Traffic eco-management in urban traffic networks

Abstract : The problem of energy-aware traffic management in urban environment is addressed. Such traffic management aims at reducing vehicle stops, accelerations, energy consumption, and ultimately congestion. The eco-management in urban traffic networks may be divided in two broad categories: vehicle-side control and infrastructure-side control. Both control domains can feature isolated or coordinated characteristics, depending on the type of information used in the optimization.The vehicle-side traffic management influences each single vehicle according to its own characteristics and position. Isolated vehicle control aims primarily at optimizing the powertrain and/or the driving profile of the vehicles, possibly using information about the road characteristics, but without communicating with the other agents of the traffic network. Coordinated vehicle control makes use of communication among vehicles and with the infrastructure in order to achieve larger benefits in terms of energy consumption and traffic fluidity.The infrastructure-side management, on the other hand, influences traffic lights and road side panels in order to improve the performance of the traffic as a whole. Isolated infrastructure control regulates essentially the traffic lights at a single signalized intersection, or the speed limits in a single stretch of road, without taking into account the interactions with the neighboring junctions and/or road sections. Coordinated infrastructure control overcomes this limitation by using information about traffic conditions in other road sections to alleviate congestion.The contributions of this work to the energy-aware traffic management may be summarized as follows.Firstly, a solution for the coordinated vehicle control has been proposed, in which communication with the infrastructure is exploited to reduce energy consumption. In particular, the traffic lights timings are assumed to be communicated to the vehicle and known, and the vehicle is suggested an optimal speed to drive through a sequence of signalized intersections without stopping, while following a minimum-energy trajectory. The proposed strategy, independently applied to each vehicle, has been tested in a microscopic traffic simulator in order to assess the impact on the traffic performance. The analysis has demonstrated that the energy consumption and the number of stops can be drastically reduced without affecting the travel time.Then, a solution for the isolated infrastructure control has been proposed. A macroscopic urban traffic model has been introduced, and the variable speed limits have been used as actuation to improve traffic performance. In particular, the analysis has been carried out at saturated traffic conditions, with given and fixed traffic lights scheduling. The optimization aims at reducing the energy consumption in trade-off with the average travel time of the vehicles in the considered road section. Experiments have demonstrated that there exists an optimal speed limit that improves traffic performance and reduces the length of the queue at the traffic light.Lastly, a solution for the coordinated infrastructure control has been proposed. Traffic lights coordination on arterials has been proved to be effective in terms of traffic delay reduction. Our analysis has demonstrated that an optimization problem can be cast to take into account also energetic aspects. Extensive experiments in a microscopic traffic simulator have showed that a correlation exists between traffic progression and traffic performance indexes, such as energy consumption, travel time, idling time, and number of stops. The proposed control strategy has showed that a significant reduction of energy consumption can be achieved, almost completely eliminating number of stops and idling time, without affecting the travel time.
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Submitted on : Thursday, November 5, 2015 - 6:02:28 PM
Last modification on : Friday, May 17, 2019 - 11:41:20 AM
Long-term archiving on : Saturday, February 6, 2016 - 11:29:48 AM


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  • HAL Id : tel-01225232, version 1



Giovanni de Nunzio. Traffic eco-management in urban traffic networks. Automatic. Université Grenoble Alpes, 2015. English. ⟨NNT : 2015GREAT064⟩. ⟨tel-01225232⟩



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