A unified approach to semi-autonomous control of passenger vehicles in hazard avoidance scenarios

Abstract

This paper describes the design of unified active safety framework that combines trajectory planning, threat assessment, and semi-autonomous control of passenger vehicles into a single constrained-optimal-control-based system. This framework allows for multiple actuation modes, diverse trajectory-planning objectives, and varying levels of autonomy. The vehicle navigation problem is formulated as a constrained optimal control problem with constraints bounding a navigable region of the road surface. A model predictive controller iteratively plans the best-case vehicle trajectory through this constrained corridor. 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. Simulated results are presented here to demonstrate the framework's ability to incorporate multiple threat thresholds and configurable intervention laws while sharing control with a human driver.

A Review of Shared Control for Automated Vehicles: Theory and Applications

“…The scientific literature supporting this article was collected from a variety of online databases (e.g., Google Scholar and Web of Science) using various keywords, such as shared control, haptic guidance systems [20], parallel autonomy [21], intelligent copilot [22], cooperative steering assistance system [23], and semiautonomous vehicle control [24]. The first search started in June 2017 and ended in November 2018, with the result that 100 contributions related to the field were found.…”

On responsiveness, safety, and completeness in real-time motion planning

“…Such techniques have been successful in robot navigation (Stachniss and Burgard 2002;Anderson et al 2009); for example the classic dynamic windowing technique introduced for indoor mobile robot navigation is essentially MPC by another name (Stachniss and Burgard 2002). In nonlinear systems, truncated optimal control problems are often solved using numerical optimization or dynamic programming (Mayne et al 2000;Allgöwer and Zheng 2000).…”

“…Some common techniques are to reuse information from previous plans (Bruce and Veloso 2002), to use precomputed coarse global plans to essentially reduce the depth of local minima (Stachniss and Burgard 2002;Anderson et al 2009;Kallmann and Mataric 2004;van den Berg and Overmars 2005), or a combination (Bekris and Kavraki 2007;Zucker et al 2007). These approaches are mostly orthogonal to the choice of time step and can be integrated with the adaptive time stepping approach proposed in this paper.…”

Minimizing driver interference under a probablistic safety constraint in emergency collision avoidance systems

“…A longitudinal collision-mitigation braking strategy was described by Hillenbrand et al (2006) that gradually applies stronger braking as the collision boundary is approached, which smoothes the control output and copes some uncertainty [6]. Anderson et al (2009) present a 2D hazard avoidance scheme based on model predictive control which allows varying levels of autonomy based on risk assessed by control magnitudes [7]. Our approach introduces the additional considerations of uncertainty which provides a more natural definition of risk.…”