Traffic Decongestion via Real-Time Bidding and Dynamic Allocation
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Solution Overview
Problem
Current traffic management systems fail to efficiently allocate traffic rights based on real-time dynamics, leading to congestion and inefficient road usage, lacking a mechanism for users to actively influence their travel times and costs.
Innovation Solution
A system and method that utilizes real-time bidding, integrating navigation systems, communication devices, and traffic sensors with a Central Computing Unit to allocate traffic rights based on economic principles, allowing users to bid for faster or slower journeys, and compensating those willing to take less desired routes, while prioritizing emergency vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional traffic management systems are used, then infrastructure cost is reduced, but traffic congestion increases and road usage efficiency decreases
Solution Approach 1:
The patent introduces a Central Computing Unit as an intermediary that coordinates between multiple traffic lights and users. This mediator receives journey requests, conducts auctions, and allocates priority rights, enabling efficient traffic management without requiring complex modifications to individual traffic light infrastructure.
Solution Approach 2:
The system implements dynamic traffic light control where priority rights are auctioned and allocated in real-time based on current traffic conditions and user bids. Traffic light phases are dynamically adjusted according to the auction results, allowing the system to adapt to changing road usage patterns and optimize throughput.
2Productivity
If real-time bidding system is implemented, then traffic congestion is reduced and road usage is optimized, but system complexity and infrastructure cost increase
Solution Approach 1:
The Central Computing Unit performs multiple functions including receiving journey requests, conducting auctions, allocating priority rights, and coordinating traffic lights. This multi-functional approach consolidates control logic into a single system, reducing overall complexity compared to distributed intelligent agents at each traffic light.
Solution Approach 2:
The system implements feedback loops where traffic light performance data is collected and used to inform future auction decisions. The Central Computing Unit continuously monitors road usage patterns and adjusts priority allocations based on observed outcomes, creating a self-optimizing control system.
3Adaptability or versatility
If dynamic traffic allocation is used, then travel time flexibility is improved, but user participation complexity increases
Solution Approach 1:
Users submit their journey requirements (origin, destination, time constraints) to the system, which then automatically conducts auctions and allocates priority rights. The system handles the complexity of bid evaluation and traffic coordination, while users simply receive their allocated time windows and route instructions.
Solution Approach 2:
Users can submit their journey requests in advance of their intended travel time. The system processes these requests ahead of time, conducts auctions for upcoming time slots, and provides users with confirmed priority allocations before their journey begins, reducing last-minute complexity.
Data Source
AI summary
A system and method for traffic decongestion which allows users to bid for faster passage and faster journeys. The system and method allows autonomous, semi-autonomous or user-driven cars to bid for faster passage for their journeys. Users willing to use slower journeys may be compensated for their contribution in reducing traffic congestion. In addition to reduction of traffic congestion, the system and method can normalize road usage, minimize road wear, give municipalities a new revenue stream, and save users time currently wasted by traffic.