title: An Improved Simulated Annealing Technique for Enhanced Mobility in Smart Cities.
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.
authors.affiliation: Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK. hmamer1@sheffield.ac.uk.
authors.forename: Hayder
authors.initials: H
authors.lastname: Amer
authors.affiliation: Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK. n.salman@sheffield.ac.uk.
authors.forename: Naveed
authors.initials: N
authors.lastname: Salman
authors.affiliation: Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK. m.hawes@sheffield.ac.uk.
authors.forename: Matthew
authors.initials: M
authors.lastname: Hawes
authors.affiliation: College of Information Technology, UAE University, Al Ain 15551, United Arab Emirates. moumena@uaeu.ac.ae.
authors.forename: Moumena
authors.initials: M
authors.lastname: Chaqfeh
authors.affiliation: Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK. l.s.mihaylova@sheffield.ac.uk.
authors.forename: Lyudmila
authors.initials: L
authors.lastname: Mihaylova
authors.affiliation: Department of Civil and Structural Engineering, University of Sheffield, Sheffield S1 3JD, UK. martin.mayfield@sheffield.ac.uk.
authors.forename: Martin
authors.initials: M
authors.lastname: Mayfield
keywords: Internet of Things; Internet of Vehicles; multi-objective optimisation; simulated annealing; traffic congestion; vehicle re-routing