Make motion control functions even safer

Bosch products enjoy a high reputation when it comes to safety-critical control applications. For example, ABS, ESP, and advanced driver assistance systems help reduce and prevent fatal accidents. To ensure this remains the case in the future, too, we are constantly improving our development methods. This is also important because systems are becoming increasingly complex and their software content is rising.

So the question is: How can we make these sophisticated control functions for vehicle guidance and navigation even safer? We need to develop methods that incorporate and satisfy safety-related system constraints, already during the design phase of the development process. In this blog post, we would like to present two concepts for safe path tracking whose performance we have verified on a modular vehicle platform.

The concepts help us handle safety-critical dynamic systems where system constraints must be satisfied at all times. A descriptive example is motion control in highly automated or autonomous driving. The task is to track a given path provided by a planning layer while staying within the given road boundaries.

In addition to these classical motion control structures, model predictive control (MPC) has become established with great success in recent decades. It is now considered the primary control method for systematically handling system constraints in various applications, including motion control. The basic idea is to formulate a desired motion controller, including all safety constraints, as an optimization problem. Within this problem, the future behavior of the vehicle is predicted over a finite horizon. The starting point is the vehicle state measurement. Based on the prediction, the optimal input sequence is computed, and the first element is applied to the vehicle. In this way, safety can be taken into account at the design stage already. This significantly reduces the testing effort required for release.

In the following, the effectiveness of MPC for motion control is demonstrated on the MockUp vehicle. The MockUp is a research vehicle and a platform for integrating innovative mechatronic systems and vehicle motion control concepts. The electric vehicle serves as a rapid prototyping platform with full control of all actuators. This also includes a newly developed steer-by-wire system and wheel-individual actuation through electric motors.

The second concept we would like to introduce is predictive safety filters. They use the same core algorithms as model predictive control with some modifications. These adaptions allow us to use the safety filters as a modular safety framework for any desired control signal. These signals include potentially unsafe control structures or even human driver inputs such as steering and braking. Unlike traditional control tasks, such as tracking a reference path, these filters have a predictive function – they assess whether desired control inputs may potentially lead to violations of constraint in the future. If there is a safety risk, the safety filter intervenes – it is entitled to modify desired input signals to the minimum extent necessary to ensure safety.