The University of Waterloo (UW) is conducting research into intelligent vehicle systems, seeking to leverage both advanced software algorithms and state-of-the-art sensor and control systems to maximize both system efficiency and safety.
Multiple teams at UW are exploring, in parallel, both advanced driver assistance systems (ADAS) and autonomous vehicle systems. The sensor technologies under test include but are not limited to radar, lidar, cameras, and various forms of RF communication systems. Project test platforms include several full-size production vehicles (MY2015 Lincoln MKZ Hybrids) fully retrofitted for autonomous control development, with additional projects involving vehicles ranging from sedans to sport utility vehicles.
Integrating a variety of sensors into a full vehicle testbed introduces new challenges with respect to testing and validation. To evaluate the vehicle platforms in edge cases that could result in unsafe conditions in the real-world, a controlled environment is needed that can excite sensors in a precise manner, and allow the vehicle to operate as if it was on a real road.
The Green and Intelligent Automotive (GAIA) research facility is one of UW’s most comprehensive vehicle research labs featuring test cells at the battery, powertrain and vehicle levels. The vehicle test cell (VTC) features a two-axle chassis dynamometer, which allows for drive cycle testing of any light-duty automotive platform. We intend to expand the functionality of this system to accommodate driver behaviour studies, as well as ADAS/autonomous vehicle testing. To this end, a visual/haptic feedback simulation system is required that can accurately simulate real-world sensory input, focusing on driver immersion and visual sensor input.
The proposed system will be hereafter referred to as the Driving Simulation System (DSS).
This research is funded in part by the Canada Foundation for Innovation (CFI), Ontario Research Fund Research Infrastructure (ORF-RI), and the University of Waterloo.
