Safe Driving Distance and Speed for Collision Avoidance in Connected Vehicles

Area of Science:

• Intelligent Transportation Systems (ITS)
• Internet of Vehicles (IoV)
• Road Safety Engineering

Background:

• Tailgating, or driving too close to the vehicle ahead, is a major cause of road accidents.
• The Assured Clear Distance Ahead (ACDA), or Safe Driving Distance, is crucial for preventing rear-end collisions.
• Connected vehicles and advancements in ITS offer new possibilities for proactive safety measures.

Purpose of the Study:

• To propose an Internet of Vehicles (IoV) based technique for connected vehicles to determine Safe Driving Distance and Speed.
• To enable connected vehicles to avoid forward collisions by calculating and maintaining the Assured Clear Distance Ahead (ACDA).
• To enhance road utilization by dynamically adjusting safe following distances based on real-time parameters.

Main Methods:

• Developed an IoV-based technique to calculate Safe Driving Distance and Safe Driving Speed.
• The method considers two scenarios: vehicles with and without Autonomous Emergency Braking (AEB).
• Calculations incorporate variables like vehicle weight, tire condition, road type, and weather.

Main Results:

• Safe Driving Distance and Speed are significantly influenced by vehicle parameters, road conditions (snowy, wet, icy asphalt), and weather (clear, foggy).
• The proposed technique effectively calculates the ACDA, crucial for collision avoidance.
• The system dynamically enforces minimum safe gaps, optimizing road capacity.

Conclusions:

• The IoV-based technique provides an effective solution for connected vehicles to avoid tailgating and forward collisions.
• Dynamic calculation of Safe Driving Distance and Speed based on multiple parameters enhances road safety.
• This approach maximizes road utilization by intelligently managing vehicle separation.