Lars Svensson

KTH Royal Institute of Technology | KTH · Department of Machine Design (MMK)

In this article, we address the problem of motion planning and control at the limits of handling, under locally varying traction conditions. We propose a novel solution method where traction variations over the prediction horizon are represented by time-varying tire force constraints, derived from a predictive friction estimate. A \CFTOClong (\CFTO...

The road traffic environment is inherently uncertain and unpredictable. An automated vehicle (AV) deployed in such an environment will eventually experience unforeseen critical situations, i.e., situations in which the probability of having an accident is rapidly increased compared to a nominal driving situation. Critical situations can occur for e...

Traction adaptive motion planning and control has potential to improve an an automated vehicle's ability to avoid accident in a critical situation. However, such functionality require an accurate friction estimate for the road ahead of the vehicle that is updated in real time. Current state of the art friction estimation techniques include high acc...

The deployment of autonomous vehicles on public roads calls for the development of methods that are reliably able to mitigate injury severity in case of unavoidable collisions. This study proposes a data-driven motion planning method capable of minimizing injury severity for vehicle occupants in unavoidable collisions. The method is based on establ...

In this paper we address the problem of motion planning and control at the limits of handling, under locally varying traction conditions. We propose a novel solution method where locally varying traction is represented by time-varying tire force constraints. A constrained finite time optimal control problem is solved in a receding horizon fashion,...

An articulated vehicle is a two-body design capable of precise maneuvering around obstacles, while carrying heavy loads over rough terrain. In the context of path planning for automated articulated vehicles, it is desirable to fully utilize the maneuverability of the vehicle to enable autonomous operation in confined areas. In this paper we study t...

The complexity of automated driving poses challenges for providing safety assurance. Focusing on the architecting of an Autonomous Driving Intelligence (ADI), i.e. the computational intelligence, sensors and communication needed for high levels of automated driving, we investigate so called safety supervisors that complement the nominal functionali...

In this paper, we tackle the problem of trajectory planning and control of a vehicle under locally varying traction limitations, in the presence of suddenly appearing obstacles. We employ concepts from adaptive model predictive control for run-time adaptation of tire force constraints that are imposed by local traction conditions. To solve the resu...

As deployment of automated vehicles increases, so does the rate at which they are exposed to critical traffic situations. Such situations, e.g. a late detected pedestrian in the vehicle path, require operation at the handling limits in order to maximize the capacity to avoid an accident. Also, the physical limitations of the vehicle typically vary...

The complexity of automated driving poses chal- lenges for providing safety assurance through cost-efficient solutions. Focusing on the architecting of an Autonomous Driv- ing Intelligence (ADI), i.e. the computational intelligence, sen- sors and communication needed for high levels of automated driving, we investigate so called safety supervisors...

Highly automated road vehicles need the capability of stopping safely in a situation that disrupts continued normal operation, e.g. due to internal system faults. Motion planning for safe stop differs from nominal motion planning, since there is not a specific goal location. Rather, the desired behavior is that the vehicle should reach a stopped st...

Cooperative automated driving is a promising development in reducing energy consumption and emissions, increasing road safety, and improving traffic flow. The Grand Cooperative Driving Challenge (GCDC) 2016 was an implementation oriented project with the aim to accelerate research and development in the field. This paper describes the development o...

Nearly 1.3 million people die each year in traffic-related accidents, whereas an additional 20–50 million people are injured. Introducing autonomous vehicles would aim to reduce these numbers by removing the driver from the loop entirely and thus removing the human error. Intersections are considered a complex traffic situation for autonomous vehic...