Role of Customized Bus Services in the Transportation System: Insight from Actual Performance

Abstract

After attaining great prevalence from the end of 2013, customized bus (CB) transit services have experienced a huge decline in China. The feasibility of this new bus sharing system is thus being questioned. Therefore, it is imperative to investigate the actual role of CB services in the overall transportation system based on successful cases, as the role of the CB service determines its primary service object, system construction, marketing orientation, and even government function. To examine the role of CB services, this study investigates the practical performance, advantages, and spatial and temporal coverage of a successful CB system based on practical subscription data for more than two years. The results illustrate that the CB service is an eclectic choice that can balance service quality and cost between traveling by traditional public transportation (PT) and private cars/taxis. Even though the travel cost increased to a limited extent, the CB service significantly improved the travel experience in terms of the travel time, travel speed, number of stations, and difference arrival time compared to PT services. The multinomial logit model and regression models demonstrate a significant positive relationship between the relative advantage and amount of demand for the CB services. Furthermore, the CB service primarily serves trips generated during the peak traffic hours of the city and supplements traditional PT service in areas with poor coverage levels.

Optimizing Multi-Terminal Customized Bus Service With Mixed Fleet

“…Wang et al [2] found that CB is very attractive especially to commuters traveling in the peak hours because of its features in reducing travel time and coverage of spatiotemporal demand. It was also found that CB could serve as a supplement mode in the areas with low PT coverage.…”

“…Transit agencies thus promote demand responsive transit (DRT) as an alternative mode to elevate service quality by offering greater mobility and accessibility during the peak hours. With the rapid development of mobility as a service (MaaS) and personal mobile devices, an emerging DRT service, called customized bus (CB), has been initiated [1,2].…”

“…Several practical issues concerned by the CB suppliers but missed in previous studies are addressed, which include: (1) The desired arrival time at destination requested by passengers is ensured, while the inconvenience caused by early arrival at the destination is treated as penalty in user's cost. (2) Considering spatiotemporal passenger demand, a mixed bus fleet with various sizes is employed to increase the vehicle utilization and reduce supplier cost. (3) To reduce deadheading travel distance and associated cost, the multi-terminal operation is introduced.…”

Operational strategy of customized bus considering customers’ variety seeking behavior and service level

“…Currently, the literature focuses on two aspects of research on CB, namely, route planning ( Tong et al, 2017 ; Guo et al, 2019 ) and case (or factor) study ( Cao and Wang, 2016 ; Wang et al, 2019 ). There is little discussion of operational strategy or customer (or passenger) behavior.…”

Research on Optimization of Customized Bus Routes Based on Uncertainty Theory

“…Xue [13] considered the uncertain factor of number of passengers at a bus stop in reality, introduced the uncertainty theory to construct an uncertain bi-level programming model of bus line allocation, and solved it using MATLAB. Other scholars [14][15][16][17][18] analyzed customized buses from the aspects of passenger flow prediction and influencing factors. However, in real life, the time for a vehicle to arrive at each stop is not fixed, and few studies regard it as an uncertain variable.…”