The use of high level architecture in car traffic simulations
Although a number of car-traffic simulators have been developed fur various purposes, none of the existing simulators enhance the simulation accuracy using sensor data or allow the system structure to re-configure the system structure depending on the application. Our goal was to develop a highly accurate, highly modular, flexible, and scalable micro-model car-traffic simulation syst,em. The HLA (High Level Architecture) was applied to every system module as a standard interface between each module. This allows an efficient means for evaluating and validating a variety of micro-model simulation schemes. Our ongoing projects consist of running several identical simulations concurrently, with different parameter sets. By sending the results of these simulations to a manager module, which analyzes both the parameter sc ta and the simulated results, the manager module can evaluate the best-simulated results and determine the next action LS comparing these results with the sensor data. In this system, the sensor data or the statistical data on the flow of traffic, obtained LS monitoring real roads, is used to improve the simulation accuracy. Future systems are being planned to employ real time sensor data, where the input of the data occurs at almost real time speed. In this paper, we discuss the design of a HLA-based car-traffic simulation system and the construction of a sensor-data fusion algorithm. We also discuss our preliminary Evaluation of the results obtained with this system. The results show that the proposed fusion algorithm can adjust the simulation accuracy to the logged sensor data within a difference of 5% (minimum 1.5%) in a specific: time period. We also found that simulations with 500 different parameter sets can be executed within 5 minutes using 8 simulator modules.
car traffic simulation hla fusion algorithm parallel and distributed simulation large scale simulation erti