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Energy Efficient Route Planning Using VANET

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  • Tue, 12/05/2017 - 10:00am - 11:30am




Energy Efficient Route Planning Using VANET

MSc Thesis Defense by:

Nazmul Sumon

Date:  Tuesday, Dec 5, 2017
Time:  10:00 am – 11:30 am
Location: 3105, Lambton Tower

Abstract: One of the key challenges in conducting dynamic route planning is the process of collecting and disseminating instantaneous travel data in real time. Recent studies are evaluating VANET (Vehicular Ad Hoc Network) and its associated WAVE (Wireless Access in Vehicular Environment) standards to facilitate this process. In these studies, travel data accumulated from vehicle OBUs (on board unit) are shared with other vehicles over DSRC (dedicated short- range communication) medium using centralized or distributed approach. In most studies, data collection and dissemination process are not scalable enough for high density traffic environment. Specifically, with a centralized approach if traffic management center (TMC) or RSU performs route planning for vehicles, there will be many bidirectional communication between the centralized entity and vehicles, leading to higher channel congestion in heavy traffic area. With distributed approach, information shared by other vehicles might not be useful or pertinent for an ego vehicle, leading to wastage of channel bandwidth. Methods used for data collection also needs to intelligent to count in non-traditional circumstances to achieve accuracy. In this paper, we have proposed a three tiered architecture for data collection, analysis and dissemination. In addition, 1) we used the concept of queuing delay at intersection for travel time calculation and developed a hybrid metric that considers average travel time and occupancy rate, 2) we offload the computation of route planning to vehicle OBUs and 3) we developed an algorithm that determines the area of propagation for data that needs to be disseminated. We evaluated the performance of our approach progressively using VEINS, SUMO and OMNET++ simulators.

Thesis Committee:
Internal Reader: Dr. Mehdi Kargar  
External Reader: Dr. Kemal Tepe     
Advisors: Dr. Arunita Jaekel and Dr. Robert D. Kent
Chair:  Dr. Dan Wu



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