SMARTS

Author:

Ramamohanarao Kotagiri1,Xie Hairuo1,Kulik Lars1,Karunasekera Shanika1,Tanin Egemen1,Zhang Rui1,Khunayn Eman Bin1

Affiliation:

1. University of Melbourne, Victoria, Australia

Abstract

Microscopic traffic simulators are important tools for studying transportation systems as they describe the evolution of traffic to the highest level of detail. A major challenge to microscopic simulators is the slow simulation speed due to the complexity of traffic models. We have developed the Scalable Microscopic Adaptive Road Traffic Simulator (SMARTS), a distributed microscopic traffic simulator that can utilize multiple independent processes in parallel. SMARTS can perform fast large-scale simulations. For example, when simulating 1 million vehicles in an area the size of Melbourne, the system runs 1.14 times faster than real time with 30 computing nodes and 0.2s simulation timestep. SMARTS supports various driver models and traffic rules, such as the car-following model and lane-changing model, which can be driver dependent. It can simulate multiple vehicle types, including bus and tram. The simulator is equipped with a wide range of features that help to customize, calibrate, and monitor simulations. Simulations are accurate and confirm with real traffic behaviours. For example, it achieves 79.1% accuracy in predicting traffic on a 10km freeway 90 minutes into the future. The simulator can be used for predictive traffic advisories as well as traffic management decisions as simulations complete well ahead of real time. SMARTS can be easily deployed to different operating systems as it is developed with the standard Java libraries.

Funder

Linkage Project

Discovery Project

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Theoretical Computer Science

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2. CityFlowER: An Efficient and Realistic Traffic Simulator with Embedded Machine Learning Models;Lecture Notes in Computer Science;2024

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