Mobile Computing Traffic Simulation Data Process

Abstract

This paper presents a mobile computing traffic simulation based on an ad hoc distributed simulation with optimistic execution. In this system, data collection, processing, and simulations are performed in a distributed fashion. Each individual simulator models the current traffic conditions of its local vicinity focusing only on its area of interest, without modeling other less relevant areas. Collectively, a central server coordinates the overall simulations with an optimistic execution technique and provides a predictive model of traffic conditions in large areas by combining simulations geographically spread over large areas. This distributed approach increases computing capacity of the entire system and speed of execution. The proposed model manages the distributed network, synchronizes the predictions among simulators, and resolves simulation output conflicts. Proper feedback allows each simulator to have accurate input data and eventually produce predictions close to reality. Such a system could provide both more up-to-date and robust predictions than that offered by centralized simulations within a single transportation management center. As these systems evolve, the mobile computing online traffic predictions can be used in surface transportation management and travelers will benefit from more accurate and reliable traffic forecast.