Autonomous Vehicle Routing With Depart Constraints
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating dynamic environments due to outdated map data and lack of real-time information about events and conditions affecting travel routes, leading to inefficiencies and safety concerns.
Innovation Solution
A system that uses dynamic constraint data, including depart constraints, to manage navigation by defining permissible and exclusion areas based on geographic identifiers and application types, allowing autonomous vehicles to adjust routes in real-time and avoid hazardous conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If map data is used for navigation, then autonomous vehicles can determine travel routes, but the map data is outdated and does not reflect changing availability of travel ways
Solution Approach 1:
The system transitions from static map data to dynamic constraint data that updates in real-time. Constraint data includes geographic identifiers and application types that change based on current conditions such as road closures, construction, and events, allowing the navigation system to reflect the most current state of travel ways without requiring continuous map updates.
Solution Approach 2:
The system pre-defines constraint data with geographic identifiers and application types for various conditions (road closures, construction zones, events) before they occur or as they are reported. This allows the navigation system to quickly apply appropriate constraints when conditions change, rather than waiting for map data to be updated.
2Reliability
If traditional routing constraints are applied, then vehicles avoid exclusion areas, but vehicles may become stranded if already inside the excluded area when constraints are imposed
Solution Approach 1:
The depart constraint applies different rules to different situations: vehicles outside the geographic area cannot enter, but vehicles already inside the area when the constraint is imposed are permitted to exit. This local differentiation resolves the contradiction by applying strict avoidance to new routes while providing flexibility for vehicles already in the area.
Solution Approach 2:
The system changes the parameter of constraint application from binary (always forbid) to conditional (forbid with exception). The depart constraint modifies the default forbid behavior by adding a time-based condition: if the vehicle is inside the area when the constraint is imposed, the constraint allows exit rather than forcing immediate termination or rerouting.
3Adaptability or versatility
If real-time constraint data is implemented, then vehicles can dynamically adjust routes, but the system complexity increases
Solution Approach 1:
The constraint data is segmented into discrete geographic identifiers (polygons, circles, rectangles) with associated application types. This segmentation allows the system to process constraints as individual, manageable units rather than continuous complex data, reducing computational burden while maintaining real-time capability.
Solution Approach 2:
The constraint data structure with geographic identifiers and application types serves multiple functions: it defines exclusion areas, specifies depart constraints, provides real-time updates, and works across different navigation scenarios. This universal structure reduces overall system complexity by using a single data format for multiple purposes.
Data Source
AI summary
A method of controlling navigation of autonomous vehicles includes accessing map data descriptive of the identity and location of different travel ways within a surrounding environment of an autonomous vehicle and accessing constraint data descriptive of one or more geographic areas or geographic identifiers, within the map data, for which associated navigational constraints are defined. The constraint data includes a depart constraint that specifies an area that an autonomous vehicle may not enter but may exit if inside the area when the depart constraint is imposed, thereby preventing the autonomous vehicle from being trapped in a forbidden area even though the autonomous vehicle may safely complete its route. A travel route is determined for the autonomous vehicle based at least in part on the map data evaluated relative to the constraint data including the depart constraint, and motion of the autonomous vehicle is controlled based on the determined travel route.