Modeling and Control of Mobility-on-Demand Systems

Remarkable technological advancements in intelligent transportation systems have raised the interest in of Mobility On-Demand (MOD) systems. MOD provide customers with a wide range of vehicles at any time, within an easy-to-use and affordable transportation infrastructure, through the sharing of combustion-, electric-, or human-powered vehicles. MOD systems offer the same benefits of privately-owned vehicles without requiring additional roads and parking spaces, paying only for the actual use of the vehicle, and allow access to zones with traffic restrictions.  Effective design, monitoring, and control of MOD systems are indeed complex problems. Several scientific and technological challenges must be addressed to achieve such objectives, involving all the actors in the system: vehicles, providers, customers, and not less important, the environment. Such challenges include optimal vehicle assignment, fleet balancing, predictive maintenance, and the achievement of low operational costs while preserving quality of service.  The goal of this activity is to research on the analysis, modeling and control of MOD systems. In particular, we aim at concurrently increasing providers' revenues and customers' satisfaction. Sought applications include system rebalancing, vehicle pooling and hand-over strategies, intelligent parking strategies, state-of-charge-aware planning and control of aelectric vehicles, etc.

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ERC Sector:

  • PE7_1 Control engineering
  • PE7_3 Simulation engineering and modelling
  • PE7_8 Networks (communication networks, networks of sensors, robots...)

Keywords:

  • Smart Transportation
  • Complex Systems
  • Mobility on demand
  • Optimization

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