Evaluating the effects of the route guidance variable message signs on driving behaviors—a driving simulation study

References

• Agyapong F, Ojo TK. 2018. Managing traffic congestion in the Accra central market, Ghana. J Urban Manag. 7(2):85–96.
   Web of Science ®Google Scholar
• Beijing Municipal Commission of Transport. 2018. Driver’s subjective questionnaire survey report on variable intelligence board information demand: Beijing Municipal Commission of Transport.
   Google Scholar
• Dutta A, Fisher DL, Noyce DA. 2004. Use of a driving simulator to evaluate and optimize factors affecting understandability of variable message signs. Transp Res Part F Traffic Psychol Behav. 7(4–5):209–227.
   Web of Science ®Google Scholar
• Hasegawa T, Yamashita M, Suzuki T, Hisa Y, Wada Y. 2009. Active linear head motion improves dynamic visual acuity in pursuing a high-speed moving object. Exp Brain Res. 194(4):505–516. 10.1007/s00221-009-1716-6
   PubMed Web of Science ®Google Scholar
• Huang Y, Sun D, Zhang L-H. 2018. Effects of congestion on drivers’ speed choice: Assessing the mediating role of state aggressiveness based on taxi floating car data. Accid Anal Prev. 117:318–327. 10.1016/j.aap.2018.04.030
   PubMed Web of Science ®Google Scholar
• Irwin DE, Zacks JL, Brown JS. 1990. Visual memory and the perception of a stable visual environment. Percept Psychophys. 47(1):35–46. 10.3758/bf03208162
   PubMedGoogle Scholar
• Kersavage K, Guler SI, Pietrucha M. 2020. Analysis of colored variable message signs for visibility and comprehensibility. Transp Res Rec. 2674(1):125–134.
   Web of Science ®Google Scholar
• Klauer SG, Dingus TA, Neale VL, Sudweeks JD, Ramsey DJ. 2006. The impact of driver inattention on near-crash/crash risk: an analysis using the 100-car naturalistic driving study data. Washington DC: U.S. Department of Transportation.
   Google Scholar
• Lai CJ. 2010. Effects of color scheme and message lines of variable message signs on driver performance. Accid Anal Prev. 42(4):1003–1008. 10.1016/j.aap.2009.12.002
   PubMed Web of Science ®Google Scholar
• Lansdown TC, Stephens AN, Walker GH. 2015. Multiple driver distractions: a systemic transport problem. Accid Anal Prev. 74:360–367.
   PubMed Web of Science ®Google Scholar
• Liang Y, Lee J, Yekhshatyan L. 2012. How dangerous is looking away from the road? Algorithms predict crash risk from glance patterns in naturalistic driving. Hum Factors. 54(6):1104–1116. 10.1177/0018720812446965
   PubMed Web of Science ®Google Scholar
• Liu B, Sun L, Rong J. 2011. Driver’ s visual cognition behaviors of traffic signs based on eye movement parameters. J Transp Syst Eng Info Tech. 11(04):22–27.
   Google Scholar
• Poulopoulou M, Spyropoulou I. 2019. Active traffic management in urban areas: Is it effective for professional drivers? The case of variable message signs. Transp Res Part A Policy Pract. 130:412–423.
   Web of Science ®Google Scholar
• Qi W, Pei Y, Song M, Bie Y. 2013. Pattern analysis of driver’s "Pressure-State-Response" in traffic congestion. Discrete Dyn Nat Soc. 2013:1–11.
   Web of Science ®Google Scholar
• Qi W, Wen H, Wu Y, Qin L. 2017. Effect model of urban traffic congestion on driver’s lane-changing behavior. Adv Mech Eng. 9(9):1–12.
   Web of Science ®Google Scholar
• Richards A, McDonald M. 2007. Questionnaire surveys to evaluate user response to variable message signs in an urban network. IET Intell Transp Sy. 1(3):177–185.
   Web of Science ®Google Scholar
• Saifuzzaman M, Haque MM, Zheng Z, Washington S. 2015. Impact of mobile phone use on car-following behaviour of young drivers. Accid Anal Prev. 82:10–19. 10.1016/j.aap.2015.05.001
   PubMed Web of Science ®Google Scholar
• Stanton NA, Salmon PM. 2009. Human error taxonomies applied to driving: a generic driver error taxonomy and its implications for intelligent transport systems. Saf Sci. 47(2):227–237.
   Web of Science ®Google Scholar
• Tejero P, Insa B, Roca J. 2018. Increasing the default interletter spacing of words can help drivers to read traffic signs at longer distances. Accid Anal Prev. 117:298–303.
   PubMed Web of Science ®Google Scholar
• Traffic Administration Bureau of the Ministry of public security of the People’s Republic of China. 2021. In 2020, 33.28 million newly registered motor vehicles nationwide and 4.92 million new energy vehicles. https://www.mps.gov.cn/n2254098/n4904352/c7647179/content.html. Accessed 22 March, 2021.
   Google Scholar
• Xu C, Tarko AP, Wei W, Pan L. 2013. Predicting crash likelihood and severity on freeways with real-time loop detector data. Accid Anal Prev. 57:30–39.
   PubMed Web of Science ®Google Scholar
• Xu C, Wu Y, Rong J, Peng Z. 2020. A driving simulation study to investigate the information threshold of graphical variable message signs based on visual perception characteristics of drivers. Transp Res Part F Traffic Psychol Behav. 74:198–211.
   Web of Science ®Google Scholar
• Yang Y, Chen J, Easa SM, Zheng X, Lin W, Peng Y. 2020. Driving simulator study of the comparative effectiveness of monolingual and bilingual guide signs on Chinese highways. Transp Res Part F Traffic Psychol Behav. 68:67–78.
   Web of Science ®Google Scholar
• Yang Y, Chen Y, Wu C, Easa SM, Lin W, Zheng X. 2020. Effect of highway directional signs on driver mental workload and behavior using eye movement and brain wave. Accid Anal Prev. 146(105705):105705.
   PubMedGoogle Scholar
• Yao X, Zhao X, Liu H, Huang L, Ma J, Yin J. 2019. An approach for evaluating the effectiveness of traffic guide signs at intersections. Accid Anal Prev. 129:7–20.
   PubMed Web of Science ®Google Scholar
• Zhao W, Ma Z, Yang K, Huang H, Monsuur F, Lee J. 2020. Impacts of variable message signs on en-route route choice behavior. Transp Res Part A Policy Pract. 139:335–349.
   Web of Science ®Google Scholar
• Zheng Z, Ahn S, Monsere CM. 2010. Impact of traffic oscillations on freeway crash occurrences. Accid Anal Prev. 42(2):626–636.
   PubMed Web of Science ®Google Scholar