Abstract
The study presented in this paper aims to quantify the impact of level of service on real time crash risks on freeways and to investigate the mechanisms of crash occurrences in different level of service. Using crash data and paired traffic data extracted from a northbound segment of the I-880 freeway in the United States, a conditional logit model is conducted to relate the crash risks to levels of service. It is found that LOS E had the greatest impact on crash occurrences on freeways, followed by LOS F and LOS D, and the crash risks associated with LOS B are not significantly different from those associated with LOS A. The random forest algorithm is further conducted to identify the contributing factors to crash occurrence in different LOS. The findings of random forest demonstrate that the mechanisms of crash occurrence are quite different across different levels of service. The vehicle platoon and abrupt change in vehicle speed contribute to the crash risks in LOS A and B. In LOS C or LOS D, lane changes have impacts on crash risks, and the high crash risks associated with LOS E are mainly caused by high traffic volumes and oscillating traffic conditions. The findings of this study suggests that different traffic management strategies should be developed in dynamic freeway traffic management systems based on the contributing factors to crash occurrences in different levels of service.
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