Analysis of the Impact of Traffic Violation Monitoring on the Vehicle Speeds of Urban Main Road: Taking China as an Example

TLDR

Traffic violation monitoring has become increasingly common worldwide, and vehicle speed distributions can be derived from probability density models. This study investigates how traffic violation monitoring on urban main roads affects nearby vehicle speeds. The authors recorded traffic flow on a representative urban main road using cameras, calculated vehicle speeds before, within, and after the monitoring zone, and used SPSS and mathematical modeling to build speed probability density models for each zone. The monitoring area reduced average and maximum speeds, with only 15.9% of vehicles speeding compared to 70.1% before and 80.2% after, and speeds initially drop then rise, demonstrating that the effect is confined to the immediate vicinity.

Abstract

In recent years, there are more and more applications of traffic violation monitoring in some countries. The present work aims to analyze the vehicle speeds nearby road traffic violation monitoring area on urban main roads and find out the impact of road traffic violation monitoring on the vehicle speeds. A representative urban main road section was selected and the traffic flow was recorded by camera method. The vehicle speeds before, within, and after the road traffic violation monitoring area were obtained by the calculation method. The speed data was classified and processed by SPSS software and mathematical method to establish the vehicle speed probability density models before, within, and after the road traffic violation monitoring area. The results show that the average speed and maximum speed within the traffic violation monitoring area are significantly slower than those before and after the traffic violation monitoring area. 70.1% of the vehicles before the road traffic violation monitoring area were speeding, and 80.2% of the vehicles after the road traffic violation monitoring area were speeding, while within the road traffic violation monitoring area, the speeding vehicles were reduced to 15.9%. When vehicles pass through the road traffic violation monitoring area, the vehicle speeds tend to first decrease and subsequently increase. In its active area, road traffic violation monitoring can effectively regulate driving behaviors and reduce speeding, but this effect is limited to the vicinity of the traffic violation monitoring. The distribution of vehicle speeds can be calculated from vehicle speed probability density models.