Connected Vehicle Standoff Resolution via Causality Analysis
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Solution Overview
Problem
Intelligent transportation systems (ITS) face challenges in resolving standoffs between vehicles, particularly in high-volume areas, due to a lack of coordination and overreliance on operators, leading to increased traffic congestion and frustration.
Innovation Solution
A control system that forms a connected vehicle network, using a happens-before relationship analysis to identify the cause of a standoff and generate mitigation plans, including vehicle actions to resolve the standoff, by sharing information and adapting solutions based on prior experiences through a machine learning model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If vehicles use peer-to-peer communication to form a connected vehicle network, then information sharing between vehicles is improved, but the time to generate standoff solutions is increased
Solution Approach 1:
The system pre-establishes communication protocols and data sharing frameworks before standoffs occur. Vehicles continuously exchange basic information (position, speed, trajectory) through the connected vehicle network, so that when a standoff situation arises, the foundational information structure is already in place, eliminating the need to build communication infrastructure from scratch during the critical resolution phase.
Solution Approach 2:
The system dynamically adjusts the level of information sharing and processing based on the standoff situation. During normal operation, vehicles share information at a baseline level. When a standoff is detected, the system intensifies information exchange specifically related to the standoff parameters, focusing computational resources on the critical decision-making data rather than maintaining constant full-spectrum communication.
2Measurement precision
If the control system uses causality relationship analysis with happens-before relationships, then the accuracy of identifying right of way is improved, but the complexity of the system increases
Solution Approach 1:
The system introduces a dedicated analysis module that acts as an intermediary between raw sensor data and decision-making processes. This module specifically handles causality relationship analysis by processing happens-before relationships between events (such as vehicle arrivals, right-of-way signals, and maneuver initiations). By isolating this complex analytical function in a specialized component, the system achieves high precision in right-of-way identification without distributing complexity across the entire vehicle control architecture.
3Productivity
If the control system automatically detects standoffs and generates mitigation plans, then the productivity of resolving standoffs is improved, but the extent of automation increases system complexity
Solution Approach 1:
The automated standoff resolution system is divided into distinct functional modules: detection module (identifies standoff conditions), analysis module (evaluates causality and right-of-way), planning module (generates mitigation strategies), and execution module (implements vehicle maneuvers). Each module handles a specific aspect of the resolution process, allowing the system to achieve high productivity through automated end-to-end processing while managing complexity through functional decomposition and specialized processing at each stage.
Data Source
AI summary
System, methods, and other embodiments described herein relate to resolving a standoff by a vehicle. In one embodiment, a method includes generating a happens-before relationship that explains events between the vehicle and other vehicles before the standoff. The standoff may be a dispute for a right of way between the vehicle and the other vehicles. The method also includes identifying the standoff using a causality relationship analysis according to the happens-before relationship. The method also includes generating a mitigation plan for the standoff that forms standoff solutions in association with the standoff being similar to a prior standoff. The method also includes resolving the standoff by causing vehicle maneuvers associated with the vehicle according to the standoff solutions.