Physics-Based Sensor Models for Virtual Simulation of Connected and Autonomous Vehicles
This document contains the final project report for the SAFER-SIM project titled “Physics-Based Sensor Models for Virtual Simulation of Connected and Autonomous Vehicles.” The report includes discussion of sensors models for simulation autonomous vehicles, and overviews the simulation framework developed in accordance with the project. The framework, called Chrono::Sensor is developed as a module alongside Project Chrono to augment the open-source multi-physics engine with the capability to simulation sensor data from within its virtual environment. Chrono::Sensor provides support for the modeling and simulation of camera, Light Detection and Ranging (lidar), Global Positioning System (GPS), and Inertial Measurement Unit (IMU). It also provides a framework to implement custom sensors that can leverage existing sensor generation functionality. Chrono::Sensor generates data using ray-tracing algorithms that mimic the data acquisition process of cameras and lidars. In addition to data collection, the sensors support further data augmentation including the addition of sensor-specific noise. Results from each sensor implementation are included as part of the corresponding sensor discussion, with the report concluding with two demonstrations showing the use of Chrono::Sensor, in combination with Chrono, to simulate autonomous vehicles.
- Dataset URL:
- Record URL:
- Record URL:
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Supplemental Notes:
- This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program. Supporting datasets available at: https://doi.org/10.7910/DVN/KMDINO
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Corporate Authors:
Safety Research Using Simulation University Transportation Center (SaferSim)
University of Iowa
Iowa City, IA United States 52242Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Authors:
- Negrut, Dan
- 0000-0003-1565-2784
- Serban, Radu
- 0000-0002-4219-905X
- Elmquist, Asher
- 0000-0002-0142-1865
- Publication Date: 2020-5
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; Photos; References; Tables;
- Pagination: 47p
Subject/Index Terms
- TRT Terms: Algorithms; Autonomous vehicles; Cameras; Connected vehicles; Data collection; Global Positioning System; Laser radar; Sensors; Simulation
- Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01754652
- Record Type: Publication
- Contract Numbers: 69A3551747131
- Files: UTC, NTL, TRIS, ATRI, USDOT
- Created Date: Oct 14 2020 5:41PM