Intersection Speed Model Generation for Autonomous Vehicles
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Solution Overview
Problem
In automatic driving scenarios, predicting the behavior of other vehicles at intersections is challenging due to complex speed changes, making it difficult for vehicles to accurately anticipate the movements of surrounding vehicles.
Innovation Solution
An information processing apparatus with a travel information acquisition unit, intersection information acquisition unit, route specification unit, control point detection unit, and model generation unit that predicts the speed of a moving object at an intersection by specifying a reference route and detecting speed control points to generate a speed model that minimizes speed changes, allowing for accurate speed prediction and trajectory calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the vehicle attempts to predict other vehicles' behavior at intersections using conventional methods, then the prediction capability is limited, but the system complexity remains low
Solution Approach 1:
The patent segments the intersection prediction problem into distinct components: detecting speed control points, generating speed models for different vehicle types, and calculating trajectories. This segmentation allows the system to handle complex predictions through modular, manageable sub-tasks, improving prediction accuracy without overwhelming system complexity
Solution Approach 2:
The system changes parameters by generating different speed models for different vehicle types (e.g., vehicles with different acceleration patterns, sizes, or destinations). By adjusting speed model parameters based on vehicle classification and detected control points, the system achieves higher prediction accuracy while maintaining a structured approach to complexity
2Loss of energy
If the vehicle reduces speed at intersections to match traffic flow, then fuel efficiency improves, but travel time increases
Solution Approach 1:
The system performs preliminary actions by detecting speed control points and generating speed models in advance before the vehicle reaches the intersection. This allows the vehicle to optimize its speed profile proactively, reducing speed smoothly at appropriate points to match traffic flow and improve fuel efficiency while minimizing unnecessary delays
Solution Approach 2:
The system applies dynamics by generating dynamic speed patterns that alternate between acceleration and inertia travel sections. The vehicle adjusts its speed dynamically based on predicted trajectories and detected control points, allowing it to cooperate with traffic flow for fuel efficiency while maintaining optimal travel time through adaptive speed control
Data Source
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AI summary
According to an arrangement, an information processing apparatus (10) includes a travel information acquisition unit (42), an intersection information acquisition unit (44), a route specification unit (48), a control point detection unit (50), and a model generation unit (52). The travel information acquisition unit (42) acquires a dynamic state related to traveling of a moving object entering an intersection. The intersection information acquisition unit (44) acquires intersection information indicating a configuration of the intersection. The route specification unit (48) specifies a reference route along which the moving object is predicted to travel at the intersection, based on the dynamic state and the intersection information. The control point detection unit (50) detects a speed control point included in the specified reference route. The model generation unit (52) generates a speed model representing a temporal change in a predicted speed of the moving object so that the speed at the speed control point is locally minimized, based on the dynamic state and the intersection information.