Fig 1.
Collision avoidance scenarios addressed extensively in literature.
(a) Rear end collision avoidance, (b) Cooperative collision avoidance in Adaptive Cruise Control or Platooning, (c) Lane departure or Lateral collision avoidance, (d) Flock like topology (A typical scenario in congested urban road).
Fig 2.
AVs installed with proposed social agents interacting socially with each other.
Fig 3.
Main simulation screen of Richardson’s arms race model inspired agent-based collision detection and avoidance scheme.
Table 1.
Simulation parameters and their designated ranges.
Table 2.
Test cases along the parameters and their corresponding values.
Table 3.
Test cases to find optimal safety distances and sonar ranges.
Fig 4.
Graphical representation of test case 1.
Fig 5.
Graphical representation of test case 2.
Fig 6.
Graphical representation of test case 3.
Fig 7.
Graphical representation of test case 4.
Fig 8.
Graphical representation of test case 5.
Fig 9.
Graphical representation of test case 6.
Fig 10.
Infield experiment using flock like topology.
Fig 11.
Results of in field experiments in terms of time taken by the social agent for the collision avoidance in the flock like topology.
Table 4.
Results of prototype experiments in terms of the time taken by the IEEE 802.11n based mirror neuron inspired intention awareness and cooperative perception approach [32] for the collision avoidance in the flock like topology.