Optimising public transport through the integration of micro and macro-level simulations.

Han, Kate; Christie, Lee A.; Zăvoianu, Alexandru-Ciprian; McCall, John A.W.

Abstract

The European Commission and the UK aim for net zero emissions in transportation by 2050. This work explores the potential of connected and autonomous vehicles (CAVs) to support this goal by enhancing public transport (PT) via strategic deployment within optimised services. Macro-level mobility simulations integrating open data are coupled with meta-heuristic solvers to offer insight into optimal CAV route design while micro-level mobility simulations are used to increase the realism of generated solutions by providing insights on realistic travel speed variability in rush hour traffic across the considered study area. Results obtained with different solvers and two methods of transferring micro-level simulation insights to the macro-level service planning strategy indicate the potential for 3.0% to 38% average area-wide commuting time improvement when an optimised CAV service is added into the existing PT system.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 19th International conference on Computer-aided systems theory 2024 (EUROCAST 2024)
• Publication Date: Dec 31, 2025
• Volume: Part 1
• Pages: 107-121
• DOI: https://doi.org/10.1007/978-3-031-82949-9_10
• Public URL: https://rgu-repository.worktribe.com/output/2836758