Modeling the Driver's Recognitive Characteristics to Crossing Pedestrians at Night for the Maximum Speed Limit and Lighting Index in China

Abstract

Aiming to reduce the number of crashes caused by speeding at night on road section with a crosswalk, a study was conducted on the maximum speed limit and safe average luminance at night. In order to investigate the potential relationship between drivers' recognitive characteristics and driving speed under different road lighting features, data of remaining driving time (period from the time that crossing pedestrian is recognized to the time that vehicle arrives at crosswalk with an uniform speed) were recorded. The results of the data analysis show that it is more difficult for divers to recognize crossing pedestrian at night when a single pedestrian is statistic and wears dark clothes. The remaining driving time decreases with the increase of driving speed and the decrease of road luminance. With the collected data, several multivariate nonlinear regression models were established to capture the relationship among the variables of remaining driving time at night, the driving speed, and the average luminance. Then the modeling results were used to develop the reasonable speed limit and safe average luminance by physical equations. The case studies are also introduced at the end of the paper.