Agent-Based Implementation of Particle Hopping Traffic Model With Stochastic and Queuing Elements

Abstract

Lagging or halted traffic is bothersome. As such, it is desirable to have a model that can begin to determine the efficiency of various traffic standardizations. Our model intended to create a multifaceted realistic simulation of traffic flow while considering several factors. These factors included: passing conventions, e.g., right except to pass (REP) rule, system perturbation caused by insertion of an accident into the system, accessible number of lanes available with the REP, various human factors such as variation of individual maximum speed and likelihood to pass. A succession of models were created from a variation on an existing single-lane traffic model and adding extra dimensionality to the lattice to include multiple lanes, passing conventions, stochastic elements for individuality, and queuing rules to movement algorithms. We found that the REP is an effective means of increasing the critical density that a system can support. Eliminating human factors and thereby automating the system, results in a 160% increase in the sustainable critical density of the system. The number of lanes increases the critical density of the system, but the maximum efficiency of the speed distribution remains the same. Excluding system automation, the optimal speed distribution for drivers maximal speed was found to be Beta(5,5). Accidents in stable systems can cause small local jams without causing global jams.