Title :
Overtaking maneuvers by non linear time scaling over reduced set of learned motion primitives
Author :
Duggal, Vishakh ; Bipin, Kumar ; Singh, Arun Kumar ; Gopalakrishnan, Bharath ; Bharti, Brijendra Kumar ; Khiat, Abdelaziz ; Krishna, K. Madhava
Author_Institution :
Robot. Res. Lab., IIIT Hyderabad, Hyderabad, India
fDate :
June 28 2015-July 1 2015
Abstract :
Overtaking of a vehicle moving on structured roads is one of the most frequent driving behavior. In this work, we have described a Real Time Control System based framework for overtaking maneuver of autonomous vehicles. Proposed framework incorporates Intelligent Planning and Modular control modules. Intelligent Planning module of the framework enables the vehicle to intelligently select the most appropriate behavioral characteristics given the perceived operating environment. Subsequently, Modular control module reduces the search space of overtaking trajectories through an SVM based learning approach. These trajectories are then examined for possible future time collision using Velocity Obstacle. It employs non linear time scaling that provides for continuous trajectories in the space of linear and angular velocities to achieve continuous curvature overtaking maneuvers respecting velocity and acceleration bounds. Further time scaling also can scale velocities to avoid collisions and can compute a time optimal trajectory for the learned behavior. The preliminary results show the appropriateness of our proposed framework in virtual urban environment.
Keywords :
acceleration control; angular velocity control; collision avoidance; intelligent transportation systems; learning (artificial intelligence); mobile robots; motion control; nonlinear control systems; road accidents; road safety; road traffic control; road vehicles; support vector machines; time optimal control; trajectory control; SVM based learning approach; acceleration bounds; angular velocities; autonomous vehicles; behavioral characteristics; collision avoidance; continuous curvature overtaking maneuvers; continuous trajectories; driving behavior; future time collision; intelligent planning; learned motion primitives; linear velocities; modular control modules; nonlinear time scaling; overtaking trajectories; real time control system; reduced set; search space; structured roads; time optimal trajectory; velocity bounds; velocity obstacle; virtual urban environment; Acceleration; Automata; Mobile robots; Real-time systems; Roads; Trajectory; Vehicles;
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2015 IEEE
Conference_Location :
Seoul
DOI :
10.1109/IVS.2015.7225672