Dynamic trajectory generation using continuous-curvature algorithms for door to door assistance vehicles

Abstract

In this paper, an algorithm for dynamic path generation in urban environments is presented, taking into account structural and sudden changes in straight and bend segments (e.g. roundabouts and intersections). The results present some improvements in path generation (previously hand plotted) considering parametric equations and continuous-curvature algorithms, which guarantees a comfortable lateral acceleration. This work is focused on smooth and safe path generation using road and obstacle detection information. Finally, some simulation results show a good performance of the algorithm using different ranges of urban curves. The main contribution is an Intelligent Trajectory Generator, which considers infrastructure and vehicle information. This method is recently used in the framework of the project CityMobil2 1 , for urban autonomous guidance of Cybercars.

Urban Motion Planning Framework Based on N-Bézier Curves Considering Comfort and Safety

“…where P is roundabout entrance coordinates, P is roundabout exit coordinates, values of → and → are defined by (6), but the intersection point P is substituted by roundabout points P and P , respectively. In these equations, the upper sign is used when traffic is defined counter clockwise and lower one for clockwise traffic [31].…”

“…Lateral and longitudinal controllers [6][7][8], as well as perception (sensors) [9,10] and communications [11], are some of the topics mostly studied.…”

Intelligent Land Vehicle Model Transfer Trajectory Planning Method Based on Deep Reinforcement Learning

“…There are various ways of trajectory generation in trajectory planning, including Nelson polynomial, spiral curve equation, spline curve, Bezier curve etc [3]. For example, 4 th -order polynomial and dynamic bicycle model are utilized to describe vehicles kinematics model [4], considering the overtaking and chasing behavior of different cost functions in each case.…”

“…[6] proposes a trajectory planning based on Bezier Curve that takes the command of 3 After that, the new samples are adopted to modify the strategy  for several times. After a great deal of iterative learning, the agent finally learns the optimal strategy *  to complete the corresponding task.…”

Curve Path Detection in Autonomous Vehicle using Deep Learning

“…Radar reflectors system was used in the lane boundaries to detect the lane and the vehicle automation by Alexey Voronov, johan Hulte n, Johan Wedlin, CristoferEnglund, Viktoria Swedish [11]. An automatically intelligent trajectory generator was developed and used for the lane and curve path detection by Joshue Perez Rastelli and ray Lattarulo and Fawzi Nashashibi [12]. An Predictive virtual lane algorithm was developed to mark the lane boundaries using the vision by Young Seop, Wonhee Kim, Seung-Hi Lee, and Chung Choo Chung [13].…”