Lateral Control Of Autonomous Vehicles Research Articles

Lateral Control of Autonomous Vehicles Using Multi-Model and Fuzzy Approaches

This paper discusses the fundamental issues in vehicle lateral motion control within Automated Highway Systems. Lane keeping control and lane changing control are concerned. One major challenge for lateral controller design is the smoothness and robustness under different vehicle conditions. A multi-model fuzzy controller, which includes four local controllers, is then proposed for both the operations of lane keeping and lane changing. These four local controllers are set up for four vehicle speed regions respectively. A fusion block is then introduced to ensure smooth and accurate transition between the different local controllers. The proposed controller inherits the advantages of both the multi-model control and fuzzy control. Simulations show that it could get good performances in the whole range of operation speed, and could also repel the system uncertainties such as changes in vehicle load, movement inertia and wheel cornering stiffness. Furthermore, the calculation procedure of the proposed controller is not complex, and is rather rapid. It appears a promising control algorithm for realtime embedded applications.

A Study on Lateral Control of Autonomous Vehicles via Fired Fuzzy Rules Chromosome Encoding Scheme

In this paper, we propose a novel Fired Rules Chromosomes (FRC) encoding scheme for a fuzzy controller tuned by Genetic Algorithms (GA). The proposed method improves the optimization speed through the reduction of the search space. In addition, an improvement in convergence is demonstrated. The fuzzy controller optimized by the FRC scheme is employed to maintain the lateral position of an autonomous vehicle. The robustness of the controller to parameter variation is studied by Monte-Carlo analysis. Simulation and experimental studies demonstrate the performance of the lateral controller.

Lateral control of autonomous vehicle by yaw rate feedback

In an autonomous vehicle, the reference lane is continually detected by a machine vision system. Then the vehicle is steered to follow the reference yaw rates which are generated by the deviations of lateral distance and the yaw angle between the vehicle and the reference lane. To cope with the steering delay and the side-slip of a vehicle, a PI controller is introduced for the yaw rate feedback. It is tuned by the simulation that the vehicle is modeled as 2 DOF and 79 DOF and verified by the results of the actual vehicle test. The lateral control algorithm by the yaw rate feedback has good performance of lane tracking and passenger comfort.

The design of a look-down feedback adaptive controller for the lateral control of front-wheel-steering autonomous highway vehicles

An adaptive control law and a distance rate observer were developed for the lateral control of autonomous vehicles. The control law and the observer were implemented on a passenger vehicle. The test results show that both tight lateral tracking control and smooth steering can be achieved without feed forward information. The developed control law is shown to be very robust to changes in the most critical vehicle control parameters.

Vehicle Control Issues in Intelligent Vehicle Highway Systems

This paper gives an overview of vehicle control issues associated with Intelligent Vehicle Highway Systems (IVHS), in particular it treats the technology required for autonomous control of vehicles in an Automated Highway System (AHS). This is not a true survey paper in that research results of the California PATH program are presented, whereas ongoing work in Europe (Prometheus) and Asia is not treated. The primary issues dealt with in this paper concern the longitudinal and lateral control of autonomous vehicles.