Private cars induce most of the transport-related externalities. They produce lots of emissions, make inefficient use of scarce public space, push cities to be more sprawled, and increase social inequity. The opposite of private mobility is sharing a vehicle. Whether it is traditional public transport or emerging on-demand systems, when more passengers share their trips we build more sustainable cities. However, this implies coordinating up to thousands different users, each of them with their own origins and destinations, and desiring to complete their trips as soon as possible. This theme means studying to do this efficiently and in a way that does attract users, and is led by Dr. Andrés Fielbaum.

Designing shared systems implies questions in different realms, such as:

  • Public transport: How to decide the routes and frequencies of the lines? Which modes to offer? Should some vehicles operated on-demand?
  • On-demand ridepooling: How to coordinate thousands of users and vehicles online? What are the overall impacts of a mode that is more sustainable than private cars but less than public transport mass vehicles?
  • Users’ behaviour: What are the main problems preventing users to switch to public transport? What new behavioural aspects should be considered when studying on-demand transport?
  • Pricing: What are the fairest and most efficient ways to set fares for shared modes? Should subsidies or taxes be implemented?

This video is an example of our research and shows a potential integrated system where large buses follow fixed routes and small vehicles operate on-demand, which could reduce simultaneously users’ and operators’ costs.

Recent publications

  • Fielbaum, A., Tirachini, A., & Alonso-Mora, J. (2023). Economies and diseconomies of scale in on-demand ridepooling systems. Economics of Transportation34, 100313. (Paper)
  • Fielbaum, A., Kucharski, R., Cats, O., Alonso-Mora, J. (2022). How to split the costs and charge the travellers sharing a ride? Aligning system’s optimum with users’ equilibrium. European Journal of Operational Research 301(3), 956-973. (Paper) (Presentation)
  • Fielbaum, A., Kronmueller, M. & Alonso-Mora, J. (2022). Anticipatory routing methods for an on-demand ridepooling mobility system. Transportation 49, 1921-1962. (Paper)
  • Fielbaum, A. (2021). Optimizing a vehicle’s route in an on-demand ridesharing system in which users might walk. Journal of Intelligent Transportation Systems: Technology, Planning and Operation 26(4), 432-447. (Paper) (Presentation)
  • Fielbaum, A., Bai, X., & Alonso-Mora, J. (2021). On-demand ridesharing with optimized pick-up and drop-off walking locations. Transportation Research Part C: Emerging Technologies126, 103061. (Paper) (Presentation)
  • Kucharski, R., Fielbaum, A., Alonso-Mora, J., & Cats, O. (2021). If you are late, everyone is late: late passenger arrival and ride-pooling systems’ performance. Transportmetrica A: Transport Science,  17(4), 1077-1100. (Paper)
  • Fielbaum, A., & Alonso-Mora, J. (2020). Unreliability in ridesharing systems: Measuring changes in users’ times due to new requests. Transportation Research Part C: Emerging Technologies121, 102831. (Paper) (Presentation)
  • Fielbaum, A., Jara-Diaz, S., & Gschwender, A. (2020). Lines spacing and scale economies in the strategic design of transit systems in a parametric city. Research in Transportation Economics, 100991. (Paper)
  • Jara-Díaz, S., Fielbaum, A., & Gschwender, A. (2020). Strategies for transit fleet design considering peak and off-peak periods using the single-line model. Transportation Research Part B: Methodological142, 1-18. (Paper)
  • Fielbaum, A., Jara-Diaz, S., & Gschwender, A. (2020). Beyond the Mohring effect: Scale economies induced by transit lines structures design. Economics of Transportation22, 100163. (Paper)
  • Fielbaum, A. (2020). Strategic Public Transport Design Using Autonomous Vehicles and Other New Technologies. International Journal of Intelligent Transportation Systems Research 18, 193-201. (Paper)