Automatic Driving Route Control for Unachievable Rerouting
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Solution Overview
Problem
Existing automatic drive assist systems face challenges in smoothly transitioning between routes during rerouting requests, leading to driver discomfort when route changes are not achievable in time, often requiring a switch to drive assist mode.
Innovation Solution
The system includes an automatic drive controller that determines the achievability of route changes by comparing candidate routes with the current route, allowing the vehicle to continue on the original route if a change is not feasible, thereby preventing mode switches and maintaining driver comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system automatically switches to drive assist mode when route change is not achievable, then the system maintains operational safety, but driver comfort deteriorates due to frequent mode switching
Solution Approach 1:
The system dynamically adjusts the automatic driving control based on the achievability determination. When route change is achievable, it transitions to the new route; when not achievable, it maintains the current route. This dynamic adaptation eliminates unnecessary mode switching while preserving safety, as the system continuously evaluates route change feasibility and adjusts its behavior accordingly.
Solution Approach 2:
The system changes the control parameter from binary mode switching (automatic drive assist vs. drive assist) to a continuous parameter (route change achievability determination). By introducing the course-change achievability determiner that evaluates geometric and temporal feasibility, the system transitions from a discrete state change to a continuous assessment, allowing smooth route transitions without abrupt mode changes.
2Measurement precision
If the system enforces route change when rerouting is requested, then routing accuracy improves, but driving stability deteriorates due to abrupt route changes
Solution Approach 1:
The system performs preliminary evaluation of route change achievability before executing the route change. The course-change achievability determiner assesses whether the route change can be achieved within available distance and time constraints before the actual transition. This preliminary action ensures that only feasible route changes are executed, maintaining both routing accuracy and driving stability by preventing abrupt or impossible maneuvers.
Solution Approach 2:
The system implements feedback through the course comparator that continuously compares the candidate route with the current route in terms of direction and geometric constraints. This feedback mechanism provides real-time information about route change feasibility, allowing the system to adjust its routing decisions based on actual driving conditions, thereby maintaining stability while achieving accurate routing.
3Adaptability or versatility
If the system calculates multiple candidate routes, then routing versatility improves, but computational complexity increases
Solution Approach 1:
The system extracts only the necessary candidate routes for evaluation rather than processing all possible routes. The traveling route setter generates multiple candidate routes, but the course comparator focuses evaluation on specific critical aspects (direction at diverging courses, geometric constraints). This extraction approach maintains routing versatility by considering multiple options while reducing computational complexity by focusing only on relevant evaluation criteria.
Solution Approach 2:
The system performs partial evaluation of candidate routes by focusing on key decision points (diverging courses) rather than analyzing every segment of every candidate route. The course comparator evaluates routes based on critical geometric parameters at divergence points rather than comprehensive analysis of entire routes. This partial action approach provides sufficient routing versatility while significantly reducing computational burden.
Data Source
AI summary
An automatic drive assist apparatus includes a storage, an own-vehicle position estimator, a route-information input device, a traveling route setter, and an automatic drive controller including a rerouting request determiner, a course comparator, and a course-change achievability determiner. The automatic drive controller causes an own vehicle automatically traveling along a traveling route determined by the traveling route setter. When the rerouting request determiner determines that a new traveling route is reconstructed in response to a rerouting request, the course comparator reads a candidate route of the new traveling route, compares the candidate route with the traveling route determined before the reconstruction, and determines whether a route change is set. When the route change is determined not to be achievable by the course-change achievability determiner, the automatic drive controller causes the own vehicle to keep automatically driving along the traveling route determined before the reconstruction.