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QarSUMO: A Parallel, Congestion-optimized Traffic Simulator

Authors:

Stefano Giovanni Rizzo,

Giovanna Vantini,

Phillip Taylor,

Sanjay ChawlaAuthors Info & Claims

SIGSPATIAL '20: Proceedings of the 28th International Conference on Advances in Geographic Information Systems

Pages 578 - 588

https://doi.org/10.1145/3397536.3422274

Published: 13 November 2020 Publication History

Abstract

Traffic simulators are important tools for tasks such as urban planning and transportation management. Microscopic simulators allow per-vehicle movement simulation, but require longer simulation time. The simulation overhead is exacerbated when there is traffic congestion and most vehicles move slowly. This in particular hurts the productivity of emerging urban computing studies based on reinforcement learning, where traffic simulations are heavily and repeatedly used for designing policies to optimize traffic related tasks.

In this paper, we develop QarSUMO, a parallel, congestion-optimized version of the popular SUMO open-source traffic simulator. QarSUMO performs high-level parallelization on top of SUMO, to utilize powerful multi-core servers and enables future extension to multi-node parallel simulation if necessary. The proposed design, while partly sacrificing speedup, makes QarSUMO compatible with future SUMO improvements. We further contribute such an improvement by modifying the SUMO simulation engine for congestion scenarios where the update computation of consecutive and slow-moving vehicles can be simplified. We evaluate QarSUMO with both real-world and synthetic road network and traffic data, and examine its execution time as well as simulation accuracy relative to the original, sequential SUMO.

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Cited By

Zhu HMa RJin JLu H(2024)Accelerating Distributed Urban Traffic Simulation via Enhanced Stale Synchronous Parallelism2024 11th International Conference on Behavioural and Social Computing (BESC)10.1109/BESC64747.2024.10780495(1-9)Online publication date: 16-Aug-2024
https://doi.org/10.1109/BESC64747.2024.10780495
Zhang JAo WJin DLiu LLi Y(2023)A City-level High-performance Spatio-temporal Mobility Simulation SystemProceedings of the 1st ACM SIGSPATIAL International Workshop on Sustainable Mobility10.1145/3615899.3627936(23-32)Online publication date: 13-Nov-2023
https://dl.acm.org/doi/10.1145/3615899.3627936
Liang CHuang ZLiu YLiu ZZheng GShi HWu KDu YLi FLi ZSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)CBLab: Supporting the Training of Large-scale Traffic Control Policies with Scalable Traffic SimulationProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599789(4449-4460)Online publication date: 6-Aug-2023
https://dl.acm.org/doi/10.1145/3580305.3599789
Show More Cited By

Index Terms

QarSUMO: A Parallel, Congestion-optimized Traffic Simulator
1. Computer systems organization
  1. Architectures
    1. Parallel architectures
2. Information systems
  1. Information systems applications
    1. Spatial-temporal systems

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cover image ACM Conferences

SIGSPATIAL '20: Proceedings of the 28th International Conference on Advances in Geographic Information Systems

November 2020

687 pages

ISBN:9781450380195

DOI:10.1145/3397536

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Published: 13 November 2020

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SIGSPATIAL '20: 28th International Conference on Advances in Geographic Information Systems

November 3 - 6, 2020

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Cited By

Zhu HMa RJin JLu H(2024)Accelerating Distributed Urban Traffic Simulation via Enhanced Stale Synchronous Parallelism2024 11th International Conference on Behavioural and Social Computing (BESC)10.1109/BESC64747.2024.10780495(1-9)Online publication date: 16-Aug-2024
https://doi.org/10.1109/BESC64747.2024.10780495
Zhang JAo WJin DLiu LLi Y(2023)A City-level High-performance Spatio-temporal Mobility Simulation SystemProceedings of the 1st ACM SIGSPATIAL International Workshop on Sustainable Mobility10.1145/3615899.3627936(23-32)Online publication date: 13-Nov-2023
https://dl.acm.org/doi/10.1145/3615899.3627936
Liang CHuang ZLiu YLiu ZZheng GShi HWu KDu YLi FLi ZSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)CBLab: Supporting the Training of Large-scale Traffic Control Policies with Scalable Traffic SimulationProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599789(4449-4460)Online publication date: 6-Aug-2023
https://dl.acm.org/doi/10.1145/3580305.3599789
Bin Khunayn EXie HKarunasekera SRamamohanarao K(2023)Dynamic Straggler Mitigation for Large-Scale Spatial SimulationsACM Transactions on Spatial Algorithms and Systems10.1145/35789339:2(1-34)Online publication date: 6-Jan-2023
https://dl.acm.org/doi/10.1145/3578933
Varga BOrmándi TTettamanti T(2023)EGO-Centric, Multi-Scale Co-Simulation to Tackle Large Urban Traffic ScenariosIEEE Access10.1109/ACCESS.2023.328431611(57437-57447)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3284316
Potuzak T(2022)Current Trends in Road Traffic Network Division for Distributed or Parallel Road Traffic Simulation2022 IEEE/ACM 26th International Symposium on Distributed Simulation and Real Time Applications (DS-RT)10.1109/DS-RT55542.2022.9932112(77-86)Online publication date: 26-Sep-2022
https://doi.org/10.1109/DS-RT55542.2022.9932112
Wang JJiang JJiang WLi CZhao W(2021)LibCityProceedings of the 29th International Conference on Advances in Geographic Information Systems10.1145/3474717.3483923(145-148)Online publication date: 2-Nov-2021
https://dl.acm.org/doi/10.1145/3474717.3483923

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