Analyzing the Collision Probability of Autonomous Vehicle at Crossroad

It is essential to assess the autonomous vehicle operation safety during driving, which can avoid or reduce the collision risk by evaluating the drive safety. In this paper, a collision risk assessment algorithm is proposed, that is quantifies the auto-drive vehicle collision risk by the Time to Collision (TTC) frequency. Firstly, the Long Short Time Memory network (LSTM) is used to predict the surrounding vehicle trajectory; Moreover, the collision point between the auto-drive vehicle and the surrounding vehicle is determined, and the frequency distribution result of TTC is calculated by the Monte Carlo simulation method; Finally, the running speed & hazard probability is obtained by changing the running speed of auto-drive vehicle, and the running speed & safety probability is obtained further. It can be seen from the result that the proposed method can provide an effective evidence for decision-making layer of auto-drive vehicle, improve the running safety of vehicle, and reduce the operation risk of auto-drive vehicle.

• Publication year

  2020

• Venue

  2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS)

• Publication date

  2020-11-20

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.1109/DDCLS49620.2020.9275190
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Trajectory Planning and Safety Assessment of Autonomous Vehicles Based on Motion Prediction and Model Predictive Control

  2019cited by this paper
• Collision Risk Assessment Algorithm via Lane-Based Probabilistic Motion Prediction of Surrounding Vehicles

  2018cited by this paper
• Collision Risk Evaluation and Collision-Free Path Planning of Autonomous Surface Vehicles Considering the Uncertainty of Trajectory Prediction

  2018cited by this paper
• Vehicle collision risk estimation based on RGB-D camera for urban road

  2017cited by this paper
• Colouring vehicle threat and minimising threat avoidance trajectory cost for adaptive vehicle collision defence system in active safe driving

  2017cited by this paper
• Fast and Bounded Probabilistic Collision Detection in Dynamic Environments for High-DOF Trajectory Planning

  2016cited by this paper
• Real-time prediction of rear-end crashes near freeway recurrent bottlenecks

  2013cited by this paper
• Evaluation of the impacts of traffic states on crash risks on freeways.

  2012cited by this paper
• Model-Based Probabilistic Collision Detection in Autonomous Driving

  2009cited by this paper
• Real time trajectory prediction for collision risk estimation between vehicles

  2009cited by this paper
• Error Analysis and Performance Evaluation of a Future-Trajectory-Based Cooperative Collision Warning System

  2009cited by this paper
• Estimating Acceleration and Lane-Changing Dynamics Based on NGSIM Trajectory Data

  2007cited by this paper
• Analysis of traffic injury severity: an application of non-parametric classification tree techniques.

  2006cited by this paper
• Real-time hazardous traffic condition warning system: framework and evaluation

  2005cited by this paper
• An integrated collision prediction and avoidance scheme for mobile robots in non-stationary environments

  1992cited by this paper

• Driving Safety Risk Analysis and Assessment in a Mixed Driving Environment of Connected and Non-Connected Vehicles: A Systematic Survey

  2025cites this paper
• Recent Advances in Interactive Driving of Autonomous Vehicles: Comprehensive Review of Approaches

  2025cites this paper