Public transit shared mobility - connected and safe solutions
Forskningsprojekt , 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.


Xiaobo Qu (kontakt)

Biträdande professor vid Chalmers, Arkitektur och samhällsbyggnadsteknik, Geologi och geoteknik

Balázs Adam Kulcsár

Biträdande professor vid Chalmers, Elektroteknik, System- och reglerteknik, Reglerteknik

Selpi Selpi

Forskare vid Chalmers, Mekanik och maritima vetenskaper, Fordonssäkerhet



Finansierar Chalmers deltagande under 2020–2021


Finansierar Chalmers deltagande under 2019–2020

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