Vehicle Behavior Prediction for Narrow-Road Priority Avoidance
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Solution Overview
Problem
Conventional vehicle control methods struggle to determine the order of priorities for vehicles passing through narrow roads when they cannot exchange information, leading to delayed avoidance actions.
Innovation Solution
A vehicle control method and device that utilize a vehicle-behavior prediction system, including object detection, position estimation, and map acquisition, to determine priorities and initiate avoidance actions based on stop times and road structures, even without information exchange between vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vehicles cannot exchange information, then the system is more reliable in terms of communication failure, but the response time for avoidance action increases
Solution Approach 1:
The system performs preliminary actions by pre-determining priority orders based on road structure information before conflicts occur. When a narrow road is detected, the host vehicle proactively determines the priority order with other vehicles based on map data, eliminating the need for real-time communication during the actual conflict situation.
Solution Approach 2:
The system prepares cushioning measures in advance by setting default priority rules based on road structures. When communication fails, these pre-established priority rules act as a cushion, allowing the host vehicle to immediately execute avoidance actions without waiting for communication or negotiation with other vehicles.
2Ease of operation
If information exchange functions are added to vehicles, then the ability to determine priority order improves, but the device complexity increases
Solution Approach 1:
The system enables self-service by allowing the host vehicle to independently determine priority orders using its own map acquisition device and processing capabilities. Instead of relying on other vehicles to provide information or negotiate, the host vehicle autonomously determines priorities based on pre-acquired road structure data and detected vehicle positions.
Solution Approach 2:
The map acquisition device and road structure data serve as an intermediary that eliminates the need for direct vehicle-to-vehicle communication. By using the road structure map as a mediator, the system can determine priority orders based on objective criteria (such as which vehicle is closer to the narrow road or has right of way according to road rules) without requiring complex communication protocols between vehicles.
3Productivity
If real-time communication between vehicles is implemented, then coordination efficiency improves, but the system becomes more vulnerable to communication failures
Solution Approach 1:
The system performs preliminary coordination by determining priority orders in advance based on road structure information before vehicles actually reach the narrow road. This preliminary determination ensures that when vehicles arrive at the conflict point, the priority order is already established, enabling immediate action without real-time communication.
Solution Approach 2:
Each vehicle independently determines priority orders using its own map data and position information, eliminating dependency on inter-vehicle communication. This self-service approach ensures that coordination can occur even when communication fails, as each vehicle can autonomously determine its priority based on pre-acquired road structure data.
Data Source
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AI summary
A vehicle-behavior prediction device includes: a priority determination section (16) that determines the priority of a host vehicle and a vehicle concerned when the host vehicle and the vehicle concerned pass through a road section; and a vehicle control section (21) that sets the time from when the vehicle concerned stops to when the host vehicle starts action to avoid the vehicle concerned to be shorter in a case where the priority of the host vehicle is low than in a case where the priority of the host vehicle is high.