Addressing unobserved heterogeneity at road user level for the analysis of conflict risk at tunnel toll plaza: A correlated grouped random parameters logit approach with heterogeneity in means
IF 12.5 1区 工程技术Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Penglin Song , N.N. Sze , Ou Zheng , Mohamed Abdel-Aty
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引用次数: 5
Abstract
Toll plaza is a designated area of controlled-access roads like expressway, bridge, and tunnel for toll collection. A number of toll booths are often placed at the toll plaza accommodating high passing traffic and multiple payment methods. Traffic and safety characteristics of toll plazas are different from that of other road entities. Different conflict risk indicators, which are usually longitudinal, have been adopted for real-time safety assessment. In this study, correlated grouped random parameter logit models with heterogeneity in the means are established to capture the unobserved heterogeneity, with additional flexibility, at road user level for the association between conflict risk and influencing factors. In addition, modified conflict risk indicator is developed to assess the safety of diverging, merging, and weaving movements of traffic, with which vehicles’ dimensions (width and length), and longitudinal and angular movements are considered. Also, prevalence and severity of both rear-end and sideswipe conflicts are assessed. Results indicate that toll collection type, vehicle’s location, average longitudinal speed, angular speed, acceleration, and vehicle class all affect the risk of traffic conflicts. Furthermore, there are significant correlation among the random parameters of severe traffic conflicts. Proposed analytic method can accommodate the conflict risk analysis for different conflict types and account for the correlation of unobserved heterogeneity. Findings should shed light on appropriate remedial measures like traffic signs, road markings, and advanced traffic management system that can improve the safety at tunnel toll plazas.
期刊介绍:
Analytic Methods in Accident Research is a journal that publishes articles related to the development and application of advanced statistical and econometric methods in studying vehicle crashes and other accidents. The journal aims to demonstrate how these innovative approaches can provide new insights into the factors influencing the occurrence and severity of accidents, thereby offering guidance for implementing appropriate preventive measures. While the journal primarily focuses on the analytic approach, it also accepts articles covering various aspects of transportation safety (such as road, pedestrian, air, rail, and water safety), construction safety, and other areas where human behavior, machine failures, or system failures lead to property damage or bodily harm.