The Comfort of the Soft-Safety Driver Alerts: Measurements and Evaluation

References

• Abe, G., & Richardson, J. (2006). Alarm timing, trust and driver expectation for forward collision warning systems. Applied Ergonomics, 37(5), 577–586. https://doi.org/10.1016/j.apergo.2005.11.001
   PubMed Web of Science ®Google Scholar
• af Wåhlberg, A. (2006). Short-term effects of training in economical driving: Passenger comfort and driver acceleration behavior. International Journal of Industrial Ergonomics, 36(2), 151–163. https://doi.org/10.1016/j.ergon.2005.10.001
   Web of Science ®Google Scholar
• Browne, R., & Byrne, A. (2008). Highway 402 queue warning system (wireless long haul application). In 2008 Annual Conference of the Transportation Association of Canada Transportation Association of Canada (TAC).
   Google Scholar
• Butakov, V., & Ioannou, P. (2015). Driving autopilot with personalization feature for improved safety and comfort. In 2015 IEEE 18th International Conference on Intelligent Transportation Systems (pp. 387–393). IEEE.
   Google Scholar
• Campbell, J. L., Richard, C. M., Brown, J. L., & McCallum, M. (2007). Crash warning system interfaces: Human factors insights and lessons learned. Report no. DOT HS 810 697. National Highway Traffic Safety Administration.
   Google Scholar
• Chan, C.-Y., Manasseh, C., & Rezaei, S. (2010). Experimental design and evaluation of networked traveler field tests of safety applications in California. In 2010 IEEE Intelligent Vehicles Symposium (pp. 39–44). IEEE.
   Google Scholar
• Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Routledge.
   Google Scholar
• Delle Site, P., Filippi, F., & Giustiniani, G. (2011). Users’ preferences towards innovative and conventional public transport. Procedia-Social and Behavioral Sciences, 20, 906–915. https://doi.org/10.1016/j.sbspro.2011.08.099
   Google Scholar
• Dillen, N., Ilievski, M., Law, E., Nacke, L. E., Czarnecki, K., & Schneider, O. (2020). Keep calm and ride along: Passenger comfort and anxiety as physiological responses to autonomous driving styles. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–13). https://doi.org/10.1145/3313831.3376247
   Google Scholar
• Eriksson, A., & Stanton, N. A. (2017). Takeover time in highly automated vehicles: Noncritical transitions to and from manual control. Human Factors, 59(4), 689–705. https://doi.org/10.1177/0018720816685832
   PubMed Web of Science ®Google Scholar
• Kaida, K., Takahashi, M., Åkerstedt, T., Nakata, A., Otsuka, Y., Haratani, T., & Fukasawa, K. (2006). Validation of the Karolinska Sleepiness Scale against performance and EEG variables. Clinical Neurophysiology, 117(7), 1574–1581. https://doi.org/10.1016/j.clinph.2006.03.011
   PubMed Web of Science ®Google Scholar
• Khan, A. M. (2007). Intelligent infrastructure-based queue-end warning system for avoiding rear impacts. IET Intelligent Transport Systems, 1(2), 138–143. https://doi.org/10.1049/iet-its:20060086
   Web of Science ®Google Scholar
• Kim, H. J., & Yang, J. H. (2017). Takeover requests in simulated partially autonomous vehicles considering human factors. IEEE Transactions on Human-Machine Systems, 47(5), 735–740. https://doi.org/10.1109/THMS.2017.2674998
   Web of Science ®Google Scholar
• Kirchner, W. K. (1958). Age differences in short-term retention of rapidly changing information. Journal of Experimental Psychology, 55(4), 352–358. https://doi.org/10.1037/h0043688
   PubMedGoogle Scholar
• Kozak, K., Pohl, J., Birk, W., Greenberg, J., Artz, B., Blommer, M., Cathey, L., & Curry, R. (2006). Evaluation of lane departure warnings for drowsy drivers. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 50, pp. 2400–2404). Sage Publications. https://doi.org/10.1177/154193120605002211
   Google Scholar
• Lee, J. D., Hoffman, J. D., & Hayes, E. (2004). Collision warning design to mitigate driver distraction. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 65–72).
   Google Scholar
• Lee, J. D., McGehee, D. V., Brown, T. L., & Reyes, M. L. (2002). Collision warning timing, driver distraction, and driver response to imminent rear-end collisions in a high-fidelity driving simulator. Human Factors, 44(2), 314–334. https://doi.org/10.1518/0018720024497844
   PubMed Web of Science ®Google Scholar
• Maurya, A. K., & Bokare, P. S. (2012). Study of deceleration behaviour of different vehicle types. International Journal for Traffic & Transport Engineering, 2(3), 253–270. https://doi.org/10.7708/ijtte.2012.2(3).07
   Google Scholar
• Mekker, M. M., Remias, S. M., McNamara, M. L., & Bullock, D. M. (2016). Characterizing interstate crash rates based on traffic congestion using probe vehicle data. In Transportation Research Board 95th Annual Meeting.
   Google Scholar
• Merat, N., Jamson, A. H., Lai, F. C., Daly, M., & Carsten, O. M. (2014). Transition to manual: Driver behaviour when resuming control from a highly automated vehicle. Transportation Research Part F: Traffic Psychology and Behaviour, 27, 274–282. https://doi.org/10.1016/j.trf.2014.09.005
   Web of Science ®Google Scholar
• Nowakowski, C., Vizzini, D., Gupta, S. D., & Sengupta, R. (2012). Evaluation of real-time freeway end-of-queue alerting system to promote driver situational awareness. Transportation Research Record: Journal of the Transportation Research Board, 2324(1), 37–43. https://doi.org/10.3141/2324-05
   Google Scholar
• Ruan, K., Yarmand, Z., Tian, R., Li, L., Chen, Y., Li, F., & Sturdevant, J. (2019). Highway end-of-queue alerting system based on probe vehicle data. In International Conference on Human–Computer Interaction (pp. 467–478). Springer.
   Google Scholar
• Seppelt, B. D., & Victor, T. W. (2016). Potential solutions to human factors challenges in road vehicle automation. In Road vehicle automation (Vol. 3, pp. 131–148). Springer.
   Google Scholar
• Souders, D., & Charness, N. (2016). Challenges of older drivers’ adoption of advanced driver assistance systems and autonomous vehicles. In International Conference on Human Aspects of IT for the Aged Population (pp. 428–440). Springer.
   Google Scholar
• Stephanidis, C., Salvendy, G., Antona, M., Chen, J. Y. C., Dong, J., Duffy, V. G., Fang, X., Fidopiastis, C., Fragomeni, G., Fu, L. P., Guo, Y., Harris, D., Ioannou, A., Jeong, K., Konomi, S., Krömker, H., Kurosu, M., Lewis, J. R., Marcus, A., … Zhou, J. (2019). Seven HCI grand challenges. International Journal of Human–Computer Interaction, 35(14), 1229–1269. https://doi.org/10.1080/10447318.2019.1619259
   Web of Science ®Google Scholar
• Tampère, C. M., Hoogendoorn, S. P., & Van Arem, B. (2009). Continuous traffic flow modeling of driver support systems in multiclass traffic with intervehicle communication and drivers in the loop. IEEE Transactions on Intelligent Transportation Systems, 10(4), 649–657. https://doi.org/10.1109/TITS.2009.2026442
   Web of Science ®Google Scholar
• Ullman, G., Brewer, M. A., Bryden, J. E., Corkran, M. O., Hubbs, C. W., Chandra, A. K., & Jeannotte, K. L. (2013). Enforcement effectiveness for queue-end protection. In Traffic Law Enforcement in Work Zones: Phase II Research. The National Academies Press. https://doi.org/10.17226/22575
   Google Scholar
• van Boekel, J., Besselink, I., & Nijmeijer, H. (2015). Design and realization of a one-pedal-driving algorithm for the TU/e Lupo EL. World Electric Vehicle Journal, 7(2), 226–237. https://doi.org/10.3390/wevj7020226
   Google Scholar
• Work, D., Bayen, A., & Jacobson, Q. (2008). Automotive cyber physical systems in the context of human mobility. In National Workshop on High-Confidence Automotive Cyber-Physical Systems (pp. 3–4).
   Google Scholar
• Yekhshatyan, L., & Lee, J. D. (2013). Changes in the correlation between eye and steering movements indicate driver distraction. IEEE Transactions on Intelligent Transportation Systems, 14(1), 136–145. https://doi.org/10.1109/TITS.2012.2208223
   Web of Science ®Google Scholar
• Zhang, B., de Winter, J., Varotto, S., Happee, R., & Martens, M. (2019). Determinants of take-over time from automated driving: A meta-analysis of 129 studies. Transportation Research Part F: Traffic Psychology and Behaviour, 64, 285–307. https://doi.org/10.1016/j.trf.2019.04.020
   Web of Science ®Google Scholar
• Zhang, Z., Shen, D., Tian, R., Li, L., Chen, Y., Sturdevant, J., & Cox, E. (2021). Implementation and performance evaluation of in-vehicle highway back-of-queue alerting system using the driving simulator. In 2021 IEEE International Intelligent Transportation Systems Conference (ITSC) (pp. 1753–1759). https://doi.org/10.1109/ITSC48978.2021.9565067
   Google Scholar
• Zhang, Z., Tian, R., & Duffy, V. G. (2023). Trust in automated vehicle: A meta-analysis (pp. 221–234). Springer International Publishing.
   Google Scholar