Comparing Parking Strategies of Autonomous Transit On Demand with Varying Transport Demand
| Autor: | Biyu Wang, Sergio A. Ordóñez Medina, Pieter J. Fourie |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Autonomous vehicle
Operations research Computer science Agent-based modeling MATSim Parking Control (management) 020206 networking & telecommunications 02 engineering and technology GeneralLiterature_MISCELLANEOUS On demand 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences 020201 artificial intelligence & image processing Transit (satellite) General Environmental Science |
| Zdroj: | ANT/EDI40 Procedia Computer Science, 151 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2019.04.111 |
| Popis: | Autonomous transit on demand are increasingly considered to become a viable substitute for taxi services. AVs can be managed through a centralized controlling system, targeting system optimization rather than user optimality. This centralized control can enable a more efficient, strictly-adhered-to parking strategy to reduce inefficient empty traveling. In this project, four different parking strategies are implemented in the AV extension of MATSim (Multi-agent transport simulation), namely demand-based roaming, parking on the street, parking in depots and a mixed strategy of parking on the street and in depots. The influence of different PT demand levels on the different parking strategies was explored, showing that the shared system is robust to varying levels of demand, and that the different parking strategies trade off user convenience for operational cost. The road parking strategy appears to be the best for consolidating rides into larger vehicles, especially for the increased demand scenario. Procedia Computer Science, 151 ISSN:1877-0509 |
| Databáze: | OpenAIRE |
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