Two PhD Positions in Applications of Swarm Intelligence in Traffic and Mobility Management

Updated: 25 days ago
Deadline: 02 Jun 2021

In our mobility ecosystem where dependencies are increasingly complex, the need for simple, local control principles that serve the collective purpose is growing. This need is the basis for the DIT4TraM (Distributed Intelligence and Technology for Traffic and Mobility Management) project, which investigates and tests what swarm intelligence can do for managing multimodal traffic and transport flows. DIT4TraM aims at a paradigm shift within traffic and mobility management according to the principles of swarm intelligence and self-learning systems.

The TU Delft part of this project involves two PhD positions, focusing on the development and application of these principles for multimodal i-VRIs and coordinated multimodal traffic management (P1) and for tradable mobility rights and planning of new mobility services (P2).

(P1) In this PhD research you will be developing incentive mechanisms that align user and system objectives at local bottlenecks by (monetary or credit) payments (or charges) that incentivise drivers to drive in a system optimal way; design efficient incentive mechanisms for traffic performance, fairness, emissions, and a trade-off between the various travel modes.

(P2) In this PhD research you will be developing distributed demand management schemes via tradable, multi-modal travel permits, to balance user-centric versus system optimal objectives (including but not restricted to equity, sustainability, and security) the performance of the designed trading schedmeds for mobility services such as shared rides will be evaluated using an agent-based simulation model.

These PhD projects is part of the DIT4TraM project. This EU project is a collaboration between some twenty knowledge institutions, companies, service providers and local governments and road authorities in nine countries. The Department of Transport & Planning (T&P) of Delft University of Technology is coordinating this project. T&P is composed of 11 research labs addressing various transport challenges.


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