Obstacle Avoidance of Bicycle Vehicle Model using Overwhelming Controller

• Published in: Arabian journal for science and engineering (2011) Vol. 43; no. 9; pp. 4821 - 4833
• Main Authors: Singh, R., Bera, T. K.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-09-2018; Springer Nature B.V
• Subjects: Accidents; Algorithms; Autonomous cars; Bicycles; Computer simulation; Driving; Dynamic models; Engineering; Fuel economy standards; Humanities and Social Sciences; Matlab; multidisciplinary; Obstacle avoidance; Research Article - Mechanical Engineering; Science; Tracking; Trajectories; Vehicle emissions; Inverse controller; Overwhelming controller; Obstacle avoidance algorithm; Trajectory tracking; Bond graph; Bicycle vehicle model
• ISSN: 2193-567X; 1319-8025; 2191-4281
• DOI: 10.1007/s13369-018-3175-5

The major reasons of the road accidents are the traffic problem and human erroneous driving. The researchers have started developing self-driving cars to avoid such accidents. In this paper, bicycle vehicle model along with its inverse vehicle dynamic model have been developed to track the predefined path and replace the driver. A bicycle vehicle model using bond graph (BG) is created to avoid single and two obstacles of known different geometry in predefined path. The obstacle avoidance algorithm is developed in the
Matlab
environment and this consists of combination of line following, tangent bug and wall following algorithm. The trajectory data from the obstacle avoidance controller is fed to the inverse controller of bicycle vehicle model to run the forward model of bicycle vehicle. For the trajectory tracking of bicycle vehicle model, the system inversion is carried out through the bond graph-based overwhelming controller. The simulation results for trajectory tracking of bicycle model is presented for single and two static obstacles with different orientations and shapes, and finally, conclusions are presented to show that response of the forward model follows the command (actual path decided by the obstacle avoidance controller) within the acceptable limits. All the results and simulations are obtained using
Matlab
and
SymbolsShakti
®
software (Bond graph software).