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New Transportation Systems for Smart Cities

New Transportation Systems for Smart Cities

Christos G. Cassandras
Copyright: © 2015 |Pages: 26
ISBN13: 9781466682825|ISBN10: 1466682825|EISBN13: 9781466682832
DOI: 10.4018/978-1-4666-8282-5.ch011
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MLA

Cassandras, Christos G. "New Transportation Systems for Smart Cities." Handbook of Research on Social, Economic, and Environmental Sustainability in the Development of Smart Cities, edited by Andrea Vesco and Francesco Ferrero, IGI Global, 2015, pp. 213-238. https://doi.org/10.4018/978-1-4666-8282-5.ch011

APA

Cassandras, C. G. (2015). New Transportation Systems for Smart Cities. In A. Vesco & F. Ferrero (Eds.), Handbook of Research on Social, Economic, and Environmental Sustainability in the Development of Smart Cities (pp. 213-238). IGI Global. https://doi.org/10.4018/978-1-4666-8282-5.ch011

Chicago

Cassandras, Christos G. "New Transportation Systems for Smart Cities." In Handbook of Research on Social, Economic, and Environmental Sustainability in the Development of Smart Cities, edited by Andrea Vesco and Francesco Ferrero, 213-238. Hershey, PA: IGI Global, 2015. https://doi.org/10.4018/978-1-4666-8282-5.ch011

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Abstract

Poor traffic management in urban environments is responsible for congestion, unnecessary fuel consumption and pollution. Based on new wireless sensor networks and the advent of battery-powered vehicles, this chapter describes three new systems that affect transportation in Smart Cities. First, a Smart Parking system which assigns and reserves an optimal parking space based on the driver's cost function, combining proximity to destination and parking cost. Second, a system to optimally allocate electric vehicles to charging stations and reserve spaces for them. Finally, we address the traffic light control problem by viewing the operation of an intersection as a stochastic hybrid system. Using Infinitesimal Perturbation Analysis (IPA), we derive on-line gradient estimates of a cost metric with respect to the controllable green and red cycle lengths and iteratively adjust light cycle lengths to improve (and possibly optimize) performance, as well as adapt to changing traffic conditions.

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