Calibration on Expressway Car-following Model with Various Rainfall Intensities
To calibrate the expressway car-following model with various rainfall intensity,the characteristics of drivers'car-following behavior with various rainfall intensities were explored through field tests.The car-following model was calibrated based on the genetic algorithm.The calibration parameters were verified by using cross-validation.Firstly,the traffic flow data under normal,light rain,moderate rain,and heavy rain conditions were collected through field experiments.The car-following events were screened based on the headway and inter-vehicle distance.Secondly,the variability of drivers'following behavior with different rainfall intensities was analyzed.The relation between headway and following speed with different rainfall intensities was explored.Finally,the genetic algorithm was used to calibrate the parameters of GHR model,FVD model,and IDM model.The cross-validation was used to test the accuracy of models.The result indicates that there is a significant influence of rainfall intensity on expressway car-following behavior.As rainfall intensity increases,the drivers tend to maintain larger headway and lower car-following speed.Compared with normal weather condition,the average car-following distance increases by more than 30 m at the same car-following speed under heavy rain condition,while the average car-following speed decreases by more than 10 km/h at the same headway.The validation analysis further shows that the parameters of driver sensitivity in car-following model increase gradually with the increase of rainfall intensity.That reflects a tendency for the parameters of driving behavior or expected driving behavior to change in a more conservative direction.The cross-validation analysis also shows that compared with GHR model and FVD model,the IDM model accurately reflects the influence of different rainfall intensities on car-following behavior.
NETL
NSTL
万方数据
