{"title":"Towards a Benchmark for the Quantitative Evaluation of Traffic Simulators","authors":"Priya Toshniwal, Masatoshi Hanai, Elvis S. Liu","doi":"10.1145/3064911.3064928","DOIUrl":null,"url":null,"abstract":"Smart city projects, infrastructure planning, and traffic engineering are some of the applications where traffic simulations are playing an increasingly important role. Although many traffic simulators, commercial or open-sourced, are available at our disposal today, choosing the one that best fits a user's requirements is usually not possible by taking into account only the qualitative aspects and features of the simulator. In resource-constrained simulation platforms, performing traffic simulations with less memory usage and faster execution time is always highly coveted. In this paper, we propose a quantitative benchmarking approach for evaluating the performance of traffic simulator, based on commonplace scenarios and real-life city maps.","PeriodicalId":341026,"journal":{"name":"Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"50 5-6","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3064911.3064928","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Smart city projects, infrastructure planning, and traffic engineering are some of the applications where traffic simulations are playing an increasingly important role. Although many traffic simulators, commercial or open-sourced, are available at our disposal today, choosing the one that best fits a user's requirements is usually not possible by taking into account only the qualitative aspects and features of the simulator. In resource-constrained simulation platforms, performing traffic simulations with less memory usage and faster execution time is always highly coveted. In this paper, we propose a quantitative benchmarking approach for evaluating the performance of traffic simulator, based on commonplace scenarios and real-life city maps.