Standardized Longitudinal Reference Model for Vehicle Motion Control

Automated driving systems are becoming more prevalent in the heavy vehicle transportation industry. Increased automation is presumed to have positive effects on the industry's safety, productivity, and environmental impact. One essential part of increased automation is the development of high-level functionalities such as motion planning and control algorithms. This thesis proposes a new system structure for automated driving system implementations, using a simplified vehicle model with physically motivated constraints, referred to as a reference model, to give a promised behavior on future states of the vehicle. In the proposed system, there exists a high-level controller which utilizes the reference model to calculate a reference signal which corresponds to a realizable behavior. A low-level controller with better knowledge of the plant dynamics and direct access to the plant actuators is then used to realize the reference signal for the specific vehicle it is implemented in. In this thesis, the reference signal is chosen as the longitudinal acceleration of the vehicle. There are several advantages to such a system, the main one being the ability to re-use high-level functionalities between different vehicle types due to the usage of a standardized interface. This could decrease development time, as it would be possible to develop the high and low-level functionalities separately, and therefore work on both can be conducted simultaneously. These can later be merged in the implemented system. The work concerns the modeling of the longitudinal dynamics of vehicles. Models of varying complexities, in terms of available actuators are presented and evaluated to show the system's usability in the presence of parametric uncertainties as well as modeling errors. Model predictive control allocation is used and motivated for choosing which actuators to use for realizing a given reference signal. Model predictive control is also utilized as an application of the reference model where a velocity-following case is investigated. Static and dynamic constraints on longitudinal acceleration are derived for a general vehicle, and system identification of vehicle actuators' aggregate dynamics is discussed and implemented.