Effects of cooperative vehicle infrastructure system on driver’s attention––A simulator study on work zone

References

• Abdel-Aty, M., Pande, A., Lee, C., Gayah, V., & Santos, C. D. (2007). Crash risk assessment using intelligent transportation systems data and real-time intervention strategies to improve safety on freeways. Journal of Intelligent Transportation Systems, 11(3), 107–120. doi:10.1080/15472450701410395
   Web of Science ®Google Scholar
• Ahlstrom, C., & Kircher, K. (2017). Changes in glance behaviour when using a visual eco-driving system—A field study. Applied Ergonomics, 58, 414–423.
   PubMed Web of Science ®Google Scholar
• Birrell, S. A., & Fowkes, M. (2014). Glance behaviours when using an in-vehicle smart driving aid: A real-world, on-road driving study. Transportation Research Part F: Traffic Psychology and Behaviour, 22, 113–125. doi:10.1016/j.trf.2013.11.003
   Web of Science ®Google Scholar
• Chang, X., Li, H., Rong, J., Zhao, X., & Zhao, G. (2019). Connected vehicle environment simulation platform construction and its impact on driving behavior based on driving simulator. Science Technology and Engineering, 19(15), 330–335.
   Google Scholar
• Charlton, S. G. (2009). Driving while conversing: Cell phones that distract and passengers who react. Accident; Analysis and Prevention, 41(1), 160–173. doi:10.1016/j.aap.2008.10.006
   PubMed Web of Science ®Google Scholar
• Chen, H., Rao, P. L., & Guo, Z. (2017). The effects of V2V information on visual attention and driving performance of the drivers. Chinese Journal of Ergonomics, 23(4), 44–47.
   Google Scholar
• Chow, S. C., Shao, J., Wang, H., & Lokhnygina, Y. (2017). Sample size calculations in clinical research. Chapman & Hall / CRC Biostatistics Series, New York: Taylor&Francis.
   Google Scholar
• Chun, J., Lee, I., Park, G., Seo, J., Choi, S., & Han, S. H. (2013). Efficacy of haptic blind spot warnings applied through a steering wheel or a seatbelt. Transportation Research Part F: Traffic Psychology and Behaviour, 21, 231–241. doi:10.1016/j.trf.2013.09.014
   Web of Science ®Google Scholar
• Ensar, B., Edwards, C. J., Manser, M. P., & Donath, M. (2018). Aging and the use of an in-vehicle intersection crossing assist system: An on-road study. Transportation Research Part F: Traffic Psychology and Behaviour, 56, 113–122.
   Web of Science ®Google Scholar
• Ge, J. I., & Orosz, G. (2014). Dynamics of connected vehicle systems with delayed acceleration feedback. Transportation Research Part C: Emerging Technologies, 46, 46–64. doi:10.1016/j.trc.2014.04.014
   Web of Science ®Google Scholar
• Georges, A., & Shannon, B. (2011). Towards reducing traffic congestion using cooperative adaptive cruise control on a freeway with a ramp. Journal of Industrial Engineering and Management, 4(4), 699–717.
   Google Scholar
• Hu, D., Feng, X., Zhao, X., Li, H., Ma, J., & Fu, Q. (2022). Impact of HMI on driver’s distraction on a freeway under heavy foggy condition based on visual characteristics. Journal of Transportation Safety & Security, 14(6), 905–928. doi:10.1080/19439962.2020.1853641
   Web of Science ®Google Scholar
• Kraft, A.-K., Naujoks, F., Wörle, J., & Neukum, A. (2018). The impact of an in-vehicle display on glance distribution in partially automated driving in an on-road experiment. Transportation Research Part F: Traffic Psychology and Behaviour, 52, 40–50. doi:10.1016/j.trf.2017.11.012
   Web of Science ®Google Scholar
• Lerman, J. (1996). Study design in clinical research: Sample size estimation and power analysis. Canadian Journal of Anaesthesia = Journal canadien d’anesthesie, 43(2), 184–191. doi:10.1007/BF03011261
   PubMed Web of Science ®Google Scholar
• Li, X. L. Z., Zhao, X., Rong, J., & Zhang, Y. (2022). Effects of cooperative vehicle infrastructure system on driver’s visual and driving performance based on cognitive process. International Journal of Automotive Technology. In press.
   Web of Science ®Google Scholar
• Li, Y. (2015). Research on optimization design of cab visual interface based on driver’s color preference. Southwest Jiaotong University. Cheng Du. Master Degree Thesis.
   Google Scholar
• Matsumoto, S., Park, T., & Kawashima, H. (2014). A comparative study on fuel consumption reduction effects of eco-driving instructions strategies. International Journal of Intelligent Transportation Systems Research, 12(1), 1–8. doi:10.1007/s13177-013-0066-8
   Google Scholar
• Najar, S. A., & Sanjram, P. K. (2019). Driving errors and gaze behavior during in-vehicle object and spatial distractions. Journal of Transportation Safety & Security, 13(4), 381–413.
   Web of Science ®Google Scholar
• NHTSA. (2014). Visual-manual NHTSA driver distraction guidelines for in-vehicle electronic devices. US Department of Transportation Federal Register, 79(179), 55530–55534.
   Google Scholar
• NHTSA. (2015). Critical reasons for crashes investigated in the national motor vehicle crash causation survey [DOT HS 812 115]. Retrieved July 26, 2020, from www-nrd.nhtsa.dot.gov/Pubs/812115.pdf
   Google Scholar
• Raddaoui, O., & Ahmed, M. M. (2020). Evaluating the effects of connected vehicle weather and work zone warnings on truck drivers’ workload and distraction using eye glance behavior. Transportation Research Record: Journal of the Transportation Research Board, 2674(3), 293–304. doi:10.1177/0361198120910743
   Web of Science ®Google Scholar
• Raddaoui, O., Ahmed, M. M., & Gaweesh, S. M. (2020). Assessment of the effectiveness of connected vehicle weather and work zone warnings in improving truck driver safety. IATSS Research, 44(3), 230–237. doi:10.1016/j.iatssr.2020.01.001
   Web of Science ®Google Scholar
• Rouzikhah, H., King, M., & Rakotonirainy, A. (2013). Examining the effects of an eco-driving message on driver distraction. Accident Analysis & Prevention, 50, 975–983.
   PubMed Web of Science ®Google Scholar
• Shailesh, C., & Francisco, C. (2016). A simulation-based evaluation of connected vehicle technology for emissions and fuel consumption. Procedia Engineering, 145, 296–303.
   Google Scholar
• Tijerina, L., Johnston, S., Parmer, E., Pham, H. A., Winterbottom, M. D., & Barickman, F. S. (2000). Preliminary studies in haptic displays for rear-end collision avoidance system and adaptive cruise control system applications. NHTSA, DOT HS, 808 (TBD).
   Google Scholar
• Wege, C., Will, S., & Victor, T. (2013). Eye movement and brake reactions to real world brake-capacity forward collision warnings—A naturalistic driving study. Accident Analysis & Prevention, 58(sep), 259–270.
   PubMedGoogle Scholar
• Wickens, C. D., Lee, J. D., Liu, Y., & Becker, S. G. (2007). An introduction to human factors engineering. Shanghai, P.R. China: East China Normal University Press.
   Google Scholar
• Wu, Y., Mohamed, A. A., Park, J., & Zhu, J. (2018). Effects of crash warning systems on rear-end crash avoidance behavior under fog conditions. Transportation Research Part C: Emerging Technologies, 95, 481–492. doi:10.1016/j.trc.2018.08.001
   Web of Science ®Google Scholar
• Xie, C. (2014). Study on impact of IVIS to driver vision feature. Xian, P.R. China: Changan University.
   Google Scholar
• Xie, Y. (2008). Research on prominent elements of road design influencing drivers’ psychological expectation. Xian, P.R. China: Shanxi Normal University.
   Google Scholar
• Zhang, Q. (2014). Crash involvement mechanism and driving behavior pattern of Chinese carless young drivers. Shanghai, P.R. China: Shanghai Jiao Tong University.
   Google Scholar
• Zhao, X., Chen, H., Li, H., Li, X., Chang, X., Feng, X., & Chen, Y. (2021). Development and application of connected vehicle technology test platform based on driving simulator: Case study. Accident Analysis & Prevention, 161(2021), 106330.
   PubMedGoogle Scholar
• Zhao, X., Chen, Y., Li, H., Xing, G., & Feng, X. (2019). Comprehensive test and impact assessment for human factors of connected vehicle system. China Journal of Highway and Transport, 032(006), 248–261.
   Google Scholar
• Zhao, X., Xu, W., Ma, J., Li, H., Chen, Y., & Rong, J. (2019). Effects of connected vehicle-based variable speed limit under different foggy conditions based on simulated driving. Accident Analysis & Prevention, 128, 206–216.
   PubMed Web of Science ®Google Scholar
• Zhao, X., Xu, W., & Yao, Y. (2017). A study on a system of dynamic driving safety education based on simulator+. Traffic Information and Safety, 35(05), 123–130.
   Google Scholar
• Zhu, T., Wu, L., & Lu, Q. (2015). Effects of in-vehicle information on driver eye blink duration and workload. Journal of Southwest Jiaotong University, 50(003), 504–510.
   Google Scholar