Smart Urban Mobility
Research Cluster @ Artificial Intelligence Center, CTU in Prague
We are a group of researchers from Artificial Intelligence Center at CTU in Prague working on algorithms enabling more efficient and more sustainable future urban mobility.
See below for an non-exhaustive list of research themes related to smart urban mobility that are pursued within the center.
We are looking for partners in academia, industry, and public sector. If you are interested in our work, please contact either one of us:
We are developing models that provide insights into the performance of on-demand transportation systems and use them to estimate the impact of their large-scale deployment. Further, we are looking in the potential of advanced optimization techniques, automation, ride-sharing and market-based mechanisms to achieve affordable, efficient, and congestion-free urban traffic. Learn more...
We work on novel route planning and fleet management algorithms improving the experience electric mobility users. At the level of users of electric vehicles, we provide intelligent navigation systems that suggest adaptations in the travel plan to allow more efficient charging. At the fleet level, we develop management tools that help optimising fleet operations, maximising battery lifetime and minimising charging costs. Learn more...
We are developing and maintaining an agent-based micro-simulator of urban traffic called AgentPolis. The simulator can be used to perform large-scale "what-if" simulation studies involving different modes of transport such as private cars, on-demand cars, public transport etc. Agentpolis is particularly useful for evaluation of different fleet management strategies in on-demand systems. Learn more...
We are developing a model of transportation demand for the agglomeration of Prague, Czech Republic and Brno, Czech Republic. We use activity-based models trained on data from various sources. The resulting model is able to generate large, highly-granular synthetic trip data covering the entire population of the city agglomeration.
We are extending routing and journey planning algorithms to support the full spectrum of mobility services available in modern cities, combining individual and collective, fixed-schedule as well on-demand means of transport while taking into account individual user preferences and availability of transport services and resources. Try demo
Bicycles and other light transportation modes represent a sustainable alternative to private automobiles. We are developing specialized, multi-criteria route planner for cyclist that considers aspects such as elevation, surface quality, or traffic intensity along the route. Try demo