Public transit shared mobility - connected and safe solutions
Research Project, 2019 – 2021

We propose to use adaptive learning algorithms in order to (i) estimate the travel demand, (ii) define and estimate the risks of crashes/conflicts and (iii) minimize transit delays (primary and secondary). The project will initially focus on designing intelligent algorithms for the public transport in Gothenburg, for which large amount of data on city bus driving has already been recorded.
One of the tasks is to investigate and propose an appropriate level of model abstractions and control decomposition into multiple layers that allow a real-time implementable solution.

This project is supported by Chalmers AoA Transport Foundation, with a total budget of 2.4 million SEK including matchup funding. 

Participants

Xiaobo Qu (contact)

Chalmers, Architecture and Civil Engineering, Geology and Geotechnics

Balázs Adam Kulcsár

Chalmers, Electrical Engineering, Systems and control

Selpi Selpi

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

Jiaming Wu

Chalmers, Electrical Engineering, Systems and control

Funding

Chalmers

Funding Chalmers participation during 2020–2021

Chalmers

Funding Chalmers participation during 2019–2020

Related Areas of Advance and Infrastructure

Transport

Areas of Advance

Energy

Areas of Advance

Publications

More information

Latest update

8/26/2019