Estimation of trajectory data.pdf

EC D a A R R A K R V L T B E 1 p f e v t c c b a g a m F a e i e p ( 0 dAccident Analysis and Prevention 42 (2010) 1888–1893 Contents lists available at ScienceDirect Accident Analysis and Prevention journa l homepage: www.e lsev ier .com/ locate /aap stimation of rear-end crash potential using vehicle trajectory data heol Oh ?, Taejin Kim1 epartment of Transportation Systems Engineering, Hanyang University at Ansan, Sa1-dong, Sangnok-gu, Ansan-city, Kyunggi-do 426-791, Republic of Korea r t i c l e i n f o rticle history: eceived 10 February 2010 eceived in revised form 5 April 2010 ccepted 11 May 2010 eywords: ear-end crash a b s t r a c t Recent advancement in traffic surveillance systems has allowed for obtaining more detailed vehicular movement such as individual vehicle trajectory data. Understanding the characteristics of interactions between leading vehicle and following in the traffic flow stream is a backbone for designing and eval- uating more sophisticated traffic and vehicle control strategies. This study proposes a methodology for estimating rear-end crash potential, as a probabilistic measure, in real time based on the analysis of vehicular movements. The methodology presented in this study consists of two components. The firstehicle trajectory ane-changing model ime-to-collision inary logistic regression model xponential decay function estimates the probability that a vehicle’s trajectory belonging to either ‘changing lane’ or ‘going straight’. A binary logistic regression (BLR) is used to model the lane-changing decision of the subject vehicle. The other component derives crash probability by an exponential decay function using time-to-collision (TTC) between the subject vehicle and the front vehicle. Also, an aggregated measure, crash risk index (CRI) is used in the analysis to accumulate rear-end crash potential for each subject vehicle. The result of this study can be used in developing traffic control and information systems, in particular, for