摘要
The impacts of four different car-following types on rear-end crash risks at a freeway weaving section were evaluated using trajectory data, in which Type 1 represents car following car, Type 2 represents car following truck, Type 3represents truck following car and Type 4 represents truck following truck. The time to collision( TTC) was introduced as the surrogate safety measure to determine the rear-end crash risks. Then, the trajectory data at a freeway weaving section was used for the case-controlled analysis. Three logistic regression models were developed with different TTC thresholds to quantify the impacts of different car-following types. The explanatory factors were also analyzed to investigate possible reasons for the results of logistic regressions. Results showthat the rear-end crash risk of Type3 is 3. 167 times higher than that of Type 1 when the TTC threshold is 2 s. However, the odds ratios of Type 2 and Type4 are both smaller than 1, which indicates a safer condition.The analysis of explanatory factors also shows that Type 3 has the largest speed differences and the smallest net gaps. This is consistent with vehicle operation features at a weaving section and is also the reason for the larger rear-end crash risks. The results of this study reflect the mechanism of rear-end crash risks of different car-following types at the freeway weaving section.
The impacts of four different car-following types onrear-end crash risks at a freeway weaving section wereevaluated using trajectory data, in which Type 1 represents carfollowing car, Type 2 represents car following truck, Type 3represents truck following car and Type 4 represents truckfollowing truck. The time to collision （TIC） was introducedas the surrogate safety measure to determine the rear-end crashrisks. Then, the trajectory data at a freeway weaving sectionwas used for the case-controlled analysis. Three logisticregression models were developed with different TICthresholds to quantify the impacts of different car-followingtypes. The explanatory factors were alSO analyzed toinvestigate possible reasons for the results of logisticregressions. Results show that the rear-end crash risk of Type3 is 3, 167 times higher than that of Type 1 when the TICthreshold is 2 s. However, the odds ratios of Type 2 and Type4 are both smaller than 1, which indicates a safer condition.The analysis of explanatory factors also shows that Type 3 hasthe largest speed differences and the smallest net gaps. This isconsistent with vehicle operation features at a weaving sectionand is also the reason for the larger rear-end crash risks. Theresults of this study reflect the mechanism of rear-end crashrisks of different car-following types at the freeway weavingsection.
基金
The National Natural Science Foundation of China(No.51638004,51338003,51478113)
