A Data-Driven Analysis for Operational Vehicle Performance of Public Transport Network

• Published in: IEEE access 2019, Vol.7, p.96404-96413
• Main Authors: Zhang, Hui, Cui, Houdun, Shi, Baiying
• Format: Article
• Language: English
• Subjects: Data analysis; data-driven analysis; Dwell time; Global Positioning System; Global positioning systems; GPS; GPS trajectory data; Headways; Network topology; Operators; Public transport network; Public transportation; Quality of service; Satellite navigation systems; Stability analysis; Stability criteria; stability of headway; Stations; Statistical analysis; Suburban areas; Synchronization; Traffic congestion; Traffic signals; Trajectory; Trajectory analysis; Transportation networks; Travel demand
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2019.2930279

The operational stability of public transport is significant for both passengers and operators. Affected by many stochastic factors, such as traffic congestion, traffic signals and passenger demand at stops, the headway always become uneven, which greatly reduces the service quality. This paper used the big global positioning systems (GPS) trajectory data to analyze the headway stability of bus system from the perspective of network. A statistical method is proposed to analyze the operational vehicle performance of bus network. The GPS trajectory data of Jinan is used to test the model. The results show that the average dwell time, actual headway, and headway stability index of stations follow lognormal distributions with obvious right tails. Moreover, the seriously unstable situations do not appear in the peak hours, but in the time periods before peak hours. In addition, the stations with most unstable headway are located in the suburbs and the fringe area of downtown. The outcomes suggest that operators should pay more attention to the suburbs and the fringe area of downtown, and the time periods before peak hours to efficiently improve the service quality.