Autonomous Vehicle Route Conformance Scoring for Dispatch Efficiency
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Solution Overview
Problem
The performance of autonomous vehicles varies across different environments, and existing systems lack effective methods to assess and optimize route assignments based on vehicle capabilities, leading to inefficiencies and potential misallocation of services.
Innovation Solution
A system that assesses autonomous vehicle capabilities by monitoring their performance on assigned routes, using a navigator/routing engine to generate routes based on constraint data, vehicle capability data, and operational constraints, and scoring their adherence to these routes to optimize service allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous vehicles are assigned routes without assessing their capabilities, then service allocation is simplified, but route adherence and performance efficiency deteriorate
Solution Approach 1:
The system performs preliminary assessment of autonomous vehicle capabilities before assigning routes. The arranger evaluates vehicle performance metrics, capability data, and operational constraints in advance to determine suitable route assignments, ensuring vehicles are pre-matched to routes they can successfully complete
Solution Approach 2:
The system implements continuous feedback loops where route adherence data and vehicle performance metrics are monitored during route execution. This feedback is used to update vehicle capability profiles and improve future route assignments, creating a self-optimizing system that enhances both productivity and reliability over time
2Reliability
If autonomous vehicles are monitored continuously for route adherence, then route conformance is improved, but system complexity and computational resources increase
Solution Approach 1:
The monitoring function is extracted from the autonomous vehicles and centralized in the arranger system. Instead of each vehicle having complex onboard monitoring capabilities, the arranger remotely tracks vehicle positions and compares them against assigned routes, simplifying the vehicle systems while maintaining comprehensive monitoring
Solution Approach 2:
The system uses an intermediary arrangement system that acts as a mediator between route planning and vehicle execution. The arranger receives vehicle position data, processes it against route constraints, and generates compliance assessments without requiring direct complex interactions between vehicles and monitoring infrastructure
3Productivity
If route assignments are optimized based on vehicle capabilities, then overall network efficiency is improved, but data processing requirements and computational load increase
Solution Approach 1:
The system applies local quality optimization by tailoring route assignments to specific vehicle capabilities rather than using uniform assignment rules. Each vehicle receives customized route recommendations based on its unique performance characteristics, creating locally optimized solutions that aggregate to global efficiency improvements
Solution Approach 2:
The arranger dynamically adjusts assignment parameters based on vehicle capability data, operational constraints, and performance metrics. By changing the parameters used in route evaluation (such as speed capabilities, payload limits, or geographic restrictions), the system optimizes network efficiency without requiring complete reprocessing of all route data
Data Source
AI summary
Autonomous vehicles are requested to execute a route from an origin location to a destination location. The route specifies one or more waypoints between the origin location and the destination location, with the autonomous vehicle requested to transit from the origin location to the destination location via the waypoints. Some autonomous vehicles vary their route and do not necessarily visit each of the specified waypoints along the route. To improve adherence to the waypoints specified in the route, an arranger assigns a weight to each of the waypoints. The weight is used to score the vehicle's performance of the route based at least in part on whether the vehicle visited each of the waypoints and the weight associated with each of the waypoints. The score is used to control dispatch of additional service requests to the autonomous vehicle or other autonomous vehicles operated by the same operator or manufacturer.