A Choudhury, T Maszczyk, CB Math, H Li, J Dauwels . A Comprehensive Simulation Environment for Testing the Applications of a V2X Infrastructure. Augmented Intelligence Toward Smart Vehicular Applications, 97-122
Abstract:
It is a well established fact that road transportation is one of the major contributors of greenhouse gases. The increase in the number of light and heavy vehicles in cities everyday is providing additional impetus to this predicament. A solution for reducing greenhouse gas emissions would be to “engineer” traffic
to decrease congestion. One particular engineering-based solution can be to provide a Green Light Optimized Speed Advisory (GLOSA). This method involves communicating the remaining phase time to vehicles approaching a junction, which can be used to compute an approach speed that will not require the vehicle to stop. However, the field implementation of this solution would require installation of communication devices on both traffic signal heads and on vehicles, which would involve considerable
cost and policy changes. Therefore, before implementation, it is desirable that any predicted benefits be gauged using alternative means, so that the profitability of the installed infrastructure can be justified. We therefore present, a novel simulation platform, which combines VISSIM, MATLAB and NS3 in order to model
the various components of a V2X-based application such as GLOSA with a high level of fidelity. In this chapter, we apply this simulation platform to compute the benefits of implementing GLOSA on two intersections, one located in Singapore and the parameters, levels of V2X penetration and traffic
signal policy.
other located in Eindhoven, in the Netherlands. The results
illustrate the reduction in fuel consumption and queue length
due to the execution of GLOSA, for different traffic flows,
communication
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the Economic Development Board (EDB) - NTU-NXP Intelligent Transport System Test-Bed Living Lab
Grant Reference no. : S15-1105-RF-LLF
Description:
This is an Accepted Manuscript of a book chapter published by Routledge/CRC Press in Augmented Intelligence Toward Smart Vehicular Applications on 19 Dec 2020, available online: http://www.routledge.com/doi.org/10.1201/9781003006817