Multi-Modal Traffic Simulation Calibration and Integration with Real-Time Hardware in Loop Simulator
2022-01-0164
03/29/2022
- Event
- Content
- The ongoing research in intelligent transport systems and connected and automated vehicles, enabled by advancements in artificial intelligence, integrating traffic simulations has become an essential part of product/software development for the automotive industry. Nowadays, traffic simulations are used to mimic real-world environment scenarios for connected and automated driving assist systems (ADAS). With the increase in data collection methods for traffic flow, the calibration of the microscopic traffic simulations has emerged as an important research area. The underlying question in traffic modeling is how accurately simulations can mimic the real environment traffic flow conditions? This paper attempts to create a framework for microscopic traffic simulation calibration procedure which can be scaled for large networks. This paper makes the following major contributions. First, a calibration framework is proposed which harnesses the existing GPS data set of OSU campus shuttles (CABS) to determine the traffic state in the real environment and create a microscopic traffic simulation. The traffic simulation is implemented for a section of the OSU campus (“Woody Hayes Drive") in an open-source traffic simulator (SUMO) which can be extended to the entire OSU campus. The traffic flow generation is probabilistic to introduce variability between scenarios. The second contribution is the development of a communication interface between real-time dSpace ASM Hardware in Loop setup with SUMO to create a complete real-time simulation of urban environments for ADAS testing. The demo scenario is the Ohio State University campus network with traffic demand generated using the calibrated model from the first part of the work.
- Citation
- kalra, V., Tulpule, P., and Isaman, J., "Multi-Modal Traffic Simulation Calibration and Integration with Real-Time Hardware in Loop Simulator," SAE Technical Paper 2022-01-0164, 2022, .