An Adaptive and Hotspot Aware Taxi Zone Queuing System on Internet of Vehicles

Abstract

Taxis have a vital role in the transportation system and Internet of Vehicles (IoV) techniques can be used to improve the fuel and time efficiencies of taxis. However, the existing work does not address the traffic congestion that may occur when a large amount of taxis gathers in certain queuing areas. This paper proposes an adaptive and hotspot-aware taxi zone queuing system to deal with the problem while still guarantees the fuel and time efficiencies. The adaptive scheme features data collection, hotspot extraction, an adaptive zone queuing protocol, and navigation services for taxi drivers. Real data were collected from Taiwan Taxi Inc., the largest taxi company in Taiwan. Queuing zone hotspots were identified through the analysis of the collected data. The hotspots represented. A navigation service was based on the proposed protocol. To verify the feasibility of the proposed system, a prototype was implemented. The experimental results demonstrated that the proposed scheme outperformed other schemes in reducing waiting time and the average number of taxis.