Road Segment Traffic Control Using Targeted Vehicle Intervention
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Solution Overview
Problem
Existing systems fail to accurately predict and manage traffic conditions on road segments and geographical regions, particularly in urban areas, leading to frequent traffic congestion and obstructions.
Innovation Solution
A system and method using a finite discrete-time Markov chain model to analyze vehicle data, such as velocity and position, to predict future traffic states and communicate intervention instructions to vehicles equipped with ADS features, adjusting their behavior to optimize traffic flow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traffic conditions are monitored and predicted for all vehicles in a geographical region, then traffic state prediction accuracy is improved, but system complexity and computational resources required increase significantly
Solution Approach 1:
The system segments the plurality of vehicles into different subsets based on their contribution to traffic congestion. Instead of monitoring all vehicles uniformly, only vehicles identified as congestion-causing are selected for detailed monitoring and intervention. This segmentation allows the system to maintain prediction accuracy for critical traffic states while reducing the overall system complexity and computational burden.
Solution Approach 2:
The system applies partial action by focusing computational resources on a subset of vehicles that have the most significant impact on traffic congestion. Rather than attempting to control or monitor all vehicles equally, the system identifies and targets specific vehicles whose behavior changes would have the greatest positive effect on traffic flow, thereby achieving effective traffic state prediction and control with reduced system complexity.
2Productivity
If intervention instructions are communicated to all vehicles, then traffic flow optimization is improved, but communication overhead and implementation complexity increase
Solution Approach 1:
The system segments the vehicle population and identifies only those vehicles within specific subsets that require intervention instructions. By determining which vehicles are actually contributing to congestion and would benefit from behavior changes, the system communicates with a limited number of vehicles rather than all vehicles in the region. This reduces communication overhead and simplifies implementation while maintaining traffic flow optimization effectiveness.
3Productivity
If vehicle behavior is adjusted based on comprehensive traffic analysis, then congestion alleviation is improved, but response time and computational processing increase
Solution Approach 1:
The system performs preliminary identification and classification of vehicles into subsets based on their congestion-causing potential before traffic conditions deteriorate. By pre-segmenting vehicles and preparing intervention strategies for identified congestion-causing vehicles, the system can implement behavior adjustments more rapidly when congestion occurs, reducing the overall response time while maintaining effective congestion alleviation.
Data Source
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AI summary
The present disclosure relates to a method, system, a computer-readable storage medium and a computer program product. There is provided a method for controlling a future traffic state on road segments based on a current traffic state in a geographical region by obtaining vehicle data from at least one subset of vehicles among a plurality of vehicles in the current traffic state, determining, based on the obtained vehicle data, the future traffic state on the one or more road segment(s), determining a plurality of alternative future traffic states based on a plurality of predetermined vehicle behavior criteria configured to influence the determined future traffic state, selecting a predetermined vehicle behavior resulting in an augmented future traffic state being representative of a most desired future traffic state, and communicating the selected predetermined vehicle behavior to one or more vehicle(s) comprised in the subset of vehicles.