This page contains a limited bibliography of technical papers and presentations related to CarSim and TruckSim in real-time applications such as driving simulators and testing of hardware in the loop (HIL).
Joshi, A., "Real-Time Implementation and Validation for Automated Path Following Lateral Control Using Hardware-in-the-Loop (HIL) Simulation," SAE Technical Paper 2017-01-1683, 2017, doi:10.4271/2017-01-1683. SAE paper 2017-01-1683. March 2017. Show summary
Software for autonomous vehicles is highly complex and requires vast amount of vehicle testing to achieve a certain level of confidence in safety, quality and reliability. According to the RAND Corporation, a 100 vehicle fleet running 24 hours a day 365 days a year at a speed of 40 km/hr, would require 17 billion driven kilometers of testing and take 518 years to fully validate the software with 95% confidence such that its failure rate would be 20% better than the current human driver fatality rate . In order to reduce cost and time to accelerate autonomous software development, Hardware-in-the-Loop (HIL) simulation is used to supplement vehicle testing. For autonomous vehicles, path following controls are an integral part for achieving lateral control. Combining the aforementioned concepts, this paper focuses on a real-time implementation of a path-following lateral controller, developed by Freund and Mayr . The controller is implemented on a powertrain subsystem HIL simulation bench to enable lateral control of the longitudinal controlled HIL setup for automated driving applications. 2017 Ford Fusion Hybrid powertrain controllers and actuators were used as the hardware platform for the powertrain subsystem. The simulation of other subsystem plants and controllers was achieved by using a real-time CarSim-Simulink co-simulation environment representative of the 2017 Ford Fusion Hybrid through a dSPACE HIL simulator.The objectives of this research were three-fold. The first objective was to implement a real-time version of the path-following lateral controller to add lateral capability to a powertrain-based longitudinal controlled HIL setup. The second objective was to validate the path-following capability of the lateral controller. Lastly, the third objective was to quantitatively understand the real-time behavior and sensitivity of the lateral controller using simulations over varying vehicle inertial and environmental conditions such as speed, payload mass, payload position, surface type/friction, rapid acceleration/deceleration, and crosswinds.
Gary Bertollini, Linda Brainer, Jacqueline A. Chestnut, Steven Oja, and Joseph Szczerba (General Motors). "General Motors Driving Simulator and Applications to Human Machine Interface (HMI) Development." SAE paper 2010-01-1037. April 2010. Show summary
This report describes a new driving simulator capability at General Motors (GM) Research and Development's (R&D) Vehicle Development Research (VDR) Laboratory and its application in an iterative HMI development process. The paper also provides an overview of three recent simulator usability tests supporting HMI development.
In recent years, the increased use of electric power steering in vehicles has increased the importance of issues such as making systems more compact and lightweight, and dealing with increased development man-hours.
John Wilkinson, Thomas Klingler (General Motors), and Cedric W. Mousseau (Michelin Tire). "Brake Response Time Measurement for a HIL Vehicle Dynamics Simulator." SAE paper 2010-01-0079. April 2010. Show summary
Vehicle dynamics simulation with Hardware In the Loop (HIL) has been demonstrated to reduce development and validation time for dynamic control systems. For dynamic control systems such as Anti-lock Braking System (ABS) and Electronic Stability Control (ESC), an accurate vehicle dynamics performance simulation system requires the Electronic Brake Control Module (EBCM) coupled with the vehicles brake system hardware. This kind of HIL simulation-specific software tool can further increase efficiency by means of automation and optimization of the development and validation process. This paper presents a method for HIL vehicle dynamics simulator optimization through Brake Response Time (BRT) correlation. The paper discusses the differences between the physical vehicle and the HIL vehicle dynamics simulator. The differences between the physical and virtual systems are used as factors in the development of a Design Of Experiment (DOE) quantifying HIL simulator performance. Finally, the DOE results are used to drive the development of a tool to correlate the HIL system hardware to the physical vehicle BRT. This leads to the development of hardware with improved BRT, and to the design of new HIL simulators with improved brake response.
Yuuki Shiozawa, Masatsugu Yokote, Masaaki Nawano, Hiroshi Mouri (Nissan Motor Co., Ltd.), "Development of a Method for Controlling Unstable Vehicle Behavior." SAE paper 2007-01-0840, April 2007. Show summary
A model-based predictive controller is validated for a lane keeping assistant system using CarSim in a HIL system.
Goossens, P., "Model-based Design, Virtual Prototyping and Automated Testing of Electromechanical Subsystems for Automotive Applications," Opal-RT Technologies, July 2004. Click here for the PDF | Show summary
HIL testing of automotive subsystems using the Opal-RT platform at McGill University.
Presentation made at the 2004 dSPACE user conference showing an early version of CarSim/dSPACE HIL.
Watanabe, Y., Sayers , M.W., "Extending Vehicle Dynamics Software for Analysis, Design, Control, and Real-Time Testing," presented at the The 6th AVEC Symposium, Hiroshima, Japan, Sep 9-13, 2002. Show summary
An overview of CarSim and CarSim RT.
Chen, C. and Peng, H., "Rollover prevention for Sports Utility Vehicles With Human-in-the-Loop Evaluations," 5th Int'l Symposium on Advanced Vehicle Control, August 2000, Ann Arbor, Michigan. Click here for the PDF | Show summary
Rollover is studied using TruckSim for regular simulation and also a driving simulator.
Sayers, M.W., "Vehicle Models for RTS Applications." Vehicle System Dynamics, Vol. 32, No. 4-5, Nov. 1999, pp. 421-438. Show summary
This paper presents the modeling assumptions in CarSim RT.