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Safety Evaluation of Toll Plaza Diverging Area Considering Different Vehicles’ Toll Collection Types
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Different toll collection types of vehicles and different distribution of tollbooths lead to the toll plaza diverging area becoming a typical vehicle weaving area with frequent crossing behaviors and conflicts on highways. This study aims to identify contributing factors to conflict risks of four vehicle-following patterns in a toll plaza diverging area by developing random parameters ordered logit models with heterogeneity in means and variances. The model can flexibly capture the unobserved heterogeneity of the contributing factors in different vehicle-following patterns. Real-world vehicle trajectory data obtained from the toll plaza diverging area in Nanjing, China, are used for model estimation. The results show that vehicle-following patterns with the same toll collection types have higher percentage of severe conflict risks. The average acceleration of the following vehicles, lane marking indicator, the initial lanes and lane-changes of vehicles are significantly associated with the collision risk levels. The standard deviation of surrogate safety measures of all vehicles in sub-segments are found differ significantly between vehicle-following patterns. Furthermore, a series of likelihood ratio tests are adopted to test the spatial dependence in sub-segments of the diverging area. The findings of this study could provide valuable information for safety improvement in toll plazas.
Title: Safety Evaluation of Toll Plaza Diverging Area Considering Different Vehicles’ Toll Collection Types
Description:
Different toll collection types of vehicles and different distribution of tollbooths lead to the toll plaza diverging area becoming a typical vehicle weaving area with frequent crossing behaviors and conflicts on highways.
This study aims to identify contributing factors to conflict risks of four vehicle-following patterns in a toll plaza diverging area by developing random parameters ordered logit models with heterogeneity in means and variances.
The model can flexibly capture the unobserved heterogeneity of the contributing factors in different vehicle-following patterns.
Real-world vehicle trajectory data obtained from the toll plaza diverging area in Nanjing, China, are used for model estimation.
The results show that vehicle-following patterns with the same toll collection types have higher percentage of severe conflict risks.
The average acceleration of the following vehicles, lane marking indicator, the initial lanes and lane-changes of vehicles are significantly associated with the collision risk levels.
The standard deviation of surrogate safety measures of all vehicles in sub-segments are found differ significantly between vehicle-following patterns.
Furthermore, a series of likelihood ratio tests are adopted to test the spatial dependence in sub-segments of the diverging area.
The findings of this study could provide valuable information for safety improvement in toll plazas.
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