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Study of Group Route Optimization for IoT enabled Urban Transportation Network

Koh, SS, Zhou, B, Yang, P and Yang, Z (2017) Study of Group Route Optimization for IoT enabled Urban Transportation Network. In: 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) . (IEEE CPSCom/GreenCom/iThings/SmartData, 21 June 2017 - 23 June 2017, Exeter, Devon).

Study of Group Route Optimization for IoT enabled Urban Transportation Network.pdf - Accepted Version

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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)
Additional Information: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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: 30 May 2024 10:47
DOI or ID number: 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.137
URI: https://researchonline.ljmu.ac.uk/id/eprint/6604
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