Modeling Pedestrian Level of Service at Signalized Intersection Crosswalks under Mixed Traffic Conditions. Issue 1 (January 2015)

• Record Type: Journal Article
• Authors: Ye, Xiaofei; Chen, Jun; Jiang, Guiyan; Yan, Xingchen
• Is Part Of: Transportation research record. Volume 2512:Issue 1(2015)
• Page Start: 46
• Page End: 55
• Publication Date: 2015-01
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.3141/2512-06
• Languages: English
• ISSNs: 0361-1981

Abstract

The objectives of this study were to identify the factors affecting the pedestrian level of service (LOS) at signalized intersection crosswalks under mixed traffic conditions and to develop a suitable method for estimating pedestrian LOS. The important factors influencing pedestrian LOS at crosswalks were summarized: turning traffic, through traffic, number of pedestrians, and pedestrian delay. In the Highway Capacity Manual method, pedestrian delay can be calculated by Webster's delay model, which assumes that pedestrians arrive at a uniform rate and comply with the signal at an intersection. However, that assumption is not suitable for the Chinese scenario. A pedestrian delay model was developed by considering nonuniform arrival rates and noncompliant behavior under mixed traffic conditions. The data collected by video and a questionnaire survey include information on 1, 257 participants' real-time sense of comfort and safety when crossing five selected intersections and on the operational characteristics of the intersections. With perceived LOS as a dependent variable, Pearson correlation analysis and linear regression techniques were explored to determine the significant factors affecting LOS. To overcome the limitations of linear regression techniques, cumulative logistic regression was done to develop a model that fits mixed traffic conditions in China—a model that can predict the probability of responses within each LOS on the basis of a combination of explanatory variables. The results showed that the cumulative logistic model fit the survey data better than the linear regression model and produces LOS A for the crosswalks.