T-START: Time, Status and Region Aware Taxi Mobility Model for Metropolis

• Haiquan Wang,
• Shuo Lei,
• Binglin Wu,
• Yilin Li,
• Bowen Du,

Vol. 12, No. 7, July 30, 2018
10.3837/tiis.2018.07.004, Download Paper (Free):

• mobility model
• taxi status
• region transition probability
• urban vehicular networks

Abstract

The mobility model is one of the most important factors that impacts the evaluation of any transportation vehicular networking protocols via simulations. However, to obtain a realistic mobility model in the dynamic urban environment is a very challenging task. Several studies extract mobility models from large-scale real data sets (mostly taxi GPS data) in recent years, but they do not consider the statuses of taxi, which is an important factor affected taxi’s mobility. In this paper, we discover three simple observations related to the taxi statuses via mining of real taxi trajectories: (1) the behavior of taxi will be influenced by the statuses, (2) the macroscopic movement is related with different geographic features in corresponding status, and (3) the taxi load/drop events are varied with time period. Based on these three observations, a novel taxi mobility model (T-START) is proposed with respect to taxi statuses, geographic region and time period. The simulation results illustrate that proposed mobility model has a good approximation with reality in trajectory samples and distribution of nodes in four typical time periods.

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