Selecting Non-Line of Sight Critical Scenarios for Connected Autonomous Vehicle Testing

The on-board sensors of connected autonomous vehicles (CAVs) are limited by their range and inability to see around corners or blind spots, otherwise known as non-line sight scenarios (NLOS). These have the potential be fatal (critical scenarios) may detect an obstacle much later than amount time needed for car react. In such cases, mechanisms vehicular communication required extend visibility CAV. Despite there being a substantial body work on development navigational algorithms scenarios, is no standard method generating selecting critical NLOS testing these in scenario-based simulation environment. This paper puts forward novel utilising genetic algorithm selection from set all possible particular road need select pertinent number driving generated large them against each other consuming, unnecessary expensive. selected then validated criticality using series MATLAB based simulations.