Speeding behavior while using adaptive cruise control and lane centering in free flow traffic

References

• Atchley P, Tran AV, Salehinejad MA. 2017. Constructing a publically available distracted driving database and research tool. Accid Anal Prev. 99(Pt A):306–311. doi:10.1016/j.aap.2016.12.005
   PubMedGoogle Scholar
• Bagheri N, Jamieson GA. 2004. Considering subjective trust and monitoring behavior in assessing automation-induced “complacency.” In: Vicenzi DA, Mouloua M, Hancock PA, editors, Human performance, situation awareness, and automation: current research and trends. Mahwah (NJ): Erlbaum. p. 54–59.
   Google Scholar
• Bates D, Maechler M, Bolker B, Walker S. 2015. Fitting linear mixed-effects models using lme4. J Stat Softw. 67(1):1–48. doi:10.18637/jss.v067.i01
   Web of Science ®Google Scholar
• Besseling H, van Boxtel A. 2001. Intelligent speed adaptation: results of the Dutch ISA Tilburg trial. Rotterdam, The Netherlands: Ministry of Transport, Transport Research Centre AVV.
   Google Scholar
• Biding T, Lind G. 2002. Intelligent speed adaptation: results of large-scale trials in Borlänge, Lidköping, Lund and Umeå during the period 1999–2002. Borlänge, Vägverket: Swedish National Road Administration. Report No. 2002: 89 E.
   Google Scholar
• Caird JK, Willness CR, Steel P, Scialfa C. 2008. A meta-analysis of the effects of cell phones on driver performance. Accid Anal Prev. 40(4):1282–1293. doi:10.1016/j.aap.2008.01.009
   PubMed Web of Science ®Google Scholar
• Carsten OMJ, Tate FN. 2005. Intelligent speed adaptation: accident savings and cost-benefit analysis. Accid Anal Prev. 37(3):407–416. doi:10.1016/j.aap.2004.02.007
   PubMed Web of Science ®Google Scholar
• Crump ET. (Ed.). 1984. 55, a Decade of experience. Washington (DC): Transportation Research Board. Report No. 201-201.
   Google Scholar
• Cunningham ML, Regan MA. 2018. Driver distraction and inattention in the realm of automated driving. IET Intell Transp Syst. 12(6):407–413. doi:10.1049/iet-its.2017.0232
   Web of Science ®Google Scholar
• De Winter JC, Happee R, Martens MH, Stanton NA. 2014. Effects of adaptive cruise control and highly automated driving on workload and situation awareness: a review of the empirical evidence. Transp Res Part F: Traffic Psychol Behav. 27(Part B):196–217. doi:10.1016/j.trf.2014.06.016
   Google Scholar
• Dingus TA, Guo F, Lee S, Antin JF, Perez M, Buchanan-King M, Hankey J. 2016. Driver crash risk factors and prevalence evaluation using naturalistic driving data. Proc Natl Acad Sci USA. 113(10):2636–2641. doi:10.1073/pnas.1513271113
   PubMed Web of Science ®Google Scholar
• Elvik R. 2009. The power model of the relationship between speed and road safety: update and new analyses. Oslo, Norway: Institute of Transport Economics. No. 1034/2009
   Google Scholar
• Enriquez J, Pickrell TM. 2019. Seat belt use in 2018 — overall results. Washington (DC): National Highway Traffic Safety Administration. Report No. DOT HS-812-662.
   Google Scholar
• Farmer C. 2019. The effects of higher speed limits on traffic fatalities in the United States, 1993–2017. Arlington (VA): Insurance Institute for Highway Safety.
   Google Scholar
• Federal Highway Administration. 2013. Highway functional classification concepts, criteria and procedures. Washington (DC): U.S. Department of Transportation.
   Google Scholar
• Fridman L, Brown DE, Glazer M, Angell W, Dodd S, Jenik B, Terwilliger J, Patsekin A, Kindelsberger J, Ding L, et al. 2019. MIT advanced vehicle technology study: Large-scale naturalistic driving study of driver behavior and interaction with automation. IEEE Access. 7:102021–102038. doi:10.1109/ACCESS.2019.2926040
   Web of Science ®Google Scholar
• Garber NJ, Ehrhart AA. 2000. Effect of speed, flow, and geometric characteristics on crash frequency for two-lane highways. Transp Res Record. 1717(1):76–83. doi:10.3141/1717-10
   Google Scholar
• Guo F, Klauer SG, Fang Y, Hankey JM, Antin JF, Perez MA, Lee SE, Dingus TA. 2017. The effects of age on crash risk associated with driver distraction. Int J Epidemiol. 46(1):258–265. doi:10.1093/ije/dyw234
   PubMed Web of Science ®Google Scholar
• Hetherington C, Flin R, Mearns K. 2006. Safety in shipping: the human element. J Safety Res. 37(4):401–411. doi:10.1016/j.jsr.2006.04.007
   PubMed Web of Science ®Google Scholar
• Highway Loss Data Institute. 2019a. 2013–2017 BMW collision avoidance features. HLDI Bullet. 36(37):1–8.
   Google Scholar
• Highway Loss Data Institute. 2019b. HLDI facts and figures: 1981–2020 vehicle fleet. Arlington (VA). Report No. VIF-19
   Google Scholar
• Hoedemaeker M, Brookhuis KA. 1998. Behavioral adaptation to driving with an adaptive cruise control (ACC). Transp Res Part F Traffic Psychol Behav. 1(2):95–106. doi:10.1016/S1369-8478(98)00008-4
   Google Scholar
• Hoogendoorn SP, Viti F, Ossen SJL, Van Nifterick W, Doelman M, Zijderhand F, Kesting A, Alkim T. 2006. Fulltraffic research report. Delft University of Technology: The Netherlands.
   Google Scholar
• Insurance Institute for Highway Safety. 2020. Speed. https://www.iihs.org/topics/speed.
   Google Scholar
• Kessler C, Etemad A, Alessandretti G, Heinig K, Selpi C, Brouwer R, … Benmimoun M. 2012. European large-scale field operational tests on in-vehicle systems. Deliverable D11.3 Final Report. http://www.eurofotip.eu/download/library/deliverables/eurofotsp120121212v11dld11.3_final_report.pdf
   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): National Highway Traffic Safety Administration. DOT HS 810 594.
   Google Scholar
• Kloeden CN, McLean AJ, Glonek G. 2002. Reanalysis of travelling speed and the risk of crash involvement in Adelaide South Australia. Canberra, Australia: Australian Transport Safety Bureau. Report No. CR 207.
   Google Scholar
• Llaneras RE, Salinger J, Green CA. 2013. Human factors issues associated with limited ability autonomous driving systems: Drivers’ allocation of visual attention to the forward roadway. Proceedings of the Seventh International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design; 2013 June 17-20, Bolton Landing, New York. Iowa City, IA. p. 92–98. doi:10.17077/drivingassessment.1472
   Google Scholar
• Longo M, Bramani M. 2015. The automation control systems for the efficiency of metro transit lines. In 2015 AEIT International Annual Conference (AEIT); IEEE. p. 1–6. doi:10.1109/AEIT.2015.7415254
   Google Scholar
• Monk CA, Boehm-Davis DA, Trafton JG. 2004. Recovering from interruptions: implications for driver distraction research. Hum Factors. 46(4):650–663. doi:10.1518/hfes.46.4.650.56816
   PubMed Web of Science ®Google Scholar
• National Highway Traffic Safety Administration. 1998. Intelligent cruise control field operational test. Washington (DC). DOT HS 808 849
   Google Scholar
• National Highway Traffic Safety Administration. 2006. Exploratory study of early adopters, safety-related driving with advanced technologies. Washington (DC). DOT HS 809 972.
   Google Scholar
• National Highway Traffic Safety Administration. 2015. The economic and societal impact of motor vehicle crashes, 2010 (Revised). Washington (DC). DOT HS 812 013.
   Google Scholar
• Nilsson L. 1995. Safety effects of adaptive cruise control in critical traffic situations. In Proceedings of the 2nd World Congress of Intelligent Transport Systems; Tokyo, Japan. p. 1254–1259.
   Google Scholar
• Parasuraman R, Riley V. 1997. Humans and automation: Use, misuse, disuse, abuse. Hum Factors. 39(2):230–253. doi:10.1518/001872097778543886
   Web of Science ®Google Scholar
• Reagan IJ, Hu W, Cicchino JB, Seppelt B, Fridman L, Glazer M. 2019. November. Measuring adult drivers’ use of Level 1 and 2 driving automation by roadway functional class. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Vol. 63, No. 1, p. 2093–2097, Sage CA. Los Angeles, CA: SAGE Publications. doi:10.1177/1071181319631225
   Google Scholar
• Richard CM, Joonbum L, Brown JL, Landgraf A. 2020. Analysis of SHRP2 speeding data. Washington (DC): National Highway Traffic Safety Administration. DOT HS 812 858.
   Google Scholar
• Satterthwaite FE. 1946. An approximate distribution of estimates of variance components. Biometrics. 2(6):110–114. doi:10.2307/3002019
   PubMed Web of Science ®Google Scholar
• Viti F, Hoogendoorn SP, Alkim TP, Bootsma G. 2008. June. Driving behavior interaction with ACC: results from a field operational test in the Netherlands. In 2008 IEEE Intelligent Vehicles Symposium; IEEE. p. 745–750.
   Google Scholar
• Wickens CD. 1994. Designing for situation awareness and trust in automation. In Proceedings of the International Federation of Automatic Control (IFAC) Conference. Baden-Baden, Germany: IFAC. p. 174–179
   Google Scholar
• Wiener EL, Curry RE. 1980. Flight-deck automation: promises and problems. Ergon. 23(10):995–1011. doi:10.1080/00140138008924809
   Web of Science ®Google Scholar
• Wilde GJS. 1998. Risk homeostasis theory: an overview. Inj Prev. 4(2):89–91. doi:10.1136/ip.4.2.89
   PubMedGoogle Scholar
• Xiong H, Boyle LN. 2013. Drivers’ selected settings for adaptive cruise control (ACC) implications for long-term use. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 57(1):1928–1932. Sage CA: Los Angeles, CA: SAGE Publications. doi:10.1177/1541931213571431
   Google Scholar
• Zhang J, Yu KF. 1998. What's the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA. 280(19):1690–1691. doi:10.1001/jama.280.19.1690
   PubMed Web of Science ®Google Scholar