Russell, Gordon, Shaw, Paul and Ferguson, Neil (1996) Accurate rapid simulation of urban traffic using discrete modelling. Technical Report. Edinburgh Napier University.
Available under License Creative Commons Attribution Non-commercial.
Increasing model complexity has traditionally been viewed as a key way of improving microscopic model accuracy. However, with complexity comes an increase in execution time. In some applications, such as UTC systems, low execution times and a high degree of accuracy are important design objectives. Discrete modelling can allow fast execution times to be attained, but this approach has always been viewed as an inaccurate approach to traffic simulation.
In this paper, we investigate the accuracy of the JUDGE model. This model was developed to be as simple and accurate as possible. Model complexities were only included where the improved accuracy could be justified. This has produced a simple, discrete modelling technique which can rival many traditionally derived microscopic models in accuracy terms, with a simulation speed for entire cities measurably faster than real-time. We give a high-level introduction to the proposed target application of the JUDGE model, its underlying structure, and a summary of some other research into high-speed modelling techniques. We then present out graphical interface to the JUDGE model, and compare results generated by JUDGE to results calculated from theory. We believe that these results show that the JUDGE modelling scheme is sufficiently accurate to be used as a slot-in replacement for many systems currently based on traditional (and significantly slower) microscopic modelling techniques.
|Item Type:||Monograph (Technical Report)|
|Uncontrolled Keywords:||model accuracy; UTC systems; discrete; traffic simulation; JUDGE model;; accuracy; microscopic modelling;|
|University Divisions/Research Centres:||Faculty of Engineering, Computing and Creative Industries > School of Computing|
|Dewey Decimal Subjects:||000 Computer science, information & general works > 000 Computer science, knowledge & systems > 003 Systems > 003.3 Computer modelling & simulation|
|Library of Congress Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Depositing User:||Computing Research|
|Date Deposited:||09 Sep 2010 15:00|
|Last Modified:||12 Jan 2011 04:52|
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