Intersection Vehicle Control Using Virtual Traffic Prediction
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Solution Overview
Problem
Current automatic driving technologies face challenges in ensuring safety at intersections without signal lights, as they struggle to handle undetermined traffic situations, leading to potential collisions due to blocked views and unclear road conditions.
Innovation Solution
A vehicle control method that acquires real-time road condition information and vehicle state information, including virtual vehicles to simulate potential obstructions, and uses a motion prediction model to anticipate and avoid collisions when passing through intersections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If automatic driving technology is applied to intersections without signal lights, then driving operation is simplified, but driving safety cannot be guaranteed due to blocked views and undetermined traffic situations
Solution Approach 1:
The system performs preliminary actions by predicting potential vehicle motions before they occur. The prediction model anticipates possible trajectories and behaviors of surrounding vehicles at intersections, allowing the autonomous vehicle to prepare appropriate responses in advance, thereby ensuring safety even when views are blocked
Solution Approach 2:
The system applies preliminary anti-action by proactively identifying potential collision risks and taking preventive measures. The prediction model detects possible harmful motions of other vehicles and the autonomous vehicle responds with counter-actions (such as deceleration or trajectory adjustment) before actual collisions can occur
2Device complexity
If the observation field of view is limited, then the system complexity is reduced, but the ability to detect potential obstacles in blocking areas deteriorates
Solution Approach 1:
The system creates virtual copies of potential vehicles in blocking areas through prediction. Instead of requiring physical sensors to detect every possible obstacle, the system generates virtual vehicle models representing potential threats, allowing it to maintain simple sensor systems while still achieving comprehensive obstacle awareness through predictive simulation
Data Source
AI summary
Disclosed are a vehicle control method, a vehicle control apparatus, and a storage medium. The method includes acquiring real-time road condition information about an ego vehicle. The real-time road condition information can be used to indicate whether the ego vehicle arrives at an intersection. Vehicle state information can be acquired when the ego vehicle arrives at the intersection. Once a prediction result is obtained based on the vehicle state information, the ego vehicle can be controlled according to the prediction result.