Yuting Zhang

Dr. Yuting Zhang


Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 November 2016 in Accident Analysis & Prevention
Verified
Journal Article
Closed access
YZYuting Zhang
Yuting Zhang
XYXuedong Yan
Xuedong Yan
XLXiaomeng Li
Xiaomeng Li
QXQingwan Xue
Qingwan Xue

YZYuting Zhang
Yuting Zhang
XYXuedong Yan
Xuedong Yan
XLXiaomeng Li
Xiaomeng Li
JWJiawei Wu
Jiawei Wu
VDVinayak Dixit
Vinayak Dixit
Red-light running (RLR) has been identified as one of the prominent contributing factors involved in signalized intersection crashes. In order to reduce RLR crashes, primarily, a better understanding of RLR behavior and crashes is needed. In this study, three RLR crash types were extracted from the general estimates system (GES), including go-straight (GS) RLR vehicle colliding with go-straight non-RLR vehicle, go-straight RLR vehicle colliding with left-turn (LT) non-RLR vehicle, and left-turn RLR vehicle colliding with go-straight non-RLR vehicle. Then, crash features within each crash type scenario were compared, and risk analyses of GS RLR and LT RLR were also conducted. The results indicated that for the GS RLR driver, the speed limit displayed the highest effects on the percentages of GS RLR collision scenarios. For the LT RLR driver, the number of lanes displayed the highest effects on the percentages of LT RLR collision scenarios. Additionally, the drivers who were older than 50 years, distracted, and had a limited view were more likely to be involved in LT RLR accidents. Furthermore, the speeding drivers were more likely to be involved in GS RLR accidents. These findings could give a comprehensive understanding of RLR crash features and propensities for each RLR crash type.