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Sensors 2016, 16(7), 1013; doi:10.3390/s16071013

An Improved Simulated Annealing Technique for Enhanced Mobility in Smart Cities

1
Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK
2
College of Information Technology, UAE University, Al Ain 15551, United Arab Emirates
3
Department of Civil and Structural Engineering, University of Sheffield, Sheffield S1 3JD, UK
*
Author to whom correspondence should be addressed.
Academic Editors: Andrea Zanella and Toktam Mahmoodi
Received: 24 April 2016 / Revised: 23 June 2016 / Accepted: 24 June 2016 / Published: 30 June 2016
(This article belongs to the Special Issue Smart City: Vision and Reality)
View Full-Text   |   Download PDF [4387 KB, uploaded 30 June 2016]   |  

Abstract

Vehicular traffic congestion is a significant problem that arises in many cities. This is due to the increasing number of vehicles that are driving on city roads of limited capacity. The vehicular congestion significantly impacts travel distance, travel time, fuel consumption and air pollution. Avoidance of traffic congestion and providing drivers with optimal paths are not trivial tasks. The key contribution of this work consists of the developed approach for dynamic calculation of optimal traffic routes. Two attributes (the average travel speed of the traffic and the roads’ length) are utilized by the proposed method to find the optimal paths. The average travel speed values can be obtained from the sensors deployed in smart cities and communicated to vehicles via the Internet of Vehicles and roadside communication units. The performance of the proposed algorithm is compared to three other algorithms: the simulated annealing weighted sum, the simulated annealing technique for order preference by similarity to the ideal solution and the Dijkstra algorithm. The weighted sum and technique for order preference by similarity to the ideal solution methods are used to formulate different attributes in the simulated annealing cost function. According to the Sheffield scenario, simulation results show that the improved simulated annealing technique for order preference by similarity to the ideal solution method improves the traffic performance in the presence of congestion by an overall average of 19.22% in terms of travel time, fuel consumption and CO2 emissions as compared to other algorithms; also, similar performance patterns were achieved for the Birmingham test scenario. View Full-Text
Keywords: traffic congestion; Internet of Vehicles; Internet of Things; simulated annealing; multi-objective optimisation; vehicle re-routing traffic congestion; Internet of Vehicles; Internet of Things; simulated annealing; multi-objective optimisation; vehicle re-routing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Amer, H.; Salman, N.; Hawes, M.; Chaqfeh, M.; Mihaylova, L.; Mayfield, M. An Improved Simulated Annealing Technique for Enhanced Mobility in Smart Cities. Sensors 2016, 16, 1013.

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