{"id":27383,"date":"2024-05-03T11:29:08","date_gmt":"2024-05-03T03:29:08","guid":{"rendered":"https:\/\/tum-asia.edu.sg\/?p=27383"},"modified":"2025-01-21T15:52:25","modified_gmt":"2025-01-21T07:52:25","slug":"use-of-autonomous-modular-vehicles-in-local-public-transport","status":"publish","type":"post","link":"https:\/\/staging.tum-asia.edu.sg\/cn\/doctoral-studies\/phd\/use-of-autonomous-modular-vehicles-in-local-public-transport\/","title":{"rendered":"Use of Autonomous, Modular Vehicles in Local Public Transport"},"content":{"rendered":"

Supervising Professor<\/strong>:<\/p>\n

The supervision at TUM will be performed by the Chair of Traffic Engineering and Control, Univ.-Prof. Dr.-Ing. Klaus Bogenberger<\/em>.<\/p>\n

About:<\/strong><\/p>\n

The research position is funded by the German Academic Exchange Service (DAAD) and TUM Asia and offers a full-time, fixed-term position at the TUM Singapore Campus. You will be enrolled as an active doctoral candidate in the TUM Graduate School with the objective to obtain a doctoral degree awarded by TUM. You will be based in Singapore and be a member of a small group of doctoral candidates working together in the TUM Asia Graduate College, and will have the opportunity to spend some time at the main TUM Campus in Munich, Germany.<\/p>\n

Given TUM\u2019s strategic collaboration with the Nanyang Technological University (NTU, Singapore), there is also the option to obtain a joint TUM-NTU doctoral degree, if you also fulfil the NTU PhD requirements and are accepted by NTU.<\/p>\n

The scholarship is tenable for one year in the first instance and is renewable subject to good research performance. The maximum period of the Scholarship is 4 years for doctoral candidates, as determined by the school, as well as availability of research funding in each case.<\/p>\n

Your contribution:<\/strong><\/p>\n

The planned research topic: \u201cUse of autonomous, modular vehicles in local public transport\u201d will focus on automation of road-based transport services with new possibilities for providing flexible and adaptable public transport services that still provide sizeable capacities for urban transport. A basic principle can be to use autonomous shuttles (modules) on branches and feeders, that once reaching the trunk can couple together digitally and continue service on the main demand corridor as a platoon. The state of the art in simulation and optimisation of public transport considers on-demand services and line operations as two separate entities.<\/p>\n

The main aim of this PhD project is to combine these two service forms into one seamless entity for the use case of the modular shuttles. In a first step the dynamic routing of the on-demand branches is temporally coordinated with the timetables and capacities of the trunk. Subsequently, further flexibilization steps shall be developed such as a timetable-free operation, dynamic coupling of modules on the trunk or the flexible origin-destination assignment of each module according to the current demand.<\/p>\n

A basic framework for simulation of on-demand operations is provided with FleetPy, developed by TUM. The framework shall get extended to cover the seamless combination of flexible trunk and branches.<\/p>\n

To apply:<\/strong><\/p>\n

Interested candidates should send their full applications via email, including a resume, academic transcripts and a cover letter to:<\/p>\n

phd.admission@tum-asia.edu.sg<\/a><\/p>\n

We expect that you have:<\/p>\n