Characteristics and a Safety Analysis of Driver's Free Lane-changing Behavior in a Virtual Reality-based Connected Environment
Traditional driving simulators need help to accurately simulate complex interactions,such as speed varia-tions and lane changes in connected vehicle environments.The connected virtual reality(VR)driving simulator can more realistically replicate vehicle physical characteristics,traffic flow dynamics,and actual road environments us-ing advanced sensors and real-time data processing.A driving simulation system for free lane-changing experiments is developed using traffic simulation and 3D modeling technologies,based on which a scenario library is established and further carry out experiments about free lane-changing behavior.Generalized estimating equations is adopted to establish models of gap selection and lane-changing time.An accelerated failure time model is adopted to analyze the safety impact of the connected environment on free lane-changing behavior.The results can be concluded in two aspects.In connected environments:①Female drivers exhibit longer lane-changing gaps and need more time.Younger drivers show shorter gaps and need less time.②An increase of 1 m/s2 in acceleration noise can reduce col-lision risk by 28％during lane changes,and a 1 m increase in lane-changing gap can increase collision risk by 1.1％.③Older drivers have a higher level of lane-changing safety.Middle-aged and elderly drivers(>40 years old)show 38.3％and 64.3％higher regarding time-to-collision(TTC)than young(>27～40 years old)and younger drivers(>18～27 years old)do.④Female drivers have a higher level of lane-changing safety than male drivers do,with a 20.1％higher of TTC during free lane-changes.Compared to non-connected environments:①Drivers in connected environments show a 1.16 m increase in lane-changing gap,a 2.41 s increase in lane-changing time and a 19.72％improvement in the level of safety.②The probability of occurring lane-changing accidents decreases with the in-crease of collision risk durations.Specifically,it reduces by 5.8％,17.2％,14.4％,and 3.0％at 1,2,3,and 4 s of col-lision risk duration,respectively.These probabilities vary significantly across drivers'genders and ages.
traffic engineeringconnected environmentfree lane-changingvirtual realitygeneralized estimating equationsaccelerated failure model
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