Analysis of drivers’ deceleration behavior based on naturalistic driving data

References

• Du JB, Xu YY, He XK. 2017. Study on the braking behavior of private cars based on the road measure data. Automob Parts. (12):56–59.
   Google Scholar
• Every JL, Guenther DA, Heydinger GJ. 2015. A method of frequency content based analysis of driving braking behavior. SAE Int J Commer Veh. 8(1):63–8.
   Web of Science ®Google Scholar
• Guan X, Cui WF, Jia X, Zhang LZ. 2017. A research on longitudinal control correction and switch scheme for intelligent vehicles. Automot Eng. 9(39):75–9.
   Google Scholar
• Guo JH. 2012. Research on lateral and longitudinal control of intelligent vehicle based on vision navigation. Dalian, Liaoning, China: Dalian University of Technology.
   Google Scholar
• Kusano KD, Chen R, Montgomery J, Gabler HC. 2015. Population distributions of time to collision at brake application during car following from naturalistic driving data. J Saf Res. 54(95):e29–104.
   PubMedGoogle Scholar
• Lu G, Liu M, Wang Y, Wan H, Tian D. 2015. Logit-based analysis of drivers’ crossing behavior at unsignalized intersections in China. Hum Factors. 57(7):1101–1114.
   PubMed Web of Science ®Google Scholar
• McCall JC, Trivedi MM. 2007. Driver behavior and situation aware brake assistance for intelligent vehicles. Proc IEEE. 95(2):374–87.
   Web of Science ®Google Scholar
• Merat N, Lee JD. 2012. Preface to the special section on human factors and automation in vehicles: designing highly automated vehicles with the driver in mind. Hum Factors. 54(5):681–6.
   PubMed Web of Science ®Google Scholar
• Miyajima C, Takeda K. 2016. Driver-behavior modeling using on-road driving data: a new application for behavior signal processing. IEEE Signal Process Mag. 33(6):14–21.
   Web of Science ®Google Scholar
• Montgomery J, Kusano K D, Gabler H C. 2014. Age and gender differences in time to collision at braking from the 100-car naturalistic driving study. Traffic Inj Prev. 15(sup1):S15–S20.
   PubMed Web of Science ®Google Scholar
• Parasuraman R, Riley V. 1997. Humans and automation: use, misuse, disuse, abuse. Hum Factors. 39(2):230–53.
   Web of Science ®Google Scholar
• Reinhard R, Tutulmaz E, Rutrecht HM, Hengstenberg P, Geissler B, Hecht H, Muttray A. 2019. Effects of visually induced motion sickness on emergency braking reaction times in a driving simulator. Hum Factors. 12(3):1–15.
   Google Scholar
• Risto M, Martens MH. 2013. Time and space: the difference between following time headway and distance headway instructions. Transp Res Part F Traffic Psychol Behav. 17(17):45–51.
   Google Scholar
• Salmeron R, Garcia CB, Garcia J. 2018. Variance inflation factor and condition number in multiple linear regression. J Stat Comput Simul. 88(12):2365–84.
   Web of Science ®Google Scholar
• Seacrist T, Douglas EC, Huang E, Megariotis J, Prabahar A, Kashem A, Elzarka A, Haber L, MacKinney T, Loeb H, et al. 2018. Analysis of near crashes among teen, young adult, and experienced adult drivers using the SHRP2naturalistic driving study. Traffic Inj Prev. 19(sup1):S89–S96.
   PubMed Web of Science ®Google Scholar
• Soccolich SA, Fitch GM, Perez MA, Hanowski RJ. 2014. Comparing handheld and hands-free cell phone usage behaviors while driving. Traffic Inj Prev. 15(sup1):S21–S6.
   PubMed Web of Science ®Google Scholar
• Summala H. 2000. Brake reaction times and driver behavior analysis. Transp Hum Factors. 2(3):217–26.
   Google Scholar
• Tay R, Rifaat SM, Chin HC. 2008. A logistic model of the effects of roadway, environmental, vehicle, crash and driver characteristics on hit-and-run crashes. Accid Anal Prev. 40(4):1330–6.
   PubMed Web of Science ®Google Scholar
• Viti F, Hoogendoorn SP, Alkim TP, Bootsma G. 2008. Driving behavior interaction with ACC: results from a field operational test in the Netherlands. Intelligent Vehicles Symposium, Eindhoven, Netherlands; p. 745–50.
   Google Scholar
• Wada T, Doi S, Tsuru N, Isaji K, Kaneko H. 2010. Characterization of expert drivers' last-second braking and its application to a collision avoidance system. IEEE Trans Intell Transp Syst. 11(2):413–22.
   Web of Science ®Google Scholar
• Yan XD, Zhang XR, Xue QW. 2018. How does intersection field of view influence driving safety in an emergent situation. Accid Anal Prev. 15(07):162–75.
   Google Scholar