4.28 - Street Space Allocation for Transportation: A Simulation-optimization approach

Research team

Urban street space is a limited resource that faces a growing demand from several different uses. This can be extended for road infrastructure, where often there are several transport modes competing for the use of the same street space.

When considering urban roads, there are many different practices and visions on how to allocate space for transportation. Over the years the vision for urban road space evolved from a perspective centered on supplying wide lanes for light vehicles, to a more sustainable and efficient provision of space for all modes.

The thesis goal is to help improve on the good practices for road management, focusing on the road space allocation to different traffic management strategies. Therefore, a novel methodology was developed based on a Simulation-Optimization approach. This methodology will enable the evaluation of a wide array of traffic management strategies considering different performance criteria applied to variable environments.

The Simulation-Optimization framework consists in a combination of benchmark traffic microsimulation models and optimization techniques, as well as machine-learning methods. The combination of these different tools will allow for detailed results, obtained in an acceptable timeframe, on top of allowing the inference of results for other environments.

Research Team
  • Luís Coimbra
  • Álvaro Seco (supervisor)
  • Carolina Osorio (supervisor for the MIT visiting period)
Financial Support
  • PhD Scholarship granted by FCT, under the MIT-Portugal Program
Stage of Progress
  • To be finished by December 2019