Should drivers cooperate? Performance evaluation of cooperative navigation on simulated road networks using network DEA

Nichalin S. Summerfield, Amit V. Deokar, Mei Xu and Weiwei Zhu

Journal of the Operational Research Society, 2021, vol. 72, issue 5, 1042-1057

Abstract: For drivers, traffic congestion causes enormous delays and increases energy consumption. For a city’s traffic management team, traffic congestion challenges economic growth and increases pollution. Many drivers rely on a GPS navigation system to choose the fastest route to reach their destination. The GPS algorithms generally work for a single driver, while ignoring their collective resulting impact on the road network. If there exists a cooperative centralised routing algorithm that minimises the whole network congestion, the city can greatly benefit from congestion reduction, though some drivers may suffer from such a cooperative routing algorithm. These drivers may opt-out from the cooperative centralised routing, which, in turn, impacts the whole network routing efficiency. So, does having higher proportions of cooperative drivers on the road network always work better? In this paper, we take a heuristic cooperative routing algorithm which minimises the network congestion. We simulate a road network and measure its performance under various proportions of cooperative drivers. We measure both the congestion and the average drivers’ perceived road network performance. Network data envelopment analysis (network DEA) technique is used to see which proportions of cooperative drivers can best benefit the city and drivers collectively.

Date: 2021
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DOI: 10.1080/01605682.2019.1700766

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