The aim of the paper is to propose collision-free path planning algorithm for autonomous parallel parking based on Ackermann steering geometry. A geometrical path planning algorithm has been employed for generating a path that is based on two straight lines and two identical circles. The algorithm is taking into account that the left side of the street is taken as another parking slot occupied by full of cars. The ego’s kinematics model appropriate for the low-velocity parking scenario and the maximum allowable steering angle for the narrow streets is used in the path planning stage by considering mechanical and environmental limits. According to the steering angle, required length of the parking space is obtained. The algorithm can adapt itself according to the lateral position of the ego in case it is parallel to other parked cars. The steering angle to be used and the required parking space length according to the lateral position of the vehicle in the environmental model are given with graphics.

In this paper, a path planning method is introduced to perform the autonomous perpendicular parking of a four-wheel steered vehicle. The method consists of the kinematic model of the vehicle and geometrical equations. Mentioned method is based on retrieving the vehicle from the parking spot and using the same path inversely to park the vehicle. MATLAB simulations are performed with different kinematic properties and positions. Three new equations are derived to calculate the longitudinal maneuver to locate the vehicle at ready to reverse position, the maximum approach to left side of the road during the parking maneuver, and the minimum distance between the right side of the vehicle and edge of the parking space. A methodology is introduced to define the required driving corridor by using these equations and it is shown by simulation that feasibility of the planned autonomous perpendicular parking maneuver can be evaluated by taking environmental telemetry and kinematics of the vehicle into account.

Heavy-vehicle Anti-lock Braking System (ABS) controllers are commonly tested using simulations before vehicle testing, but pneumatic actuation and measurement limitations can affect the results in the field. This paper presents the complete design process of a pneumatic ABS controller. System identification tests, estimation experiments, and reverse engineering methods were used to develop the models used for testing, including a vehicle model, pneumatic circuit model, etc. Model-in-the-loop (MIL) and software-in-the-loop (SIL) simulations were used to test and validate the algorithm in the simulation environment. Hardware-in-the-loop (HIL) simulations were also used to test and tune the ABS algorithm using a physical pneumatic circuit before real vehicle testing. Lastly, the ABS controller was deployed to a custom ECU and tested on the real vehicle on dry and wet asphalt. The developed controller prevented sustained wheel lock and produced repeatable deceleration and stopping-distance results during dry- and wet-asphalt testing. Qualitative assessment by the test driver and engineering team also indicated ABS intervention and modulation characteristics broadly consistent with commercial alternatives.