The METS-R SIM was initially developed for the project Multi-modal Energy-optimal Trip Scheduling in Real-time. Through extensive development, METS-R has evolved into a comprehensive road traffic simulator capable of scaling to large road networks. Similar to existing traffic simulators such as SUMO and VISSIM, METS-R employs car-following and lane-changing models to accurately simulate vehicle interactions, providing user-friendly online APIs for monitoring and manipulating vehicle and service behaviors.
Distinct from other simulators, METS-R Simulator uniquely:
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Introduces a structured framework for shared mobility services, including ride-hailing and microtransit, driven by intelligent agents representing geographic zones, service requests, and detailed travel plans for vehicles and passengers.
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Utilizes Kafka for real-time simulation of data streams generated by connected vehicles.
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Integrates seamlessly with Scenic for sophisticated scenario generation and testing.
METSR_demo.-.Made.with.Clipchamp.mp4
| Resource name | Link |
|---|---|
| The latest document | https://umnilab.github.io/METS-R_doc/ |
| The HPC module | https://github.com/umnilab/METS-R_HPC |
| A visualization demo | https://engineering.purdue.edu/HSEES/METSRVis/ |
| The simulation paper | https://www.sciencedirect.com/science/article/abs/pii/S1569190X24000121 |
The current contributors of METS-R SIM are Zengxiang Lei ([email protected]) and Ruichen Tan ([email protected]). If you have any questions, please feel free to contact them.
The following people contributed directly to the source code of the METS-R SIM until 2021: Zengxiang Lei, Jiawei Xue, Xiaowei Chen, Charitha Samya, Juan Esteban Suarez Lopez, and Zhenyu Wang.
METS-R SIM was developed based on a hurricane evacuation simulator named A-RESCUE, whose authors are: Xianyuan Zhan, Samiul Hasan, Christopher Thompson, Xinwu Qian, Heman Gelhot, Wenbo Zhang, Zengxiang Lei, and Rajat Verma.
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Lei, Z., Xue, J., Chen, X., Qian, X., Saumya, C., He, M., ... & Ukkusuri, S. V. (2024). METS-R SIM: A simulator for Multi-modal Energy-optimal Trip Scheduling in Real-time with shared autonomous electric vehicles. Simulation Modelling Practice and Theory, 132, 102898.
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Lei, Z., Xue, J., Chen, X., Saumya, C., Qian, X., He, M., ... & Ukkusuri, S. V. (2021). ADDS-EVS: An agent-based deployment decision-support system for electric vehicle services. In 2021 IEEE International Intelligent Transportation Systems Conference (ITSC) (pp. 1658-1663). IEEE
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Chen, X., Xue, J., Lei, Z., Qian, X., & Ukkusuri, S. V. (2022). Online eco-routing for electric vehicles using combinatorial multi-armed bandit with estimated covariance. Transportation Research Part D: Transport and Environment, 111, 103447.
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Qian, X., Xue, J., & Ukkusuri, S. V. (2021). Demand-adaptive route planning and scheduling for urban hub-based high-capacity mobility-on-demand services. Accepted in ISTTT 24 Proceedings.
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Qian, X., Xue, J., Sobolevsky, S., Yang, C., & Ukkusuri, S. (2019). Stationary spatial charging demand distribution for commercial electric vehicles in urban area. In 2019 IEEE intelligent transportation systems conference (ITSC) (pp. 220-225). IEEE.
- Chen, X., Lei, Z., & Ukkusuri, S. V. (2024). Modeling the influence of charging cost on electric ride-hailing vehicles. Transportation Research Part C: Emerging Technologies, 160, 104514.