Intelligent Transportation Planning

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The road-transportation sector represents nowadays a major contributing factor to the count of Green-House Gas emissions. This contribution is mostly due to the large ratio of vehicles powered by traditional fossil fuels, and by the constant rise of the number of vehicles on the roads. The transportation sector has, however, the perspective of undergoing an authentic technological revolution, labelled as Transportation 4.0 (Tr4), whose main elements are: 1) the transition towards the electrification of the transportation system, 2) the adoption of self-driving and Autonomous Vehicles (AVs), 3) the advances in Information Technology, 4) the widespread collection and storage of transportation data, and 5) the instantaneous and distributed access to computing resources. While the technological advances implicit in the Tr4 set up the conditions for more sustainable and efficient transportation systems, their management becomes dramatically more challenging. When surveying the scientific literature, one finds that there is a considerable lack of methodologies to address the challenges presented by the Tr4, both in the context of transit systems, as well as in freight distribution. Therefore, the main objective of this proposal is to develop decision-support tools to enable the transportation industry to fully profit from the opportunities given by the Tr4. The proposed methods are rooted in the fields of operations research and artificial intelligence. This research program is organized around two themes. The first theme considers transit systems and focuses on planning problems arising in the integration of on-demand services with traditional transit. This is done by adopting a modeling framework named Semi-flexible Transit System (STS). STSs aim to provide demand-responsive service within the framework of regularly scheduled transit. Combining characteristics of traditional and on-demand systems, STSs require an extremely complex planning activity. More specifically, this proposal aims to develop the methodology to incorporate a fleet of AVs in the operations planning of STSs, and build a simulation framework to analyze the performance of a system integrating STSs with traditional transit, and its impact on the mobility at a city-scale. The second theme considers freight transportation and focuses on stochastic and dynamic routing problems arising in the context of the Tr4. More specifically, this second theme aims to develop decision-support tools for real-time routing of vehicles under stochastic and dynamic traffic conditions, as well as dynamic policies for routing and charging operations when operating a fleet of battery-equipped electric vehicles. By developing tools to enable the Tr4 revolution, the anticipated impact of this research program is to provide more sustainable and more equitable transportation services, both in terms of public transit, as well as freight distribution.