Factors that affect highway-related crash frequency and injury severity vary across observations. Using a methodology that does not account nor correct for heterogeneity in observed and unobserved crash factors across...Factors that affect highway-related crash frequency and injury severity vary across observations. Using a methodology that does not account nor correct for heterogeneity in observed and unobserved crash factors across highway segments may lead to biased and inconsistent estimated coefficients, thus resulting in erroneous inferences. The present paper demonstrates the use of random-parameters models to facilitate and enhance how crash factors affect crash frequency and injury severity along a highway segment. The results indicate that a unit increase in the presence of stop sign along a highway segment reduces crash frequency by 2.471 for 87.24% of the roadway segments. For the remaining 12.76% of the roadway segments, crash frequency is increased by the same margin. Using the random-parameters multinomial logit model, the result indicates that, for 90.89% of the observations, the presence of a stop sign on a highway segment increases the probability of the injury outcome. For 9.11% of the observations, the presence of a stop sign on a highway segment reduces the probability of the injury outcome, and the marginal effect value across observations is 0.0017. Vertical grades greater than 5% increase crash frequency for 58.46% of the highway segments, and decrease for 41.54% of the highway segments by 0.121 for one unit increase in vertical grades.展开更多
Improper lane-changing behaviours may result in breakdown of traffic flow and the occurrence of various types of collisions.This study investigates lane-changing behaviours of multiple vehicles and the stimulative eff...Improper lane-changing behaviours may result in breakdown of traffic flow and the occurrence of various types of collisions.This study investigates lane-changing behaviours of multiple vehicles and the stimulative effect on following drivers in a consecutive lanechanging scenario.The microscopic trajectory data from the HighD dataset are used for driving behaviour analysis.Two discretionary lane-changing vehicle groups constitute a consecutive lane-changing scenario,and not only distance-and speed-related factors but also driving behaviours are taken into account to examine the impacts on the utility of following lane-changing vehicles.A random parameters logit model is developed to capture the driver’s psychological heterogeneity in the consecutive lane-changing situation.Furthermore,a lane-changing utility prediction model is established based on three supervised learning algorithms to detect the improper lane-changing decision.Results indicate that 1)the consecutive lane-changing behaviours have a significant negative effect on the following lane-changing vehicles after lane change;2)the stimulative effect exists in a consecutive lane-change situation and its influence is heterogeneous due to different psychological activities of drivers;and 3)the utility prediction model can be used to detect an improper lane-changing decision.展开更多
文摘Factors that affect highway-related crash frequency and injury severity vary across observations. Using a methodology that does not account nor correct for heterogeneity in observed and unobserved crash factors across highway segments may lead to biased and inconsistent estimated coefficients, thus resulting in erroneous inferences. The present paper demonstrates the use of random-parameters models to facilitate and enhance how crash factors affect crash frequency and injury severity along a highway segment. The results indicate that a unit increase in the presence of stop sign along a highway segment reduces crash frequency by 2.471 for 87.24% of the roadway segments. For the remaining 12.76% of the roadway segments, crash frequency is increased by the same margin. Using the random-parameters multinomial logit model, the result indicates that, for 90.89% of the observations, the presence of a stop sign on a highway segment increases the probability of the injury outcome. For 9.11% of the observations, the presence of a stop sign on a highway segment reduces the probability of the injury outcome, and the marginal effect value across observations is 0.0017. Vertical grades greater than 5% increase crash frequency for 58.46% of the highway segments, and decrease for 41.54% of the highway segments by 0.121 for one unit increase in vertical grades.
基金sponsored by the National Natural Science Foundation of China (Grant No.71901223)the Natural Science Foundation of Hunan Province (Grant No.2021JJ40746)the Postgraduate Research and Innovation Project of Central South University (Grant No.1053320216523).
文摘Improper lane-changing behaviours may result in breakdown of traffic flow and the occurrence of various types of collisions.This study investigates lane-changing behaviours of multiple vehicles and the stimulative effect on following drivers in a consecutive lanechanging scenario.The microscopic trajectory data from the HighD dataset are used for driving behaviour analysis.Two discretionary lane-changing vehicle groups constitute a consecutive lane-changing scenario,and not only distance-and speed-related factors but also driving behaviours are taken into account to examine the impacts on the utility of following lane-changing vehicles.A random parameters logit model is developed to capture the driver’s psychological heterogeneity in the consecutive lane-changing situation.Furthermore,a lane-changing utility prediction model is established based on three supervised learning algorithms to detect the improper lane-changing decision.Results indicate that 1)the consecutive lane-changing behaviours have a significant negative effect on the following lane-changing vehicles after lane change;2)the stimulative effect exists in a consecutive lane-change situation and its influence is heterogeneous due to different psychological activities of drivers;and 3)the utility prediction model can be used to detect an improper lane-changing decision.