Prediction of driving stress on high-altitude expressway using driving environment features: A naturalistic driving study in Tibet

References

• Agrawal S, Peeta S. 2021. Evaluating the impacts of situational awareness and mental stress on takeover performance under conditional automation. Transp Res Pt F Traffic Psychol Behav. 83:210–225. doi:10.1016/j.trf.2021.10.002.
   Web of Science ®Google Scholar
• Antoun M, Ding D, Bohn-Goldbaum EE, Michael S, Edwards KM. 2018. Driving in an urban environment, the stress response and effects of exercise. Ergonomics. 61(9):1273–1281. doi:10.1080/00140139.2018.1468494.
   PubMed Web of Science ®Google Scholar
• Cai Q, Abdel-Aty M, Zheng O, Wu YN. 2022. Applying machine learning and google street view to explore effects of drivers’ visual environment on traffic safety. Transp Res Pt C Emerg Technol. 135:103541. doi:10.1016/j.trc.2021.103541.
   Web of Science ®Google Scholar
• Chen CX, Li HW, Luo WJ, Xie JH, Yao J, Wu LF, Xia Y. 2022. Predicting the effect of street environment on residents’ mood states in large urban areas using machine learning and street view images. Sci Total Environ. 816:151605. doi:10.1016/j.scitotenv.2021.151605.
   PubMed Web of Science ®Google Scholar
• Chen LL, Zhao Y, Ye PF, Zhang J, Zou JZ. 2017. Detecting driving stress in physiological signals based on multimodal feature analysis and kernel classifiers. Expert Syst Appl. 85:279–291. doi:10.1016/j.eswa.2017.01.040.
   Web of Science ®Google Scholar
• Dai LY, Zheng CL, Dong ZK, Yao Y, Wang RF, Zhang XT, Ren SL, Zhang JQ, Song XQ, Guan QF. 2021. Analyzing the correlation between visual space and residents’ psychology in Wuhan, China using street-view images and deep-learning technique. City Environ Interact. 11:11. doi:10.1016/j.cacint.2021.100069.
   Google Scholar
• Du ZG, Wan HL, Wu CZ, Pan XD. 2014. Safety evaluation of highway tunnel-entrance illuminance transition based on eye-pupil changes. PROMET. 26(5):363–370. doi:10.7307/ptt.v26i5.1321.
   Google Scholar
• Goumopoulos C, Stergiopoulos NG, et al. 2022. Chapter 12—mental stress detection using a wearable device and heart rate variability monitoring. In: Sridhar R, Gangadharan GR, Sheng M, editors. Edge-of-things in personalized healthcare support systems. London (UK): Academic Press; p. 261–290.
   Google Scholar
• Hao TT, Zheng X, Wang HY, Xu KL, Chen SK. 2022. Linear and nonlinear analyses of heart rate variability signals under mental load. Biomed Signal Process Control. 77:103758. doi:10.1016/j.bspc.2022.103758.
   Web of Science ®Google Scholar
• Heikoop DD, de Winter JCF, van Arem B, Stanton NA. 2019. Acclimatizing to automation: driver workload and stress during ­partially automated car following in real traffic. Transp Res Pt F Traffic Psychol Behav. 65:503–517. doi:10.1016/j.trf.2019.07.024.
   Web of Science ®Google Scholar
• Helbich M, Yao Y, Liu Y, Zhang JB, Liu PH, Wang RY. 2019. Using deep learning to examine street view green and blue spaces and their associations with geriatric depression in Beijing, China. Environ Int. 126:107–117. doi:10.1016/j.envint.2019.02.013.
   PubMed Web of Science ®Google Scholar
• Horn JL. 1965. A rationale and test for the number of factors in factor-analysis. Psychometrika. 30(2):179–185. doi:10.1007/bf02289447.
   PubMed Web of Science ®Google Scholar
• Hu JB, Yang Y. 2011. Safety of driving behavior on low-volume roads in China case study of Qinghai-Tibet Highway. Transp Res Rec. 2203(1):100–105. doi:10.3141/2203-13.
   Google Scholar
• Ito K, Biljecki F. 2021. Assessing bikeability with street view imagery and computer vision. Transp Res Pt C Emerg Technol. 132:103371. doi:10.1016/j.trc.2021.103371.
   Web of Science ®Google Scholar
• Jones C, Lins Menêses A, Askew C, Scott-Parker B. 2021. The impact of courteous and discourteous drivers on physiological stress. Transp Res Pt F Traffic Psychol Behav. 82:285–296. doi:10.1016/j.trf.2021.08.015.
   Web of Science ®Google Scholar
• Karinen HM, Peltonen JE, Kähönen M, Tikkanen HO. 2010. Prediction of acute mountain sickness by monitoring arterial oxygen saturation during ascent. High Alt Med Biol. 11(4):325–332. doi:10.1089/ham.2009.1060.
   PubMed Web of Science ®Google Scholar
• Ledesma RD, Ferrando PJ, Trógolo MA, Poó FM, Tosi JD, Castro C. 2021. Exploratory factor analysis in transportation research: current practices and recommendations. Transp Res Pt F Traffic Psychol Behav. 78:340–352. doi:10.1016/j.trf.2021.02.021.
   Web of Science ®Google Scholar
• Li XJ, Cai BY, Qiu WS, Zhao JH, Ratti C. 2019. A novel method for predicting and mapping the occurrence of sun glare using Google Street View. Transp Res Pt C Emerg Technol. 106:132–144. doi:10.1016/j.trc.2019.07.013.
   Web of Science ®Google Scholar
• Lim S, Jahng S. 2019. Determining the number of factors using parallel analysis and its recent variants. Psychol Methods. 24(4):452–467. doi:10.1037/met0000230.
   PubMed Web of Science ®Google Scholar
• Lu Y, Fu XS, Guo EQ, Tang F. 2021. XGBoost algorithm-based monitoring model for urban driving stress: combining driving behaviour, driving environment, and route familiarity. IEEE Access. 9:21921–21938. doi:10.1109/ACCESS.2021.3055551.
   Web of Science ®Google Scholar
• Mehri A, Sajedifar J, Abbasi M, Naimabadi A, Mohammadi AA, Teimori GH, Zakerian SA. 2019. Safety evaluation of lighting at very long tunnels on the basis of visual adaptation. Saf Sci. 116:196–207. doi:10.1016/j.ssci.2019.03.018.
   Web of Science ®Google Scholar
• Mou LT, Zhou C, Zhao PF, Nakisa B, Rastgoo MN, Jain R, Gao W. 2021. Driver stress detection via multimodal fusion using attention-based CNN-LSTM. Expert Syst Appl. 173:114693. doi:10.1016/j.eswa.2021.114693.
   Web of Science ®Google Scholar
• National Bureau of Statistics. 2012–2020. China statistical yearbook. [accessed 2024 Jan 31]. https://www.stats.gov.cn/sj/ndsj/.
   Google Scholar
• Nees MA, Herwig K, Quigley L, Zhang JW. 2021. Relationships among driving styles, desire for control, illusion of control, and self-reported driving behaviors. Traffic Inj Prev. 22(5):372–377. doi:10.1080/15389588.2021.1909728.
   PubMed Web of Science ®Google Scholar
• Noh Y, Kim S, Yoon Y. 2019. Evaluation on diversity of drivers’ cognitive stress response using EEG and ECG signals during real-traffic experiment with an electric vehicle. IEEE Intelligent Transportation Systems Conference (IEEE-ITSC); October 27–30, 2019; Auckland, New Zealand. New York: IEEE.
   Google Scholar
• Paschalidis E, Choudhury CF, Hess S. 2018. Modelling the effects of stress on gap-acceptance decisions combining data from driving simulator and physiological sensors. Transp Res Pt F Traffic Psychol Behav. 59:418–435. doi:10.1016/j.trf.2018.09.019.
   Web of Science ®Google Scholar
• Qin PC, He J, Zhang CJ, Ye YT, Zhang H, Wang MN, Yan T. 2023. How does an extra-long freeway tunnel influence driving performance? A comparative study of driving simulation. KSCE J Civ Eng. 27(9):4043–4059. doi:10.1007/s12205-023-0423-3.
   Web of Science ®Google Scholar
• Qin PC, Wang MN, Chen ZW, Yan GF, Yan T, Han CL, Bao YF, Wang X. 2021. Characteristics of driver fatigue and fatigue-relieving effect of special light belt in extra-long highway tunnel: a real-road driving study. Tunn Undergr Space Technol. 114:103990. doi:10.1016/j.tust.2021.103990.
   Web of Science ®Google Scholar
• Qu WN, Zhang Q, Zhao WG, Zhang K, Ge Y. 2016. Validation of the Driver Stress Inventory in China: relationship with dangerous driving behaviors. Accid Anal Prev. 87:50–58. doi:10.1016/j.aap.2015.11.019.
   PubMed Web of Science ®Google Scholar
• Rastgoo MN, Nakisa B, Maire F, Rakotonirainy A, Chandran V. 2019. Automatic driver stress level classification using multimodal deep learning. Expert Syst Appl. 138:112793. doi:10.1016/j.eswa.2019.07.010.
   Web of Science ®Google Scholar
• Rastgoo MN, Nakisa B, Rakotonirainy A, Chandran V, Tjondronegoro D. 2019. A critical review of proactive detection of driver stress levels based on multimodal measurements. ACM Comput Surv. 51(5):1–35. doi:10.1145/3186585.
   Web of Science ®Google Scholar
• Shakouri M, Ikuma LH, Aghazadeh F, Nahmens I. 2018. Analysis of the sensitivity of heart rate variability and subjective workload measures in a driving simulator: the case of highway work zones. Int J Ind Ergon. 66:136–145. doi:10.1016/j.ergon.2018.02.015.
   Web of Science ®Google Scholar
• Shen Y, Yang Y-Q, Liu C, Yang J, Zhang J-H, Jin J, Tan H, Yuan F-Z-Y, Ke J-B, He C-Y, et al. 2021. Association between physiological responses after exercise at low altitude and acute mountain sickness upon ascent is sex-dependent. Mil Med Res. 7(1):53. doi:10.1186/s40779-020-00283-3.
   Web of Science ®Google Scholar
• Tavakoli A, Lai NT, Balali V, Heydarian A. 2023. How are drivers’ stress levels and emotions associated with the driving context? A naturalistic study. J Transp Health. 31:101649. doi:10.1016/j.jth.2023.101649.
   Web of Science ®Google Scholar
• Turner CE, Barker-Collo SL, Connell CJW, Gant N. 2015. Acute hypoxic gas breathing severely impairs cognition and task learning in humans. Physiol Behav. 142:104–110. doi:10.1016/j.physbeh.2015.02.006.
   PubMed Web of Science ®Google Scholar
• Wang CZ, Chen F, Zhu JY, Cheng JC, Bo W, Zhang P. 2022. Analysis on hazard perception ability of drivers in plateau areas: by different elevations. Can J Civ Eng. 49(7):1272–1280. doi:10.1139/cjce-2021-0437.
   Web of Science ®Google Scholar
• Wang CZ, Easa SM, Chen F, Cheng JC. 2023. Difference in perception-reaction time of plain and plateau drivers at expressway exit ramps. Transp Res Pt F Traffic Psychol Behav. 98:318–336. doi:10.1016/j.trf.2023.09.016.
   Web of Science ®Google Scholar
• Wang JS, Lin CW, Yang YTC. 2013. A k-nearest-neighbor classifier with heart rate variability feature-based transformation algorithm for driving stress recognition. Neurocomputing. 116:136–143. doi:10.1016/j.neucom.2011.10.047.
   Web of Science ®Google Scholar
• Watkins MW. 2018. Exploratory factor analysis: a guide to best practice. J Black Psychol. 44(3):219–246. doi:10.1177/0095798418771807.
   Web of Science ®Google Scholar
• Xu D, Fang S, Chen Y, Zhuang J. 2019. Influencing factors of truck operating speed at high altitude area. J Transp Syst Eng Inf Technol. 19(4):246–251. doi:10.16097/j.cnki.1009-6744.2019.04.035.
   Google Scholar
• Yan GF, Wang MN, Qin PC, Yan T, Bao YF, Wang X. 2022. Comparative study on drivers’ eye movement characteristics and psycho-physiological reactions at tunnel entrances in plain and high-altitude areas: a pilot study. Tunn Undergr Space Technol. 122:104370. doi:10.1016/j.tust.2022.104370.
   Web of Science ®Google Scholar
• Yu ZH, Yu T, Ge Y, Qu WA. 2023. The effect of perceived global stress and altruism on prosocial driving behavior, yielding behavior, and yielding attitude. Traffic Inj Prev. 24(5):402–408. doi:10.1080/15389588.2023.2191765.
   PubMed Web of Science ®Google Scholar
• Zhang DN, Chen F, Zhu JY, Wang CZ, Cheng JC, Zhang YL, Bo W, Zhang P. 2022. Research on drivers’ hazard perception in plateau environment based on visual characteristics. Accid Anal Prev. 166:106540. doi:10.1016/j.aap.2021.106540.
   PubMed Web of Science ®Google Scholar