Abstract
This paper describes the design of an optimal-control-based active safety framework that performs trajectory planning, threat assessment, and semi-autonomous control of passenger vehicles in hazard avoidance scenarios. This framework allows for multiple actuation modes, diverse trajectory-planning objectives, and varying levels of autonomy. A model predictive controller iteratively plans a best-case vehicle trajectory through a navigable corridor as a constrained optimal control problem. The framework then uses this trajectory to assess the threat posed to the vehicle and intervenes in proportion to this threat. This approach minimizes controller intervention while ensuring that the vehicle does not depart from a navigable corridor of travel. Simulation and experimental results are presented here to demonstrate the framework’s ability to incorporate configurable intervention laws while sharing control with a human driver.
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Anderson, S.J., Peters, S.C., Pilutti, T.E., Iagnemma, K. (2011). Design and Development of an Optimal-Control-Based Framework for Trajectory Planning, Threat Assessment, and Semi-autonomous Control of Passenger Vehicles in Hazard Avoidance Scenarios. In: Pradalier, C., Siegwart, R., Hirzinger, G. (eds) Robotics Research. Springer Tracts in Advanced Robotics, vol 70. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19457-3_3
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DOI: https://doi.org/10.1007/978-3-642-19457-3_3
Publisher Name: Springer, Berlin, Heidelberg
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