Koh, SS, Zhou, B, Yang, P and Yang, Z Study of Group Route Optimization for IoT enabled Urban Transportation Network. In: IEEE CPSCom/GreenCom/iThings/SmartData, 21 June 2017 - 23 June 2017, Exeter, Devon. (Accepted)

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Abstract

Traffic congestion is always a major issue in urban planning, especially when the vehicles in the roadway keep growing and the local authorities are lack of solutions to manage or distribute the traffics in the city. Although there are several factors that may cause traffic congestion, inefficiency in traffic management is always the main issue. Additionally, the most traditional methods of resolving traffic congestion or rerouting algorithm are mainly designed for individuals’ benefits, by simply planning a driver’s route based on minimum travel time or shortest path accordingly. There is lack of consideration in group benefit or urban development. However, with the development of technologies in Internet of Things (IoT), vehicle to vehicle (V2V) or Vehicle to Infrastructure (V2I) communications, group based routing becomes achievable. Instead of optimizing the routing path for individual drivers, this paper studies how to develop a new method to provide new routing method based on vehicles’ similarities in a specific urban’s transportation environment

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Computer Science & Mathematics
Publisher:	IEEE
Date Deposited:	26 Jun 2017 10:30
Last Modified:	13 Apr 2022 15:15
URI:	https://researchonline.ljmu.ac.uk/id/eprint/6604

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