Real Time Safety Model for Pedestrian Red-Light Running at Signalized Intersections in China

Abstract

The traditional way to evaluate pedestrian safety is a reactive approach using the data at an aggregate level. The objective of this study is to develop real-time safety models for pedestrian red-light running using the signal cycle level traffic data. Traffic data for 464 signal cycles during 16 h were collected at eight crosswalks on two intersections in the city of Nanjing, China. Various real-time safety models of pedestrian red-light running were developed based on the different combination of explanatory variables using the Bayesian Poisson-lognormal (PLN) model. The Bayesian estimation approach based on Markov chain Monte Carlo simulation is utilized for the real-time safety models estimates. The models’ comparison results show that the model incorporated exposure, pedestrians’ characteristics and crossing maneuver, and traffic control and crosswalk design outperforms the model incorporated exposure and the model incorporated exposure, pedestrians’ characteristics, and crossing maneuver. The result indicates that including more variables in the real-time safety model could improve the model fit. The model estimation results show that pedestrian volume, ratio of males, ratio of pedestrians on phone talking, pedestrian waiting time, green ratio, signal type, and length of crosswalk are statistically significantly associated with the pedestrians’ red-light running. The findings from this study could be useful in real-time pedestrian safety evaluation as well as in crosswalk design and pedestrian signal optimization.

Impact of Splitter-Island on Pedestrian Safety at Roundabout Using Surrogate Safety Measures: A Comparative Study

“…The authors observed that red light signals were more often violated by oncoming pedestrians when neighbours were doing the same in Kolkata city, India. Wu et al [27] developed a real-time safety model to investigate red-light running violations in the city of Nanjing, China. The results showed that pedestrian red-light running is statistically significantly associated with pedestrian volume, the ratio of males to females, the proportion of pedestrians on phones talking, pedestrian waiting time, green ratio, signal type, and length of the crosswalk.…”

Socio-Cognitive Determinants of Pedestrians’ Intention to Cross on a Red Light Signal: An Application of the Theory of Planned Behaviour

“…Keegan and O'Mahony [16] highlighted in their research that 35% of pedestrians cross against a red light. Studies confirm that pedestrians who cross against a red light are exposed to a higher accident risk [15,16]. In addition, King et al [17] determined that pedestrians who crossed against the red light accounted for 13% of the overall percentage of pedestrians at signalised intersections, and there were approximately eight times as many crashes per crossing event as there were legal crossings.…”

“…This can be explained by the fact that neither drivers nor pedestrians follow the rules of traffic light signalling. Studies have shown that the most common pedestrian offences are illegal crossings during a red-light phase [10][11][12][13][14][15]. Keegan and O'Mahony [16] highlighted in their research that 35% of pedestrians cross against a red light.…”