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AUTOlab brings together researchers with years of experience in transportation planning and optimization, including positions in industry, government, and academic institutes around the world. Research at AUTOlab stands on four pillars:

  • studying and understanding existing (or planned) real world transportation systems and services

  • analyzing real world big-data obtained from transportation systems and services

  • developing data-driven mathematical models and simulation models to represent the planning and operation of such systems

  • developing optimization techniques tailored for the studied services/planning problems

Our ultimate goals are both in advancing theoretical knowledge and in creating decision-aid tools that can support practitioners with their real planning problems.

Current research topics include:

  • On-demand transportation services, including ride-hailing, ride-sharing and dial-a-ride services

  • Innovative transportation services employing autonomous, connected and electric vehicles

  • Semi-autonomous last mile transportation and logistics services

  • Vehicle sharing systems including: car-sharing, bikes-sharing and micro-sharing

  • Flexible and semi-flexible public transportation services

  • Automated parking facilities

  • Vehicle platooning

  • Personal rapid transit

  • Multi-modal transportation planning

AUTOlab researchers develop and apply methodologies such as:

  • Data analytics

  • Mathematical modeling

  • Exact optimization techniques

  • On-line algorithms

  • Heuristics

  • Decomposition techniques

  • Event-based simulations

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