STATISTICAL ANALYSIS OF JAYWALKING CONFLICTS BY A LIDAR SENSOR

Abstract

The light detection and ranging (Lidar) sensor is a remote sensing technology that can be used to monitor pedestrians who cross an intersection outside of a designated crosswalk or crossing area, which is a key safety application of lidar sensors at signalized intersections. Hereupon, the Lidar sensor was installed at the Hillen Rd - E 33rd St. intersection in Baltimore city to collect real-time jaywalkers’ traffic data. In order to propose safety improvement considerations for the pedestrians as one of the most vulnerable road users, the paper aims to investigate the reasons for jaywalking and its potential risks for increasing the frequency and severity of vehicle-pedestrian conflicts. In a three-month time, interval from December 2022 to February 2023, a total of 585 jaywalkers were detected. By developing a generalized linear regression model and using K-means clustering, the highly correlated independent variables to the frequency of jaywalking were recognized, including the speed of jaywalkers, the average PET of vehicle-pedestrians, the frequency of vehicle-pedestrian conflicts, and the weather condition. The volume of vehicles and pedestrians and road infrastructure characteristics such as medians, building entrances, vegetation on medians, and bus/taxi stops were investigated, and the results showed that as the frequency of jaywalking increases, vehicle-pedestrian conflicts will occur more frequently and with greater severity. In addition, jaywalking speed increases the likelihood of severe vehicle-pedestrian conflicts. Also, during cloudy and rainy days, 397 pedestrians were motivated to jaywalk (or 68% of total jaywalkers), making weather a significant factor in the increase in jaywalking.