, which includes dyes and pigments, refers to substances capable of colouring a substrate. Colorants are used in industries like clothing, paints, plastics, photographs, prints and ceramics. They are used alone or in combination with other ingredients, which impart or alter the colour of the product[42]. Most dyes used in these processes are synthetic and are classified based on chromophore structures (namely acidic, basic, disperse, reactive, azo dyes and anthraquinone).

    Dye wastewater treatment, mainly from textile industries, is really important in order to control its negative impact on the environment. Some dye precursors or its degradation byproducts were reported as toxic, carcinogenic and mutagenic[43,44], like aromatic amines which damage the DNA in cells and this leads to a risk of cancer[42].

    The mycoremediation of dyes has shown to be a possible option to the conventional physico-chemical treatment technologies. The most widely used fungi in decolorization and degradation of dyes are the lignolytic fungi of class Basidiomycetes. However, non basidiomycotas fungi such as Aspergillus niger and A. terreus[45], Rhizopus oryzae[46] and some species of Penicillium[39,4749] can also decolorize and/or biosorb diverse dyes[50,51].

    For example, Shedbalkar et al.[47] showed that Penicillium ochrochloron decolorized cotton blue (50 mg·l−1), a triphenylmethane dye (Table 2). In this case, the dye was degraded to sulphonamide and triphenylmethane, as final products, by a battery of enzymes (lignin peroxidase, tyrosinase and aminopyrine N-demethylase) and the analysis of the phytotoxicity and microbial toxicity of extracted metabolites, suggested a decrease in their toxicity. The same P. ochrochloron has been shown to detoxify malachite green into p-benzyl-N,N-dimethylaniline and N,N-dimethyl-aniline hydrochloride. These metabolites were nontoxic when tested on Triticum aestivum and Ervum lens Linn (Table 2)[48]. The reaction was mediated by lignin peroxidase and the fungal culture was also found to have detoxified the textile effluent, reducing the values of total dissolved solids (TDS), total suspended solids (TSS), biochemical oxygen demand (BOD), and chemical oxygen demand (COD). In both works, it was demonstrated that P. ochrochloron was able to degrade and reduce the toxicity of two different dyes. However, it would be interesting to study the degradation and the analysis of the toxicity of the mixture of both dyes.

    Table 2.  Dye decolorization and degradation by Penicillium spp.
    Penicillium sppChemical groupDye nameConcentration
    (mg·l−1)
    Toxicity analysisWastewater testedReference
    P. chrysogenumAzo
    Direct Black 22,
    Direct Yellow 86,
    Direct Blue 200
    200T. aestivumDiluted effluent[4, 6]
    P. ochrochloronTriphenylmethane
    Cotton blue50T. aestivum
    E. lens
    A. vinelandii

    No[47]
    Malachite green50T. aestivum
    E. lens
    Diluted effluent[48]
    P. simplicissimum

    Azo

    Reactive Red 198 Reactive Blue 214200
    D. pulexNo[52]
    PhthalocyanineReactive Blue 21200D. pulexNo[52]
    TriphenylmethaneMethyl Violet, Crystal Violet, Malachite Green
    Cotton Blue
    50−100

    V. radiate
    B. cereus
    S. aureus
    No[53, 54]
    P. oxalicumAzoAcid Red 183, Direct Blue 15 Direct Red 75100−300NoNo[5]
    P. pinophilumTriphenylmethaneMalachite Green10NoNo[55]
     | Show Table
    DownLoad: CSV

    Moreover, Penicillium simplicissimum INCQS 40211 decolorized the textile dyes: Reactive Red 198 (RR198), Reactive Blue 214 (RB214), Reactive Blue 21 (RB21) and their mixture[52]. In this case, it was suggested that dye decolorization involved dye adsorption by the biomass first, followed by degradation. In addition, P. simplicissimum reduced the toxicity of RB21 from moderately acutely toxic to minor acutely toxic and it also reduced the toxicity of RB214 and the mixture of the three dyes, which remained minor acutely toxic. It is also worth noticing that the fungus increased the toxicity of RR198. These results showed that more studies regarding dye degradation and toxicity reduction by P. simplicissimum INCQS 40211 are necessary. Later, Chen & Ting[53] and Chen et al.[54] described the biosorption and biodegradation activities of the same Penicillium species towards triphenylmethane dyes. Crystal Violet (CV), Methyl Violet (MV), Malachite Green (MG), and Cotton Blue (CB) were decolorized by P. simplicissimum with 98.7%, 97.5%, 97.1%, and 96.1 % of decolorization efficiency, respectively, within 2 h of incubation (50 mg·l−1, pH 5.0, 25 ± 2 °C) (Table 2). In this work, only UV–visible spectral analysis of dyes was conducted before and after treatment with P. simplicissimum, indicating the occurrence of biodegradation, however the intermediate products of the degradation or complete mineralization could not be confirmed. Some enzymatic activities were detected as manganese peroxidase, tyrosinase, triphenylmethane reductase activities, suggesting their involvement in the degradation pathway. In addition, reduction of phytotoxicity and microbial toxicity were observed only for MG.

    Other Penicillium species that have been reported to have decolorization/degradation abilities are: Penicillium oxalicum[5], Penicillium pinophilum[55], Penicillium purpurogenum[56] and a Penicillium strain not characterized at the species level[57].

    In all the cases mentioned above, degradation occurs with the addition of some external carbon source. In general, dyes are evaluated in culture media and only in a few cases mixtures of dyes and real effluents are studied.

    Another strain, which is worth mentioning, is Penicillium chrysogenum. This fungus showed great potential to decolorize and degrade three azo dyes (at 200 mg·l−1) independently or a mixture of them, even in a complex wastewater matrix as it was real textile wastewater[6] (Table 2). The degradation process was carried out in the presence of glucose as a carbon source and showed that decolorization rates differed depending on the azo dye structure (number of azo bonds, terminal or substituent groups, steric hindrance, etc.). Moreover, a kinetic model for degradation was developed, which allowed prediction of the degradation kinetics of the mixture of the three azo dyes and the real textile wastewater[6]. Later, the immobilization on loofah of the same strain of P. chrysogenum significantly increased the degradation rate of DB22 in a laboratory scale as well as at bench scale reactor, with respect to the non-immobilized treatment[4]. The degradation rate of immobilized cells increased twice as compared to free-cells control and at day 5 the decolorization was almost complete, while without loofah, the total decolorization took more than 10 d. The results of these studies show an improvement in the azo dye degradation process, however, using glucose as a carbon source is still costly. Therefore, more studies should be carried out using alternative carbon sources such as waste from food industries, for example starch, beer bagasse, etc. to minimize effluent treatment costs.

    Erdal & Taskin[58], also showed the potential of a strain of P. chrysogenum MT-6 to decolorize the textile dye Reactive Black-5. However, degradation was not confirmed in this case.

    Lately, Fouda et al.[59] biosynthesized maghemite nanoparticles (γ-Fe2O3-NPs) using Penicillium expansum with the purpose of treating wastewater. Decolorization and degradation analyses, indicated that γ-Fe2O3-NPs was an effective biocatalyst for dye degradation under dose- and time-dependent manner. The highest decolorization (89%–90%) occurred after 6.0–8.0 h of incubation. The contaminant load of the textile wastewater was improved, as indicated by the reduction in COD, TDS, and TSS. Although, GC-MS results showed the complete disappearance of peaks in treated textile wastewater in comparison with the untreated samples, no toxicity analysis was carried out.

    In recent years, the increase in the use and production of pharmaceutical compounds represent a potential environmental risk, since it could lead to antibiotic resistance, toxicity and can also cause endocrine disruption[10, 12, 60, 61]. For this reason, a proper disposal and treatment or degradation of these compounds is necessary.

    In this area, additional examples of biodegradation with Penicillium isolates can be found[10, 12]. For example, the non-steroidal anti-inflammatory drug [2-(2,6-dichloroanilino) phenyl] acetic acid (Diclofenac; DFC) is used for the treatment of pain and inflammation, and it is one of the most widely used drugs around the world. It is considered as an emerging contaminant, being the number one persistent pharmaceutical substance in water bodies in 50 countries of the EU, Africa and America[62]. Olicón-Hernández et al.[10], were the first to describe the use of a Penicillium isolate able to transform DFC. They studied DFC degradation by Penicillium oxalicum in flask and bench scale bioreactors, both with free and immobilized biomass. Pellets of P. oxalicum degraded 100 μM of DFC within 24 h, and the activity of CYP450 enzymes was the key for the drug elimination. The use of P. oxalicum reduced the acute toxicity of the medium supplemented with DFC, and the free biomass system exhibited the highest rate of DFC degradation in comparison with immobilized cells in the batch bioreactor. In addition, the same Penicillium isolate was able to reduce the concentration of other pharmaceutical active compounds, such as ketoprofen, naproxen and paracetamol in batch bench scale bioreactor in 24 h[61]. In general, the industrial effluents are not sterile and they usually have microorganisms, which can inhibit the growth and/or the degradation of toxic compounds by the degrading microorganisms that are of interest for wastewater treatment. For this reasons, the results obtained by Olicón-Hernández et al.[61] are of great importance since they showed that P. oxalicum inhibited the native fungal populations, present in the non-sterile real hospital wastewater, along with opportunistic human pathogens.

    As it can be seen, in the case of DFC degradation, the immobilized cells did not improve the process, contrary to what was observed for the degradation of azo dyes with P. chrysogenum. For this reason, the treatment process of each effluent must be analysed independently to achieve optimal operating conditions.

    Additionally, Li et al.[12], recently reported a Penicillium oxalicum strain that could efficiently degrade lincomycin (88.2% by day 6) from the antibiotic wastewater treatment plant and the fungal mycelium could be reused for at least ten batches with similar biodegradation efficiency. Besides, an endophytic strain of the same species could effectively degrade triclosan, which is an antibacterial and antifungal agent, into low toxic products[63].

    These studies showed that P. oxalicum was able to reduce the concentration of pharmaceutical compounds in batch bench scale bioreactor, also it was not inhibited by the native fungal populations present in the effluent and the mycelium could be reused with good biodegradation efficiency. These characteristics strongly suggest that P. oxalicum has a high potential for the treatment of pharmaceutical compounds.

    Polycyclic aromatic hydrocarbons (PAHs) are poorly soluble, hydrophobic organic compounds which are among the most widely distributed organic contaminants[2]. They are released/transposed due to incomplete combustion of organic matter in petrochemical industries and proven to be highly genotoxic, mutagenic, carcinogenic as well as teratogenic to humans[64]. The PAHs are considered important environmental pollutants since they are the most frequently found in soil pollutants[65].

    As described by Leitão[2] and Rabha & Jha[14], there are several reports regarding biodegradation of PAHs by Penicillium species[34, 6672] (Table 3). The effect of oxygen, ciclodextrins, surfactants, carbon and nitrogen sources, and other factors on PAHs biodegradation were studied in these reports. In addition, the presence of pyrene for example was described to influence the size and shape of the fungal pellets as well as the density of mycelium and hyphal length[71]. These studies, showed the degradation of different PAHs separately. In 2014, Vanishree et al.[73] isolated a Penicillium sp. strain from petrol bunks soils and automobile workshops which can tolerate, grow and degrade different petrol concentrations.

    Table 3.  Hydrocarbon degradation by Penicillium spp.
    Chemical compoundPenicillium sppReference
    AcenaphthenePenicillium sp. CHY-2[74]
    AnthraceneP. oxalicum[75]
    P. ilerdanum[76]
    P. oxalicum SYJ-1[77]
    Benzo[a]pyrenePenicillium sp. CHY-2[74]
    P. janthinellum[66, 67]
    Benz[a]antraceneP. janthinellum[67]
    ButylbenzenePenicillium sp. CHY-2[74]
    ChryseneP. janthinellum[67]
    EthylbenzenePenicillium sp. CHY-2[74]
    Dibenz[a,h]anthraceneP. janthinellum[67]
    DibenzothiopheneP. oxalicum[75]
    DibenzofuranP. oxalicum[75]
    FluoreneP. italicum[69]
    P chrysogenum[68]
    FluorantheneP. ilerdanum[76]
    NaphthaleneP. ilerdanum[76]
    Penicillium sp. CHY-2[74]
    PhenanthreneP. frequentans[72]
    P. ilerdanum[76]
    P. oxalicum[75]
    P. oxalicum SYJ-1[77]
    PyreneP. simplicissimum,
    P. funiculosum,
    P. harzianum,
    P. terrestre
    [70]
    P. janthinellum,[66,67,70]
    P. ochrochloron[71]
    P. glabrum[34]
    P. ilerdanum[76]
    Penicillium oxalicum SYJ-1[77]
    PetrolPenicillium sp[73]
    DecanePenicillium sp. CHY-2[74]
    DodecanePenicillium sp. CHY-2[74]
    OctanePenicillium sp. CHY-2[74]
     | Show Table
    DownLoad: CSV

    Penicillium oxalicum was also reported to be able to completely remove anthracene and dibenzothiophene within 4 d, as well as phenanthrene and dibenzofuran, although at slower rates[75]. Most Penicillium strains which degrade PAHs carried out the degradation through the cytochrome P450 monooxygenase enzyme pathway. However, cytochrome P450 monooxygenase plays a role in the first steps of transformation of PAHs, while induction of oxygenase activity was detected in the subcellular fraction of the fungal mycelium exposed to these aromatic compounds.

    Aranda et al.[75] demonstrated that glucose was required for anthracene degradation by P. oxalicum using a defined growth medium with low carbon content for stable isotope tracer experiments with 13C 6-anthracene. Therefore, anthracene mineralization could not be confirmed, but 13C-labelled oxy and hydroxy-derivatives were identified by nuclear magnetic resonance (NMR) as major metabolites. Although P. oxalicum was found to be the fungus with the highest and fastest PAHs degradation capability, the toxicity of these major metabolites should be evaluated, for a safe application in biotechnological pollutant removal processes.

    Antarctic soil has also been a source of hydrocarbon degrading microorganisms[78,79] including Penicillium. A Penicillium sp. CHY-2 isolated from Antarctic soil was able to degrade not only aromatic hydrocarbons but also aliphatic hydrocarbons[74]. The highest level of degradation was for decane (49.0%), followed by butylbenzene (42.0%) and dodecane (33.0%), and lower levels of degradation were found for naphthalene (15.0%), acenaphthene (10.0%), octane (8.0%), ethylbenzene (4.0%), and benzo[a]pyrene (2.0%) at 20 °C. Later, the authors studied decane degradation in depth and showed that the addition of carbon sources such as glucose (5 g·l1) and Tween-80 (5 g·l1) enhanced decane degradation by about 1.8-fold and 1.61-fold respectively at 20 °C. 1,6-hexanediol was identified as one of the metabolites produced during the degradation of decane and a manganese peroxidase (MnP) enzyme was isolated from the fungi.

    Over the years, more and more studies with new isolates able to degrade hydrocarbons have appeared, for example in 2021 a Penicillium ilerdanum NPDF1239-K3-F21, isolated from Arabian sea sediments, showed > 75% ability to degrade naphthalene, phenanthrene, pyrene, fluoranthene and anthracene[76]. However, beyond the degradation processes, further optimization, pilot scale and toxicity studies must be carried out before applying these processes to wastewater or bioremediation treatments.

    Recently, Zhou et al.[77] showed a novel self-assembled PAH-degrading fungal mycelium Penicillium oxalicum SYJ-1-carbon nanotube (CNT) composites for pyrene removal. Their study is a good example of the combination of biodegradation and nanotechnology to increase the total PAH removal efficiency. Anthracene, phenanthrene and pyrene could be removed by 65%–92% within 72 h, while no naphthalene removal was observed by Penicillium oxalicum SYJ-1. Due to pyrene moderate degradation, this was selected as a model substrate to evaluate the possible positive effect of CNTs. The addition of it did not affect the growth of strain SYJ-1 and the complete removal of pyrene (20 mg·l1) was achieved within 48 h, while the sole fungus and CNTs alone could only remove 72% and 80% of pyrene at 72 h, respectively. Besides, the authors carried out a transcriptomic analysis, and a cytochrome P450 inhibition experiment and identified some degradation products, which allowed them to suggest that an intracellular PAH transformation pathway was employed by strain SYJ-1.

    Further, the versatility of the assembly approach was also confirmed by adding different nanomaterials (TiO2, δ-MnO2 and α-MnO2) and using them to remove phenanthrene, which was successful.

    Most of the studies carried out on hydrocarbon degradation by Penicillium spp. showed that pilot scale and toxicity studies on the metabolites are scarce, being an important point for the design of a suitable wastewater treatment.

    Fats and oils are the major wastes generated by food processing industries, dairy industries, kitchen activities, bakeries and beverages industries, etc.[21]. In most countries, waste grease has been dumped in the litter site or sewage without any pretreatment leading to severe environmental issues[22]. Grease waste in effluents can cause serious problems such as a reduction in the cell-aqueous phase transfer rates (as well as gas-liquid), reduced sedimentation, and formation of floating sludge, clogging and the emergence of unpleasant odours[80]. For these reasons and due to the high pollutant content of these effluents, it is essential to apply an efficient treatment to release it into the environment. A good option for the treatment of fat-rich wastewater is enzymatic hydrolysis with lipases (Triacylglycerol acylhydrolases, E.C. 3.1.1.3)[21, 22, 81]. These enzymes catalyze esterification, inter-esterification, acidolysis, alcoholysis and aminolysis in addition to the hydrolytic activity on triglycerides[82] and are largely produced by filamentous fungi like Penicillium chrysogenum, Penicillium cyclopium, Penicillium simplicissiimum, Penicillium expansum, Candida rugosa, Aspergillus, Trichoderma etc.[8385]. For example, Kumar et al.[21] demonstrated the production of a novel lipase by Penicillium chrysogenum when it was growing in solid media containing waste grease. This enzyme was isolated, purified, characterized and it was applied on cooking oil waste showing high acid value (26.92 mg·g–1), indicating the presence of free fatty acids.

    Later, Kumari et al.[22], reported an effective way to bio-remediate grease waste with the combination of lipase pre-treatment (commercial lipases from different fungi) and P. chrysogenum fermentation. First, the authors pre-treated the grease waste using various lipases and then, this pre-treated grease was used as a substrate by P. chrysogenum. The resulting fermented media was analysed and the production of fatty acids was detected, showing high amounts of palmitic acid (2.8 g of palmitic acid recovered from 1.0 kg grease waste). In this case not only bioremediation was successful, but also fatty acid, a value-added product, was obtained from the waste.

    Moreover, the treatment of dairy wastewater has been described, using sequential and simultaneous treatment processes, where enzymatic hydrolysis was carried out by an isolate of Penicillium citrinum, followed by anaerobic digestion[81]. Free and immobilized whole cells were used as catalysts for the treatment of dairy wastewater. Free whole cells achieved a 1.3-fold higher percent hydrolysis (92.5%) than immobilized whole cells. The biodegradability tests were conducted using crude wastewater, wastewater prehydrolyzed by whole cells, and wastewater simultaneously submitted to whole-cell hydrolysis and biodigestion. The organic matter removal reaches about 43% in all tests. However, the use of whole cells reduced the lag phase time of methanogenic archaea, which accelerated anaerobic digestion, with a higher methane production rate. These results, demonstrated the advantages of using enzymatic hydrolysis combined with anaerobic digestion, whether sequentially or simultaneously.

    So far we have reviewed large groups of organic pollutants, of which there are many references as we can see above, dyes, phenols, hydrocarbons, and others. Penicillium species have demonstrated their ability to degrade other xenobiotic compounds (Table 4).

    Table 4.  Degradation of other organic pollutants by Penicillium spp.
    CompoundPenicillium sppReference
    FormaldehydeP. chrysogenum DY-F2[86]
    DiethylketonePenicillium spp.[87]
    Polychlorinated biphenylsP. chrysogenum,
    P. citreosulfuratum,
    P. canescens.
    [88]
    Sodium dodecylbenzene sulfonateP. chrysogenum[11]
    Poly ɛ-caprolactone and Polyester vylon 200P. fellutanum (Lipases)
    [89, 90]
     | Show Table
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    In 2014, Luo et al.[86] reported a formaldehyde-degrading Penicillium chrysogenum DY-F2 strain, which was isolated from deep sea sediment. This characteristic is interesting, as this makes this fungus useful to be used for the bioremediation of polluted marine environment or wastewater with high salt content. In most studies reported previously, the fungi were isolated from contaminated soils, river sediments or from wastewater treatment plants. P. chrysogenum DY-F2 showed high formaldehyde resistance and was able to grow in the presence of formaldehyde up to 3,000 mg·l–1. In addition, it was able to degrade formaldehyde as the sole source of carbon and energy with the formation of formic acid as the intermediate. This study by Luo et al.[86] was the first to report degradation of formaldehyde by marine fungi.

    Some Penicillium species, like P. citreonigrum, P. oxalicum, P. chrysogenum, P. spinulosum, P. verruculosum and P. variabile can efficiently degrade diethyl ketone[87], sodium dodecyl benzene sulfonate[11] and grow well in agar media containing paraffin, chitin, cellulose, leather, pectin, skim milk, sunflower oil, and starch[9] (Table 4). However, the disappearance of the substrates was not measured, and therefore it cannot be confirmed that there was degradation or mineralization of these compounds.

    Polychlorinated biphenyls (PCBs) were widely used in electrical equipment and in heat transfer fluids. These pollutants are widespread, persistent, deleterious to the environment and very dangerous for humans. Germain et al.[88] recently described the isolation of four native fungal strains with a remarkable biodegradation capacity, greater than 70%. Three of the four isolates belong to the genus Penicillium: P. chrysogenum, P. citreosulfuratum and P. canescens. The last one was the only one that reduced the toxicity related to PCBs and their metabolites, significantly.

    Lately, Amin et al.[89, 90] described the degradation of poly ɛ-caprolactone (PCL), a biodegradable aliphatic polyester, and of polyester vylon 200 (PV-200), a synthetic non-biodegradable plastic, by lipases from Penicillium fellutanum. These lipases exhibited stability over a broad pH spectrum and by incubation with various industrially relevant organic solvents (benzene, hexanol, ether, and acetone). Under optimal operating conditions, lipase catalyzed the degradation of PCL film leading to 66% weight loss and 81% weight loss for PV-200. These results showed that P. fellutanum lipase would be a prospective green and ecofriendly biocatalytic system for efficient degradation and depolymerization of polyester for environmental safety.

    The removal of xenobiotics from industrial wastewater is of great interest to avoid environmental contamination. Even though biodegradation and bioremediation with fungi have been well studied, they have not yet been successfully implemented.

    Penicillium species showed their ability to adapt their metabolism to many different circumstances and these fungi can use different xenobiotics as a carbon source. In this review, many different capabilities to degrade xenobiotic compounds by Penicillium species were summarized. This revision detailed some areas where there are few studies (pilot scale, toxicity, immobilization and consortia studies) and others where there is enough information (fungi isolation and degradation studies); however, in both cases the research should be addressed to obtain new tools for the treatment of wastewater that contain xenobiotic compounds.

    For the degradation of phenols and their chlorinated derivatives, most of the Penicillium species mentioned in this review were able to use phenol as a sole carbon source (with or without shaking) and degrade chlorophenols in the presence of an auxiliary carbon source, like phenol, glucose, acetate, etc. Most of the studies were carried out with P. simplicissimum and P. chrysogenum and in batch reactors, while only in one work an up-flow column reactor was operated.

    In the search for efficient treatments for the degradation of textile effluents, many studies on dye degradation by Penicillium have been carried out. Most of these are in batch culture, testing a few dyes in simulated wastewater and did not test the final toxicity of the degradation products, which is of great importance taking into account the production of toxic aromatic amines. Besides, in the case of azo dyes, the addition of a carbon source is necessary. It is worth mentioning the case of P. chrysogenum and P. ochrochloron which were tested on real textile wastewater and showed good results.

    At the time of this report, Penicillium oxalicum was the only species reported for the degradation of pharmaceutical compounds. This subject area has gained importance as in the last few years, antibiotic pollution has increased considerably. For this reason, more studies on this issue have to be carried out.

    There are several reports about the biodegradation of PAHs by Penicillium species. These studies range from degradation of aromatic hydrocarbons to aliphatic hydrocarbons. Most of the studies showed an increase in degradation by the addition of an external carbon source or surfactants and were carried out in batch cultures with the PAHs tested independently. Therefore, more studies have to be carried out on mixtures of PAHs and crude oil.

    Degradation of fats and oils using enzymatic hydrolysis with lipases from Penicillium species and the fungi have been successful and also allowed the recovery of fatty acids as a value-added product. In general, Penicillium showed good characteristics to be applied in fats and oils treatment, since it could form pellets and can be immobilized on loofa to increase the adsorption and degradation of fats.

    In all the studies, no toxicity assays were carried out or only were done on plants and bacteria. The analysis of the toxicity on different species (more than one toxicity test) is very important to understand the efficiency of the biodegradation treatment and select the final destination of the effluent more appropriately, that is, to determine if it can be dumped into the sea or re-used for irrigation, etc. In addition, there is a lack of studies on pilot and full-scale operation processes to solve large-scale problems. The same happens with consortia studies, since taking into account the great ability of different strains of Penicillium, one could think of using a consortium made up of several Penicillium species with different degrading capacities.

    Finally, Penicillium strains have proven to be versatile and capable of being used for the biodegradation of different pollutants in wastewater. These fungi can be found in abundance naturally in the environment and it would be a reasonably cheap solution. However, for all the cases mentioned and summarized in this review, it is clear that beyond the degradation and optimization processes; pilot scale studies and toxicity studies must be carried out to be able to apply these processes for wastewater or bioremediation treatments.

    The author would like to thank National Scientific and Technical Research Council (CONICET) and National University of Mar del Plata for supporting this work. Thank you very much to Inés Lanfranconi and Jorge Froilán González for the critical reading of the manuscript and her helpful suggestions.

  • The author declares that there is no conflict of interest.

  • [1]

    des Cognets J, Rafert G. 2019. Assessing the unmet transportation needs of Americans with disabilities. https://anyflip.com/ieove/pvfg/basic

    [2]

    Harper CD, Hendrickson CT, Mangones S, Samaras C. 2016. Estimating potential increases in travel with autonomous vehicles for the non-driving, elderly and people with travel-restrictive medical conditions. Transportation Research Part C: Emerging Technologies 72:1−9

    doi: 10.1016/j.trc.2016.09.003

    CrossRef   Google Scholar

    [3]

    Stjernborg V. 2019. Accessibility for all in public transport and the overlooked (social) dimension — a case study of Stockholm. Sustainability 11:4902

    doi: 10.3390/su11184902

    CrossRef   Google Scholar

    [4]

    U.S. Department of Transportation, National Highway Traffic Safety Administration (NHTSA). 2018. Fatal Motor Vehicle Crashes 2017: Overview. Dot Hs 812603. pp. 1–9. https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812603

    [5]

    American Association for People with Disability (AAPD). 2016. Equity in Transportation for People with Disabilities. https://www.civilrightsdocs.info/pdf/transportation/final-transportation-equity-disability.pdf

    [6]

    Tillmann V, Haveman M, Stöppler R, Kvas Š, Monninger D. 2013. Public bus drivers and social inclusion: evaluation of their knowledge and attitudes toward people with intellectual disabilities. Journal of Policy and Practice in Intellectual Disabilities 10:307−13

    doi: 10.1111/jppi.12057

    CrossRef   Google Scholar

    [7]

    Park J, Chowdhury S. 2018. Investigating the barriers in a typical journey by public transport users with disabilities. Journal of Transport & Health 10:361−68

    doi: 10.1016/j.jth.2018.05.008

    CrossRef   Google Scholar

    [8]

    Council N, June D. 2005. The Current State of Transportation for People with Disabilities in the United States National. Report. National Council on Disability, US. www.govinfo.gov/content/pkg/GOVPUB-Y3_D63_3-PURL-LPS97333/pdf/GOVPUB-Y3_D63_3-PURL-LPS97333.pdf

    [9]

    Cohen S, Shirazi S. 2017. Can We Advance Social Equity with Shared, Autonomous and Electrica Vehicles? California Governer's Office of Planning and Research. Report. US: UC Davis Institute of Transportation Studies. https://3rev.sf.ucdavis.edu/sites/g/files/dgvnsk6431/files/files/page/3R.Equity.Indesign.Final_.pdf

    [10]

    Krueger R, Rashidi TH, Rose JM. 2016. Preferences for shared autonomous vehicles. Transportation Research Part C: Emerging Technologies 69:343−55

    doi: 10.1016/j.trc.2016.06.015

    CrossRef   Google Scholar

    [11]

    Litman T. 2014. Autonomous vehicle implementation predictions: implications for transport planning. Transportation Research Board Annual Meeting 42:36−42

    Google Scholar

    [12]

    Brandshaw-Martin H, Easton C. 2014. Autonomous or "driverless" cars and disability: a legal and ethical analysis. Eurpean Journal of Current Legal Issues. 20(3):00

    Google Scholar

    [13]

    Hwang J, Li W, Stough L, Lee C, Turnbull K. 2020. A focus group study on the potential of autonomous vehicles as a viable transportation option: perspectives from people with disabilities and public transit agencies. Transportation Research Part F: Traffic Psychology and Behaviour 70:260−74

    doi: 10.1016/j.trf.2020.03.007

    CrossRef   Google Scholar

    [14]

    Kassens-Noor E, Kotval-Karamchandani Z, Cai M. 2020. Willingness to ride and perceptions of autonomous public transit. Transportation Research Part A: Policy and Practice 138:92−104

    doi: 10.1016/j.tra.2020.05.010

    CrossRef   Google Scholar

    [15]

    National Center for Mobility Management. 2018. Autonomous Vehicles: Considerations for People with Disabilities and Older Adults. https://nationalcenterformobilitymanagement.org/wp-content/uploads/2018/08/AVs_PwD_OA_Final_sm.pdf.

    [16]

    U.S. Department of Transportation, Federal Highway Administration (USDOT). 2016. Small Town and Rural Multimodal Networks. https://transportation.ky.gov/BikeWalk/Documents/Small%20and%20Rural%20Town%20Multi%20Modal%20Networks%202017.pdf

    [17]

    Machek E, Burkman E, Crayton T, Cregger J, Diggs D, et al. 2018. Strategic Transit Automation Research Plan. https://doi.org/10.21949/1503427

    [18]

    Schoettle B, Sivak M. 2014. A survey of public opinion about connected vehicles in the U.S., the U.K., and Australia. 2014 International Conference on Connected Vehicles and Expo (ICCVE). Vienna, Austria, 3-7 November 2014. USA: IEEE. pp. 687−92. https://doi.org/10.1109/ICCVE.2014.7297637

    [19]

    Bennett R, Vijaygopal R, Kottasz R. 2019. Attitudes towards autonomous vehicles among people with physical disabilities. Transportation Research Part A: Policy and Practice 127:1−17

    doi: 10.1016/j.tra.2019.07.002

    CrossRef   Google Scholar

    [20]

    Hulse LM, Xie H, Galea ER. 2018. Perceptions of autonomous vehicles: relationships with road users, risk, gender and age. Safety Science 102:1−13

    doi: 10.1016/j.ssci.2017.10.001

    CrossRef   Google Scholar

    [21]

    Hwang J, Li W, Stough LM, Lee C, Turnbull K. 2021. People with disabilities’ perceptions of autonomous vehicles as a viable transportation option to improve mobility: an exploratory study using mixed methods. International Journal of Sustainable Transportation 15:924−42

    doi: 10.1080/15568318.2020.1833115

    CrossRef   Google Scholar

    [22]

    Battistini R, Mantecchini L, Postorino MN. 2020. Users' acceptance of connected and automated shuttles for tourism purposes: a survey study. Sustainability 12:10188

    doi: 10.3390/su122310188

    CrossRef   Google Scholar

    [23]

    Haboucha CJ, Ishaq R, Shiftan Y. 2017. User preferences regarding autonomous vehicles. Transportation Research Part C: Emerging Technologies 78:37−49

    doi: 10.1016/j.trc.2017.01.010

    CrossRef   Google Scholar

    [24]

    Xu X, Fan CK. 2019. Autonomous vehicles, risk perceptions and insurance demand: an individual survey in China. Transportation Research Part A: Policy and Practice 124:549−56

    doi: 10.1016/j.tra.2018.04.009

    CrossRef   Google Scholar

    [25]

    Payre W, Cestac J, Delhomme P. 2014. Intention to use a fully automated car: attitudes and a priori acceptability. Transportation Research Part F: Traffic Psychology and Behaviour 27:252−63

    doi: 10.1016/j.trf.2014.04.009

    CrossRef   Google Scholar

    [26]

    Hohenberger C, Spörrle M, Welpe IM. 2016. How and why do men and women differ in their willingness to use automated cars? The influence of emotions across different age groups. Transportation Research Part A: Policy and Practice 94:374−85

    doi: 10.1016/j.tra.2016.09.022

    CrossRef   Google Scholar

    [27]

    Madigan R, Louw T, Wilbrink M, Schieben A, Merat N. 2017. What influences the decision to use automated public transport? Using UTAUT to understand public acceptance of automated road transport systems. Transportation Research Part F: Traffic Psychology and Behaviour 50:55−64

    doi: 10.1016/j.trf.2017.07.007

    CrossRef   Google Scholar

    [28]

    Zhang T, Tao D, Qu X, Zhang X, Lin R, et al. 2019. The roles of initial trust and perceived risk in public’s acceptance of automated vehicles. Transportation Research Part C: Emerging Technologies 98:207−20

    doi: 10.1016/j.trc.2018.11.018

    CrossRef   Google Scholar

    [29]

    Xu Z, Zhang K, Min H, Wang Z, Zhao X, et al. 2018. What drives people to accept automated vehicles? Findings from a field experiment. Transportation Research Part C: Emerging Technologies 95:320−34

    doi: 10.1016/j.trc.2018.07.024

    CrossRef   Google Scholar

    [30]

    Fan HSL. 1990. Passenger car equivalents for vehicles on Singapore expressways. Transportation Research Part A: General 24:391−96

    doi: 10.1016/0191-2607(90)90051-7

    CrossRef   Google Scholar

    [31]

    McNeish D. 2016. On using Bayesian methods to address small sample problems. Structural Equation Modeling: A Multidisciplinary Journal 23:750−73

    doi: 10.1080/10705511.2016.1186549

    CrossRef   Google Scholar

    [32]

    Williams R. 2016. Understanding and interpreting generalized ordered logit models. The Journal of Mathematical Sociology 40:7−20

    doi: 10.1080/0022250x.2015.1112384

    CrossRef   Google Scholar

    [33]

    Eberly LE, Casella G. 2003. Estimating Bayesian credible intervals. Journal of Statistical Planning and Inference 112:115−32

    doi: 10.1016/s0378-3758(02)00327-0

    CrossRef   Google Scholar

    [34]

    Bürkner PC. 2018. Advanced Bayesian multilevel modeling with the R package brms. The R Journal 10:395

    doi: 10.32614/rj-2018-017

    CrossRef   Google Scholar

    [35]

    Kutela B, Kidando E, Kitali AE, Mwende S, Novat N. 2023. Examining in-vehicle distraction sources in relation to crashes using a Bayesian Multinomial Logit model. Advances in Transportation Studies 61:3−18

    Google Scholar

    [36]

    Yoon B, Park Y. 2004. A text-mining-based patent network: analytical tool for high-technology trend. The Journal of High Technology Management Research 15:37−50

    doi: 10.1016/j.hitech.2003.09.003

    CrossRef   Google Scholar

    [37]

    Hong HS, Lee SK. 2021. Text network analysis of research topics and trends on global health nursing literature from 1974−2017. Journal of Advanced Nursing 77:1325−34

    doi: 10.1111/jan.14685

    CrossRef   Google Scholar

    [38]

    Kutela B, Novat N, Langa N. 2021. Exploring geographical distribution of transportation research themes related to COVID-19 using text network approach. Sustainable Cities and Society 67:102729

    doi: 10.1016/j.scs.2021.102729

    CrossRef   Google Scholar

    [39]

    Kutela B, Langa N, Mwende S, Kidando E, Kitali AE, et al. 2021. A text mining approach to elicit public perception of bike-sharing systems. Travel Behaviour and Society 24:113−23

    doi: 10.1016/j.tbs.2021.03.002

    CrossRef   Google Scholar

    [40]

    Paranyushkin D. 2012. Visualization of text's polysingularity using network analysis. https://api.semanticscholar.org/CorpusID:61464677

    [41]

    Kim Y, Jang SN. 2018. Mapping the knowledge structure of frailty in journal articles by text network analysis. PLoS One 13:e0196104

    doi: 10.1371/journal.pone.0196104

    CrossRef   Google Scholar

    [42]

    Kyriakidis M, Happee R, de Winter JCF. 2015. Public opinion on automated driving: results of an international questionnaire among 5000 respondents. Transportation Research Part F: Traffic Psychology and Behaviour 32:127−40

    doi: 10.1016/j.trf.2015.04.014

    CrossRef   Google Scholar

    [43]

    Hussain Q, Alhajyaseen WKM, Adnan M, Almallah M, Almukdad A, et al. 2021. Autonomous vehicles between anticipation and apprehension: investigations through safety and security perceptions. Transport Policy 110:440−51

    doi: 10.1016/j.tranpol.2021.07.001

    CrossRef   Google Scholar

    [44]

    Rahman MT, Dey K, Das S, Sherfinski M. 2021. Sharing the road with autonomous vehicles: a qualitative analysis of the perceptions of pedestrians and bicyclists. Transportation Research Part F: Traffic Psychology and Behaviour 78:433−45

    doi: 10.1016/j.trf.2021.03.008

    CrossRef   Google Scholar

  • Cite this article

    Lyimo SM, Kwigizile V, Kutela B, Asher ZD. 2024. Understanding perceptions of college students on the operation of automated shuttle for persons with disabilities on campus walkways. Digital Transportation and Safety 3(2): 36−45 doi: 10.48130/dts-0024-0004
    Lyimo SM, Kwigizile V, Kutela B, Asher ZD. 2024. Understanding perceptions of college students on the operation of automated shuttle for persons with disabilities on campus walkways. Digital Transportation and Safety 3(2): 36−45 doi: 10.48130/dts-0024-0004

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Understanding perceptions of college students on the operation of automated shuttle for persons with disabilities on campus walkways

Digital Transportation and Safety  3 2024, 3(2): 36−45  |  Cite this article

Abstract: Persons with disabilities have difficulties traveling from one point to the other due to the limited options of travel modes for the first and last mile. Western Michigan University tested using an autonomous shuttle on the main campus's sidewalks for persons with disabilities. This study's objectives are to understand the empathy college students without disabilities had on the need for suitable transportation services for students with disabilities and the perceived risks of the services' operation on sidewalks. The Bayesian ordered logit model and text mining analyzed 396 survey responses. The Bayesian ordered logistic regression results revealed that age, gender, and ethnicity are important factors that contribute to different opinions concerning perceived risks and sympathy brought by an autonomous shuttle operating on pedestrians' sidewalks. The text mining results revealed several patterns. While respondents who were against the operation focused on potential safety hazards and the crowdedness of the sidewalks, supporters focused on the expected improved mobility for people with disabilities. The findings from this study are expected to assist policymakers and vehicle manufacturers with pedestrian expectations and considerations related to risk and safety when sharing their walkways with the autonomous shuttle.

    • Accessibility to flexible transportation for persons with disabilities is currently a developing field. It can be very challenging for persons with disabilities, especially block-to-block movements when the distance is too long to walk and too short to drive. While persons without disabilities can choose whether to walk, bike, use scooters, or use skateboards over short distances, the disabled population is underserved in available transportation options[1,2]. Given the type of disability, persons with disabilities can be restricted to specific transportation modes such as walking or wheelchairs where infrastructure permits[3,4]. Public transportation is essential for most of this population[1,3,5]. Persons with disabilities have different transportation needs, even within the group. However, driver behavior is a common problem[6,7]. Fixed routes, public right of way, private taxicabs, flex service, and other nontraditional transit services are the primary ways transportation barriers in public transit can occur[8]. Barriers to transportation among persons with disabilities create a transportation inequality problem between persons with disabilities and those without disabilities.

      Autonomous vehicle technology can address the existing transportation barriers by expanding transportation options among persons with disabilities[1]. The new technology provides room to improve transportation services among persons with disabilities because it can promote transportation justice by providing door-to-door transportation services[911]. It will also increase transportation independence among persons with disabilities[12]. However, how traditional transportation mediums and individuals would interact with autonomous vehicles is unknown. Specifically, how active transportation will perceive, interact, and behave with autonomous vehicles remains nebulous.

      This study, therefore, intends to narrow the literature gap on this issue. The study focuses on understanding college students' perception of the autonomous shuttles on the walkways. Specifically, the study intends to understand how students perceive the service to people with disabilities and perceived risk when sharing the walkway with the shuttle. It is hypothesized that direct interaction with the shuttle would make a difference in terms of the risk but not in the service rendered by the shuttle. Several demographic factors are also considered for upscaled shuttle operations on other campuses. The study findings are expected to open opportunities for more testing of the service on other campuses to improve the movements of people with disabilities within campuses.

      The remainder of the manuscript is arranged as follows: The literature review summarizing previous work on the perception of autonomous vehicle adoption, their acceptance by people with disabilities, and factors that increased positive perception towards adopting autonomous technology. Next is the description of the material and methods used in achieving the study's objective, in which the data description and analytical analysis are explained. It is followed by a results and discussion section whereby a summary of results from the analysis is performed; namely, the Bayesian ordered logit model and the text network analysis are presented. A detailed discussion of the results and their interpretation is also presented. The conclusion section concludes and summarizes the main observation of the study and also documents some study limitations, and highlights areas for future research. Lastly, the data availability statement and list of references are presented.

    • Due to its benefits on the traffic stream, autonomous vehicle technology in the form of first/last mile shuttles is getting more attention from researchers and practitioners in providing mobility for persons with disabilities[13,14]. Post-alterations to the conventional vehicle are necessary for a person with disabilities to own an accessible vehicle privately. These alterations, in turn, increase the final price of the vehicle compared to unaltered. Associated low income among persons with travel-limiting disabilities might be an obstacle to owning these vehicles privately. Furthermore, no automobile manufacturer manufactures accessible vehicles for the disabled market massively[1]. Research shows that the technology will provide mobility solutions to persons with disabilities by giving door-to-door services that promote transportation justice[911]. Also, people with disabilities usually depend on other people's assistance. Autonomous vehicles are expected to increase their independence[12]. The needless driver in autonomous shuttles makes them suitable options for persons with disabilities[1,15]. Hence, reducing the driver's attitude problem is commonly reported to hinder the use of public transportation by persons with travel-limiting disabilities[6,7].

      Autonomous shuttles can address problems faced by persons with disabilities using public transportation services. For example, Mobility on Demand is a transportation service that is possible with autonomous shuttles[1618]. Comfort and increased independence are among a few benefits directly addressing the needs of persons with disabilities[11,19,20]. Literature shows that using autonomous vehicles to provide transportation services to persons with disabilities is getting some acceptance from persons with disabilities[13,14,21].

      A survey of people to study their willingness to use autonomous vehicles has been a widely used data collection tool in studying factors that impact people's perception and acceptance of autonomous vehicles[14,19,2124]. Research by Jinuk & Hwang[21] studied the perception of persons with disabilities on autonomous vehicles as a viable transportation option for mobility. It revealed that persons with disabilities were more accepting of autonomous vehicle transportation. More than 70% believed that autonomous vehicle transportation would solve the transportation problem faced by persons with disabilities and meet their travel needs[21]. In another study, about 15% of occasional public transit riders were willing to ride autonomous buses[14].

      Some preliminary evidence suggests variations in the public perception of autonomous vehicle technology. Payre et al. found a positive attitude toward adopting autonomous vehicles, whereas Haboucha et al. reported a great hesitation towards autonomous vehicle adoption. In the latter investigation, about 25% said they hesitated to travel with an autonomous vehicle even if the services were free[23,25]. Perceived usefulness, perceived safety risks, perceived ease of use, perceived private risks, initial trust, performance expectancy, users' enjoyment, and social influence are some factors that increased the positive attitude toward automated vehicles[24,2628]. A study by Zhang et al. established that the initial trust is enhanced by improving the perceived usefulness and reducing the perceived safety risks. However, people with disabilities were not considered in most of these studies[28].

      Furthermore, a significant number of the existing studies depend on the perceived perception of people who, in one way or another, have limited or absent experience with autonomous vehicles[23]. However, even for the few studies that investigate the interaction of pedestrians and AVs, they do so by testing an AV operating on the roadway; thus, the interaction studied is that when the pedestrian is crossing the road and not on any other areas such as pedestrian walkways[29]. There is a significant research gap evaluating a large group of non-users. Additionally, to the authors' knowledge, none of the previous studies have assessed the interaction of autonomous shuttles with pedestrians on pedestrian walkways. Due to the block-to-block type of transportation services to persons with disabilities, interaction with pedestrians is highly expected and unavoidable. Understanding how the public sympathizes with people with disabilities concerning the need for suitable and effective transportation, the usefulness of these shuttles', safety, comfort, and other factors is a critical research need to advance the technology. This research aimed to close the existing gap by analyzing people's perceptions of the usefulness and safety of the autonomous shuttle with an actual interaction with the shuttle. It also bridges the existing gap on the usefulness of the shuttle services for people with disabilities.

      Consideration of AVs for people with disabilities in campus settings is challenging. While the public might not be willing to share the sidewalk with AVs, their feelings towards the improved mobilities for people with disabilities may change their stand. However, to this point, scarce studies that evaluated such a possibility are available. Furthermore, reasons for people's perceptions of AV operations may differ significantly. With such a great variation, predefined responses make it difficult to capture many reasons. This scenario makes the case for the application of open-ended responses. The next section presents the materials and methods applied in this study.

    • This section presents the materials and methods used in this study. It covers data description, which shows how the data was collected, and analytical approaches, which show the applied methods to analyze the data.

    • This study used an observational survey conducted from November 1st to December 31st, 2019, among college students to understand their sympathy concerning the need for transportation services specifically for students with disabilities and to investigate the safety of the shuttle operating on pedestrian walkways. This shuttle was designed by researchers from Pratt and Miller Engineering, Western Michigan University (WMU), Comet Mobility, the University of Michigan, Easterseals, and Kevadiya (WMU, 2019). It specifically operated on pedestrian walkways to provide transportation services for students with disabilities from the campus's main bus stop to different classroom blocks. It ran on campus for 11 d from October 21st to November 1st, 2019. The survey collected perceptions from two groups of pedestrians. One group interacted with the shuttle, and the other did not interact with the shuttle.

      Since the shuttle operated on the WMU campus, only WMU students/members could participate in this study. The consistency within interaction and exposure of AV among participants allowed for a single perception assessment survey and legitimate aggregations and comparisons of perceptions. The survey was in English, and the team shared a blind link with participants via email. All participants must complete the survey individually and avoid undue coercion; no identifying information was collected. Participants were supposed to select either of the following responses: not at all, a little, a moderate amount, a lot, and a great deal.

      How do you compare the risk posed by an autonomous shuttle operating on a pedestrian walkway to that of a bicycle?

      How much sympathy did you feel for students with accessibility needs on campus who used this autonomous vehicle service?

      Further, respondents were supposed to rank their perceived risk of AV.

      On a scale of 1−5, where one represents not at all and five represents very high, what level of safety risk does an autonomous vehicle on pedestrian walkways on campus pose to you?

      In addition to the age, gender, and ethnicity of participants, respondents were also provided with a section to express their open-ended views. The question stated that.

      Please share your thoughts on how you feel regarding potentially having a fleet of such autonomous vehicles operating on campus.

    • The Bayesian Ordered Logit Model and Test Network Analysis (TNA) were used to quantify how different demographic factors impact respondents' likelihood of perceptions and perceptions of sympathy and risk related to using autonomous shuttles on campus for students with disabilities.

    • Due to the limited time of data collection, the number of responses collected was relatively low (N = 396), which, upon further cleaning, declined to N = 310. With such a small sample size, Bayesian analysis performs better than traditional frequentist analysis[30,31]. Thus, this study applied a Bayesian approach to analyze the collected data.

      Further, due to the ordinal nature of the responses collected, an ordered logistic regression was performed to investigate factors associated with the differences in the likelihood of pedestrians' perceptions[32]. For an ordinal outcome variable with N number of categories of the ordinal dependent variable, the generalized ordered logistic model is expressed as Eqn (1);

      P(Yi>j)=exp(αj+Xiβj)1+[exp(αj+Xiβj)],j=1,2,3,...N1 (1)

      The probability that Y will fall under any of the values 1 to N is given by Eqns (2)−(4):

      P(Yi=1)=1g(Xiβj) (2)
      P(Yi=j)=g(Xiβj1)g(Xiβj),j=2,3,...N1 (3)
      P(Yi=1)g(XiβN1) (4)

      In the Bayesian approach, priors must consider what is already known. Since no study has analyzed similar data to answer the questions, weakly informative priors (Normal (0,10)) were used[33]. The analysis was performed in the R environment using the brms package[34]. The analysis was performed in four chains with 200 iterations during warm-up and 4000 iterations post-warm-up.

      The results are interpreted based on the estimates and credible intervals. Positive estimates are associated with higher ranking, while the opposite is true for negative estimates. Credible intervals are used to determine the credibility of the results[33,35].

      In addition to the Bayesian Ordered Logit model, the open-ended responses provided an opportunity to understand why students either support or oppose the operation of autonomous shuttles.

    • Open-ended responses were used to understand the reasons for supporting or opposing the autonomous shuttle's operation. The TNA utilized nodes and arcs to expose the hidden pattern of keywords and connections among them[3638]. Figure 1 presents a typical structure of the text network. The nodes represent keywords in this figure, while the links indicate co-occurrence. The distance between two nodes corresponds to the distance between keywords in the open-ended response. Keywords that appear next to each other are called collocated keywords and provide richer insights than co-occurring or single keywords. Furthermore, several keywords with similar themes are grouped to form a community[39,40].

      Figure 1. 

      A typical example of a text network.

      Creating a network requires three main processes: normalization, transformation, and mapping. Normalization involves formatting responses to lower cases, removing special characters, and connecting words. Transformation covers changing the unstructured to structured data. In this process, the open-response text is converted into matrices of keywords with their associated frequencies. Lastly, the keywords are mapped. In this stage, the keywords are mapped from the matrices created in the previous stage[38,40,41].

      The text network results can be interpreted based on keyword frequency, co-occurred frequency, collocated frequency, degree, centrality, and betweenness centrality, among other factors. However, keyword frequency and collocated keywords are used[36,39]. Only the top 50 most frequent keywords are mapped for computation time and power for analysis.

    • This section presents the results and discussion of the analyses conducted. These include descriptive statistics that provide a general picture of response distribution, the MWU test results, and the Bayesian ordered logistics results.

    • Three hundred ninety-six pedestrians responded to the question asked, of which 148 (37.4%) identified as males and 111 (28%) as females. In addition, about 61.9% of the respondents were pedestrians aged 18−26 years, and 49% were Caucasians. The number of respondents for each question differed depending on the type of questions asked. About 47.2% (187 pedestrians) responded to the question about their sympathy toward using autonomous shuttle services for students with disabilities, and 310 pedestrians (78.3%) responded to the question about the perceived risk of the AV shuttle operating on the sidewalk compared to bicycles—moreover, the question related to the perceived risk of AV shuttles to pedestrians. Table 1 shows the rich demographic distribution of the participants.

      Table 1.  Descriptive analysis results.

      Variable Category Sympathy
      (N = 187)
      Risk to pedestrian
      (N = 310)
      Risk (shuttle vs bicycle
      (N = 310)
      Gender Male 103 146 146
      Female 69 111 111
      Didn't respond 15 53 53
      Ethnicity Caucasian 133 192 192
      Others 38 63 63
      Didn't respond 16 55 55
      Age 18–26 years 174 244 244
      Others 10 34 34
      Didn't respond 3 32 32

      Further, the influence of the interaction with the shuttle was also evaluated in terms of sympathy and risk. Among the respondents, 214 (54%) interacted with the shuttle. Figure 2 shows the distribution of sympathy ratings and ratings by shuttle interaction. It can be observed that respondents who interacted with the shuttle showed a high level of sympathy for people with disabilities, as indicated by the size of the 'a great deal' and 'a lot' categories of sympathy. Further, a relatively large number of respondents who felt either a lot of sympathy or a great deal felt that operating the shuttle was risky to pedestrians. Furthermore, people who felt lower risk levels to pedestrians also showed either moderately lower or much lower risk of the shuttle on the sidewalk compared to the bicycle.

      Figure 2. 

      Ratings of the sympathy and ratings by shuttle interaction.

    • Bayesian Ordered Logistic regression was performed for each question against explanatory variables, as presented in Table 2. For analysis purposes, gender, age, interaction with the autonomous vehicle, and ethnicity were used as binary independent variables. A reference group was created and used for each independent variable. Each survey response was treated as a dependent variable.

      Table 2.  Bayesian ordered regression model results.

      VariableEstimateOREst.
      Error
      [95% CI]EstimateOREst.
      Error
      [95% CI]EstimateOREst.
      Error
      [95% CI]
      SympathyRisk to pedestrianRisk (shuttle vs bicycle)
      Gender
      Female
      Male−0.530.590.29−1.10.04−0.450.640.23−0.91−0.01−0.410.660.23−0.870.05
      Age group (years)
      18–25
      > 25−1.590.200.82−3.28−0.040.111.120.39−0.650.880.421.520.41−0.361.24
      Ethnicity
      Caucasian
      Non-Caucasian0.72.010.350.031.39−0.560.570.28−1.13−0.02−0.540.580.27−1.07−0.01
      Model summary
      /cut1−3.370.030.89−5.15−1.66−0.960.380.43−1.8−0.11−1.730.180.46−2.64−0.82
      /cut2−2.590.080.89−4.4−0.890.421.520.43−0.411.27−0.190.830.45−1.050.7
      /cut3−1.410.240.88−3.190.271.494.440.440.652.371.022.770.450.151.92
      /cut4−0.130.880.87−1.891.542.5813.200.511.63.592.8817.810.521.893.97
      CI = Credible interval, OR = Odds Ratio, Est Error = Estimated error.

      Table 2 presents factors that influence the differences in pedestrian perceptions of the attributes of autonomous shuttles. The 95% credible interval was considered in this study. Other variables were added to the table for comparison purposes.

      Results show that gender, age, and ethnicity are important factors contributing to differences in perceptions of the operation of the autonomous shuttle for people with disabilities in the three independent variables studied, specifically the importance of the AV shuttle to students with disabilities, the perceived risk of sidewalk operation of an autonomous shuttle on a pedestrian, and risk comparison between an autonomous shuttle and a bicycle on a sidewalk. It was revealed that while ethnicity was important in explaining the differences in perceptions of the three studied categories, gender, and age were significant in only one of the three independent variables.

      Gender was a significant factor in the perceived risk of autonomous shuttles, and results show that males are 36% less likely than females to perceive high risks of autonomous shuttles on pedestrians. Although gender was not a significant factor at a 95% credible interval on the usefulness of the autonomous, results indicate that male pedestrians are 41% less likely than female pedestrians to perceive the autonomous shuttle as useful among students with a disability. Males are also 37% less likely than females to perceive higher autonomous shuttle risks than bicyclists operating on sidewalks.

      Further, the study revealed that while age is not a significant factor in perceptions of risks of autonomous vehicles to pedestrians, gender and ethnicity were. Results show that male pedestrians were 36% less likely than females to perceive higher risks to pedestrians by an autonomous shuttle operating on sidewalks. In addition, non-Caucasian pedestrians are 43% less likely than Caucasians to perceive higher risks to pedestrians by an autonomous shuttle operating on sidewalks.

      Regarding the perceived risks imposed by an autonomous shuttle to risks imposed by a bicycle operating on a sidewalk, results revealed that gender and ethnicity were the only determinant factors. Specifically, it was found that male pedestrians were 34% less likely to perceive higher risks of autonomous shuttles compared to bicycles than female pedestrians. It was also revealed that Caucasian pedestrians have lower odds (42% less likely) of perceiving higher risks of autonomous shuttles compared to bicycles than other ethnicities.

      Similar results were also observed in the previous studies[14,20,22,42,43]. A survey by Hulse et al. revealed that age was among the factors associated with differences in people's perceptions. In their study, young adults accepted significantly autonomous cars[14,20]. A study by Battistini et al., who investigated contributing factors in autonomous shuttles (AS) for tourist purposes, revealed that gender and age were significant factors in users' perceptions of using the shuttle as a daily commute. Specifically, age was a significant factor in users' perceptions of using the shuttle as a daily commute; however, it was not an important factor in using the shuttle as tourism[22]. Further, a survey conducted among residents of the State of Qatar on the safety concerns of autonomous vehicles revealed that, compared to Arabs, non-Arabs reported higher concerns[43]. However, these studies did not focus on the perceived use of autonomous vehicles by people with disabilities.

      The regression results provided the association between various aspects of autonomous shuttle operations on campus to provide services to students with disabilities. However, the results from open-ended questions were deemed necessary to understand the insights from the actual discussions. The next section presents the text network results.

    • The text network results cover the overall perceived risks for pedestrians, perceived risks comparable to bicycles, and the sympathy for the people with disabilities who utilized the autonomous shuttle. Respondents with a scale of 4 and 5 were considered risky for the overall perceived risk to pedestrians, while the rest considered the autonomous shuttle as not risky. Considering the sympathy level, 'a great deal' and 'a lot' were considered high, while 'a little' and 'not' was considered low. Further, compared with bicycles, 'much' and 'moderately higher' were considered risky.

    • Figure 3 presents the text network for responses to the perceived risk to pedestrians. According to the networks, a relatively small number of people perceived that the AVs are risky to pedestrians, as indicated by the denseness of the network. The network for the respondents who feel that the AV is dangerous to pedestrians focused on multiple issues, as indicated by the co-located and co-occurring keywords. The accessibility issue is one of the main focus points for this group. They perceived that operating AVs on walkways would solve accessibility issues for people with disabilities, but they did not feel safe interacting with them. The typical response stated: 'If it helps students with disabilities and accessibility issues, then it should be implemented for that only. They must be responsibly monitored and controlled to make it safe'. Previous studies have reported similar findings regarding AV interactions with pedestrians[44]. However, such studies did not involve people with disabilities.

      Figure 3. 

      Text networks and collocated keywords for perceived risk to pedestrians. (a) Text network for AV as risky to pedestrians, (b) collocated keywords for AV as risky to pedestrians, (c) text Network for AV as not risky to pedestrians, (d) collocated keywords for AV as not risky to pedestrians.

      Furthermore, other respondents compared the AVs operating against the golf carts as indicated by the keywords golf carts. Respondents feel that the AV won't be any better than golf carts, "…I do not see the advantage of using autonomous vehicles over golf carts, though. Wouldn't golf carts be cheaper? And doesn't the autonomous vehicle require a person to be able to operate it?...". Other respondents showed concerns that, as it stands, the walkways are already crowded with other fleets, which makes operating AV more crowding the sidewalks: "Campus pathways are already crowded enough without a fleet of bulky, slow, ugly, and sidewalk-obscuring vehicles."

      On the other hand, people who perceived it as not risky to pedestrians thought it was a great idea, especially for students with disabilities. Most comments pointed toward their greatness to disabled people but cautioned on their operations. Some people talked about hitting pedestrians. A typical response states: 'I think it would be a good idea given they stop if someone is standing in the way or at least slow down as not to hit them. I think it's a great idea for students with disabilities' and 'I don't mind them, but it would make bikes have to pass them and possibly hit a pedestrian'. Others had issues with the number of AVs operating, as indicated by the keyword fleet in Fig. 3c. One of the associated comments stated: 'Depending on the size of 'a fleet', I'd say the realistic risk is that a student may be looking at their phone and not notice a vehicle after turning a corner'.

    • Figure 4 shows the text network for comparable risks of AV to bicycles on the sidewalks. People who feel that AVs are riskier pointed to the crowd-ness of the walkways, arguing that additional fleets of AVs will make things worse. For example, '…Campus sidewalks are already overcrowded with current construction projects claim some pathways and alternate routes to buildings...'. Others thought adding a fleet would increase tuition, which is a waste of money. For example, '…I don't think these vehicles are of good interest or good for money being spent on the vehicles. These will cause the tuition to increase even more and are not needed'.

      Figure 4. 

      Text networks and collocated keywords for perceived risk of AV compared to bicycles. (a) Text network for AV as risky compared to bicycles, (b) collocated keywords for AV were found to be risky compared to bicycles, (c) text network for AV is not risky compared to bicycles, (d) collocated keywords for AV are not risky compared to bicycles.

      On the contrary, people who support the idea think it is great for disabled people and doesn't have much impact compared to a bicycle. The keyword sidewalk is the main topic in Fig. 4c since the discussion concerns the sidewalks. At least ten people mentioned sidewalks in their responses. Some pointed to already crowded sidewalks, others to the people's behavior on sidewalks. There is also a comparison between AVs and golf carts: '…I also think having a fleet of autonomous vehicles would not be more dangerous than having a fleet of golf carts and maybe less dangerous than bicyclists on the sidewalk…'. A sample of comments that showed the greatness of the shuttles stated: 'Great for accessibility and convenience for disabled students, curious to see how it affects bicycle traffic more than foot traffic', and '…The bikers on campus are terrible, I've almost been hit three times this semester'.

    • Lastly, Fig. 5 presents the text networks of the sympathy level for people with disabilities. According to respondents with a high level of sympathy for people with disabilities (Fig.5a & b), operating an AV on the sidewalk is fine as long as it doesn't hit pedestrians. The fleet doesn't pose much safety risk as indicated by the keyword pose, much, and risk. A typical statement states: '…… What I've seen it's not too fast and poses little risk to pedestrians. And it is only a little annoying to walk around if it's blocking your path to class (but not a big deal)'. Some would be happy to see these fleets: 'I would be happy to see a fleet of autonomous vehicles'. However, others cautioned about the possible risks posed by AV operations, although they think it is a good idea for disabled people.

      Figure 5. 

      Text networks and collocated keywords for perceived sympathy level. (a) Text network for high sympathy level, (b) top collocated keywords for high sympathy level, (c) text network for low sympathy level, (d) top collocated keywords for low sympathy level.

      Furthermore, although some people showed low sympathy levels (Fig. 5c & d), they still think that it is a great idea that would benefit people with disabilities. Responses such as: 'I wouldn't mind if it helped people who needed it to get to class' signify such a sentiment. However, they warn about pedestrian obstruction, as indicated in one of the responses: 'If they don't obstruct pedestrians from walking, it is a valid idea'.

    • This paper analyzed pedestrians' perceptions of the safety risks of an autonomous shuttle operating on the WMU campus' pedestrian walkways. It leverages perceptual data towards autonomous shuttles to elucidate how using autonomous technology to solve mobility challenges can create safety concerns for other individuals not directly benefiting from the technology. Results show that actual interaction with the shuttle, age, ethnicity, and gender are significant factors affecting the pedestrian perception of the shuttle impacts. In summary, the results revealed the following.

      • Compared to females, males are 41% less likely to perceive higher sympathy towards using autonomous shuttles for students with disabilities.

      • Younger pedestrians are 78% less likely than adult pedestrians to perceive the shuttle as more important to students with disabilities.

      • Caucasians are two times more likely than other ethnicities to perceive higher levels of importance of the shuttle to students with disabilities.

      • Male pedestrians were 36% less likely than females to perceive higher-risk pedestrians by an autonomous shuttle operating on sidewalks.

      • Caucasian pedestrians were 43% less likely than other races to perceive higher risks to pedestrians by an autonomous shuttle operating on sidewalks.

      • Male pedestrians were 34% less likely than female pedestrians to perceive higher risks of autonomous shuttles compared to bicycles.

      • Caucasian pedestrians were 42% less likely than other ethnicities to perceive higher risks of autonomous shuttles than bicycles.

      On the other hand, the text mining results showed several reasons for accepting or rejecting the operation of the autonomous shuttle on the sidewalks. Safety and inconvenience were among the key attributes. Further, respondents showed that the sidewalks are already crowded, which means the operations of autonomous shuttles will complicate sidewalk accessibility even more.

      Results from this research can be used to understand the pedestrian perception of autonomous vehicle operation. It addresses the non-user gap in the body of knowledge. In addition, it highlights the potential of these services to bring about transportation equity to people with disability specifically in providing end-mile transportation services (transportation on a distance that is too short to drive but too far to walk by a person with a disability). The findings from this investigation are expected to assist policymakers and vehicle manufacturers with pedestrian expectations and considerations related to risk and safety when sharing their walkways with the shuttle. Given that the study was performed on a college campus, the results presented here will also provide the impetus for further exploration of using pedestrian walkways on large campuses for autonomous vehicles to support student accessibility needs. A clear understanding of the associated risks of these types of shuttles paves the way to mobility provision to persons with disabilities for block-to-block movements.

      Lastly, given the design of this study, causality cannot be ascertained due to a lack of experimental control. However, the uniqueness of deploying an actual autonomous shuttle and capturing non-users perceptions lends high ecological and external validity to the results presented in this study. These psychological investigations are typically only in controlled environments that compromise generalizability; thus, the authors collected data from a large and diverse sample of participants. Nevertheless, future research should seek to cross-validate the results reported in this study through controlled experimentations with high internal validity. Further, since the current research focused on the university campus, additional research is needed on using pedestrian walkways in other areas for autonomous shuttles to provide block-to-block mobility to persons with travel-limiting disabilities.

    • The authors confirm their contribution to the paper as follows: study conception and design: Lyimo SM, Kwigizile V, Asher ZD; data collection: Lyimo SM; analysis and interpretation of results: Lyimo SM, Kutela B, Kwigizile V; draft manuscript preparation: Lyimo SM, Kutela B, Kwigizile V. All authors reviewed the results and approved the final version of the manuscript.

    • The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

    • The author wishes to acknowledge the contribution of Johan Fanas Rojas, PhD, and his 2018 Michigan Mobility Challenge team in making this study possible.

      • The authors declare that they have no conflict of interest.

      • Copyright: © 2024 by the author(s). Published by Maximum Academic Press, Fayetteville, GA. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (5)  Table (2) References (44)
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    Lyimo SM, Kwigizile V, Kutela B, Asher ZD. 2024. Understanding perceptions of college students on the operation of automated shuttle for persons with disabilities on campus walkways. Digital Transportation and Safety 3(2): 36−45 doi: 10.48130/dts-0024-0004
    Lyimo SM, Kwigizile V, Kutela B, Asher ZD. 2024. Understanding perceptions of college students on the operation of automated shuttle for persons with disabilities on campus walkways. Digital Transportation and Safety 3(2): 36−45 doi: 10.48130/dts-0024-0004

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