The Use of High Level Architecture in Car Traffic Simulations

Atsuo OZAKI  Masakazu FURUICHI  Nobuo NISHI  Etsuji KURODA  

IEICE TRANSACTIONS on Information and Systems   Vol.E83-D    No.10    pp.1851-1859
Publication Date: 2000/10/25
Online ISSN: 
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Software Systems
car traffic simulation,  fusion algorithm,  parallel and distributed simulation,  large scale simulation,  HLA,  eRTI,  

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Although a number of car-traffic simulators have been developed for 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 system. 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 sets and the simulated results, the manager module can evaluate the best-simulated results and determine the next action by comparing these results with the sensor data. In this system, the sensor data or the statistical data on the flow of traffic, obtained by 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.

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