[1]

Shang T, Lian G, Xie L, Zhou A. 2023. Research on key parameters of the Fatigue Arousal Zone in extra-long tunnels based on natural driving experiments. Digital Transportation and Safety 2(4):284−97

doi: 10.48130/DTS-2023-0024
[2]

Zhang X, Tang J, Huang H, Chang F, Wang J, et al. 2022. An analysis of influential factors of crashes at tunnels and open sections of mountainous freeways. Journal of Transport Information and Safety 40(3):10−18

doi: 10.3963/j.jssn.1674-4861.2022.03.002
[3]

Shao X, Chen F, Ma X, Pan X. 2022. The impact of lighting and longitudinal slope on driver behaviour in underwater tunnels: A simulator study. Tunnelling and Underground Space Technology 122:104367

doi: 10.1016/j.tust.2022.104367
[4]

Zhang T, Chen F, Huang Y, Song M, Hu X. 2022. Analysis of car-following behaviors under different conditions on the entrance section of cross-river and cross-sea tunnels: a case study of Shanghai Yangtze River Tunnel. International Journal of Environmental Research and Public Health 19:11975

doi: 10.3390/ijerph191911975
[5]

Chen Z, Xu W, Qu Y, Chen W. 2019. Severity of traffic crashes on freeways based on mixed logit model. Journal of Transport Information and Safety 37(3):42−50

doi: 10.3963/j.issn.1674-4861.2019.03.006
[6]

Ma C, Zhao Y, Dai G, Xu X, Wong SC. 2023. A Novel STFSA-CNN-GRU Hybrid Model for Short-Term Traffic Speed Prediction. IEEE Transactions on Intelligent Transportation Systems 24(4):3728−37

doi: 10.1109/TITS.2021.3117835
[7]

Yan Y, Dai Y, Li X, Tang J, Guo Z. 2019. Driving risk assessment using driving behavior data under continuous tunnel environment. Traffic Injury Prevention 20(8):807−12

doi: 10.1080/15389588.2019.1675154
[8]

Singh H, Kathuria A. 2021. Analyzing driver behavior under naturalistic driving conditions: A review. Accident Analysis & Prevention 150:105908

doi: 10.1016/j.aap.2020.105908
[9]

Li W, Huang J, Xie G, Karray F, Li R. 2021. A survey on vision-based driver distraction analysis. Journal of Systems Architecture 121:102319

doi: 10.1016/j.sysarc.2021.102319
[10]

Huang Y, Chen F, Song M, Pan X, You . 2023. Effect evaluation of traffic guidance in urban underground road diverging and merging areas: A simulator study. Accident Analysis & Prevention 186:107036

doi: 10.1016/j.aap.2023.107036
[11]

Du Z, Pan X, Yang Z, Guo X. 2007. Research on visual turbulence and driving safety of freeway tunnel entrance and exit. China Journal of Highway and Transport 20(5):101−5

doi: 10.3321/j.issn:1001-7372.2007.05.018
[12]

Wang S, Du Z, Jiao F, Zheng H, Ni Y. 2020. Drivers’ visual load at different time periods in entrance and exit zones of extra-long tunnel. Traffic Injury Prevention 21(8):539−44

doi: 10.1080/15389588.2020.1821196
[13]

Jiao F, Du Z, Wang S, Ni Y, He R. 2020. Drivers' saccade characteristics in curves of extra-long urban underwater tunnels. Transportation Research Record 2674(2):102−11

doi: 10.1177/0361198120904643
[14]

Wu S, Chen Z, Zhang G, Chen Q, Xu J. 2023. Freeway trajectory deviation and lane lateral margin based on real vehicle data. China Journal of Highways 36(5):197−209

doi: 10.3969/j.issn.1001-7372.2023.05.017
[15]

Wang X, Liu Q, Guo F, Fang SE, Xu X, et al. 2022. Causation analysis of crashes and near crashes using naturalistic driving data. Accident Analysis & Prevention 177:106821

doi: 10.1016/j.aap.2022.106821
[16]

Vashitz G, Shinar D, Blum Y. 2008. In-vehicle information systems to improve traffic safety in road tunnels. Transportation Research Part F Traffic Psychology & Behaviour 11(1):61−74

doi: 10.1016/j.trf.2007.07.001
[17]

Feng Z, Yang M, Zhang W, Du Y, Bai H. 2018. Effect of longitudinal slope of urban underpass tunnels on drivers’ heart rate and speed: A study based on a real vehicle experiment. Tunnelling and Underground Space Technology 81:525−33

doi: 10.1016/j.tust.2018.08.032
[18]

Zhao X, Dong W, Li J, Liu Q, Ju Y. 2022. How does the mural decoration of the long tunnel sidewall affect the driver's speed control ability? Tunnelling and Underground Space Technology 130:104731

doi: 10.1016/j.tust.2022.104731
[19]

Pan F, Wu Q, Wang Z, Wang L, Zhang L, et al. 2022. Effectiveness evaluation of optical illusion deceleration markings for a V-shaped undersea tunnel based on the set pair analysis me thod and the technique for order preference by similarity to ideal solution theory. Transportation Research Record: Journal of the Transportation Research Board 2677:308−2

doi: 10.1177/03611981221130326
[20]

Li Z, Xing G, Zhao X, Li H. 2021. Impact of the connected vehicle environment on tunnel entrance zone. Accident Analysis & Prevention 157:106145

doi: 10.1016/j.aap.2021.106145
[21]

Niu JA, Liang B, Wong YD, He S, Qin C, et al. 2024. Dynamic traffic safety risk assessment in road tunnel entrance zone based on drivers' psychophysiological perception states: Methodology and case-study insights. Tunnelling and Underground Space Technology 147:105677

doi: 10.1016/j.tust.2024.105677
[22]

Ma C, Zhou J, Yang D, Fan Y. 2020. Research on the relationship between the individual characteristics of electric bike riders and illegal surpassing behavior: a questionnaire-based study. Sustainability 12(3):799

doi: 10.3390/su12030799