ITS-based Eco-Routing For Vehicle Navigation System

Alamir Tamer, Abdul-Hak, Arafat, Mohammad, and Al-Holou

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Transportation activities is the fastest growing source of U.S. greenhouse gas emissions and the second-largest source of the End-user sector, accounting for 33.1% of total energy-related CO2 emissions in 2008. Given this significant impact of motor vehicle emissions on the environment and the demand for reducing the dependency on oil, Intelligent Transportation Systems (ITS) technologies have recently focused on innovative eco-friendly solutions to “green” driving behavior. One potential solution includes advising techniques that guide the driver in fuel consumption minimizing routes: “Eco-Routing.” Recently, some car navigation systems have integrated the Eco-Routing service into their systems, utilizing different estimated emission models. However, these existing models are calculated on the basis of either predetermined or measured road link attributes, such as traffic density and average speed, which are then used as cost factors to determine the optimal route. This approach doesn’t take into consideration the change of traffic conditions. In real-time scenarios, the newly developed Dedicated Short-Range Communications (DSRC) standard, which has been the target communication technology for the IntelliDrive implementation in Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communications, provides vehicles with the capability of exchanging real-time information on traffic situations due to its superiority in communication latency.

In this research we discuss the concepts of various real-time shortest/fastest routing algorithms in addition to static ecological route search algorithms. An innovative dynamic Eco-Routing algorithm is proposed.

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This algorithm is targeted to achieve two main objectives:

1. Calculating the cost of route in terms of emission, hence reducing fuel consumption.

2. Improving the accuracy of the predictive fuel consumption model by involving real-time traffic information obtained from V2V and V2I communications.

 

Our proposed algorithm is expected to be widely applied on the long term. However, we have chosen to utilize two powerful tools; Navit, which is an open source car navigation software with routing engine, and iTETRES platform which implements an open-source integrated wireless (NS3) and traffic simulation software (SUMO) providing the capability of using V2X technologies over large scale scenarios.

Simulation results will be aimed to show that our proposed Eco-Routing algorithm will outperform similar algorithms in terms of finding the most fuel -efficient route, based on more realistic emission-aware road costs.