Vehicle Deceleration Control for Path-Relevant Obstacle Avoidance
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Solution Overview
Problem
Current vehicle control strategies often lead to unnecessary emergency braking due to considering all obstacles within the perception range, including those on other lanes or static obstacles, which reduces safety and passenger experience.
Innovation Solution
A vehicle traveling control method that determines predicted motion features of objects within the perception visual field, assesses their safety level based on these features and preset conditions, and adjusts deceleration accordingly to avoid unnecessary braking, focusing on dynamic obstacles that pose a threat to the vehicle's path.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle considers all obstacles within the perception range for control decisions, then the obstacle detection coverage is improved, but unnecessary emergency braking occurs due to including static obstacles and obstacles on other lanes
Solution Approach 1:
The patent segments obstacles into different categories (dynamic obstacles on the same lane, dynamic obstacles on other lanes, static obstacles) and applies different control strategies to each category. The processing module selectively processes only dynamic obstacles on the same lane for emergency braking decisions, while excluding other obstacle types, thereby resolving the contradiction between comprehensive detection and avoiding unnecessary braking.
Solution Approach 2:
The patent applies partial action by not processing all detected obstacles uniformly. Instead, it selectively processes only the subset of obstacles (dynamic obstacles on the same lane) that require emergency braking responses, while ignoring other obstacle types. This partial processing approach prevents unnecessary emergency braking while maintaining adequate safety coverage.
2Reliability
If the vehicle processes all detected obstacles for emergency braking, then the safety response is improved, but the control flexibility is reduced due to uniform treatment of all obstacles
Solution Approach 1:
The patent applies local quality by assigning different processing qualities to different obstacle types. Dynamic obstacles on the same lane receive high-priority processing with emergency braking responses, while dynamic obstacles on other lanes and static obstacles receive lower-priority or no processing. This differentiated local quality approach maintains safety responses for critical obstacles while providing control flexibility for non-critical situations.
Solution Approach 2:
The patent introduces dynamic processing based on obstacle characteristics and vehicle state. The determination module dynamically decides whether to process each obstacle based on real-time conditions such as obstacle type, vehicle speed, and lane position. This dynamic approach allows the system to adapt its control flexibility according to the specific situation while maintaining safety responses when necessary.
3Reliability
If the vehicle applies maximum deceleration for all obstacles, then the collision avoidance is improved, but the passenger experience deteriorates due to frequent unnecessary braking
Solution Approach 1:
The patent segments the deceleration control into different levels based on obstacle type. Maximum deceleration is applied only to dynamic obstacles on the same lane that pose immediate collision risks, while no deceleration or reduced deceleration is applied to other obstacle types. This segmentation prevents unnecessary braking events that would degrade passenger experience while maintaining collision avoidance for critical obstacles.
Solution Approach 2:
The patent converts the potential harm of comprehensive obstacle processing into benefit by using the detected obstacle information selectively. The system benefits from comprehensive detection capability but converts the potential harm of unnecessary braking into benefit by filtering out non-critical obstacles from the control decision process, thereby improving passenger experience while maintaining collision avoidance effectiveness.
Data Source
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AI summary
The disclosure relates to the technical field of vehicle engineering, in particular to a vehicle traveling control method, an electronic device, a storage medium, a chip and a vehicle. The vehicle traveling control method includes: determining (S11) predicted motion features of a to-be-avoided object within a perception visual field of a vehicle; determining (S12) a safety level of the to-be-avoided object relative to the vehicle according to the predicted motion features and preset safety conditions; and determining (S13) a target deceleration of the vehicle according to an attribute feature of the to-be-avoided object and the corresponding safety level, and controlling traveling of the vehicle according to the target deceleration.