Real-time schedule adjustments for autonomous public transport vehicles
place - australasia, mode - bus, technology - intelligent transport systems, technology - automatic vehicle monitoring, operations - capacity, operations - scheduling, operations - reliability, ridership - demand
Autonomous public transport vehicles, Real-time strategies, Schedule adjustments, Fluctuated passenger demand, Energy efficiency
New advanced technologies have made it possible to deal with real-time schedule adjustments of public transport (PT) service. Indeed, using autonomous public transport vehicles (APTVs) prudently can result in significant improvements in the reliability, efficiency, and attractiveness of PT. The lack of human drivers and the feasible control strategies of the APTVs make it possible to offer a reliable, efficient and attractive service that can handle, in real time, the fluctuations in passenger demand. This work assumes that the APTVs of a single line are controlled centrally and are responsive to real-time requests from passengers. As the result, a real-time schedule can be constructed and communicated to the passengers. However, during the actual operations, the real-time demand will be fluctuated entailing schedule adjustments. These adjustments are optimized in this work using two operational strategies for the APTVs: holding and speed changing. The solution methodology proposed is based on time-space graphical techniques using multi-criteria decision analysis to minimize schedule changes as the primary objective, as well as to reduce travel time and active energy consumption. Two multi-objective models are developed for not-considered and considered vehicle capacity and then examined using a simulation framework. A case study from Auckland, New Zealand, is selected, which assumes that ordinary buses are replaced with APTVs. The results indicate that the strategy-based optimal schedule adjustments achieve a 100% elimination of schedule deviations compared with 33-minute and 13-minute deviations for the low-demand and high-demand scenarios of the ordinary PT service, respectively. The results of the simulated case study indicate that the incorporation of APTVs, along with prudent control, can result in a more attractive PT service.
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Cao, Z., Ceder, A., & Zhang, S. (2019). Real-time schedule adjustments for autonomous public transport vehicles. Transportation Research Part C: Emerging Technologies, Vol. 109, pp. 60-78.