Cooperative Adaptive Cruise Control for Traffic Flow Optimization
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Solution Overview
Problem
Traffic congestion at restrictive points such as bridges and tunnels is difficult to manage with existing infrastructure, as it requires substantial investment and can be perceived as annoying by the public, while controlling vehicle speed and spacing is challenging without complex systems.
Innovation Solution
A processor-based system that determines traffic density and models optimal traffic parameters to control vehicle speed and spacing, using cooperative adaptive cruise control (CACC) to regulate traffic flow by communicating with multiple vehicles, thereby optimizing vehicle spacing and speed to prevent congestion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traffic control devices (lights, signals) are installed at restrictive points to optimize traffic flow, then traffic flow optimization is achieved, but substantial infrastructure investment is required and traffic is slowed unnecessarily at control points
Solution Approach 1:
The patent replaces physical traffic control infrastructure (lights, signals, barriers) with a software-based cooperative adaptive cruise control system. Vehicles equipped with CACC technology communicate with each other and with road sensors to automatically adjust speed and spacing, eliminating the need for substantial infrastructure installation while maintaining traffic flow optimization.
Solution Approach 2:
The system enables vehicles to self-regulate their speed and spacing through automated cruise control algorithms. Rather than requiring external control devices to manage traffic flow, each vehicle autonomously adjusts its behavior based on real-time data from surrounding vehicles and road conditions, reducing infrastructure requirements while maintaining optimal flow.
2Productivity
If traffic control devices are installed to optimize flow at certain points, then flow optimization is achieved, but public annoyance increases due to perceived onerous and unnecessary devices
Solution Approach 1:
By replacing visible physical control devices with invisible automated vehicle systems, the patent eliminates sources of public annoyance. The CACC system operates through vehicle-mounted sensors and communication systems rather than imposing overhead lights, signals, or physical barriers that drivers perceive as intrusive or unnecessary.
Solution Approach 2:
The system uses wireless communication and sensor data as intermediaries between vehicles and traffic management, eliminating the need for visible control devices. Information about optimal speed and spacing is transmitted electronically to vehicles, which then autonomously adjust, removing the need for physical infrastructure that causes public annoyance.
3Quantity of substance
If vehicles are spaced closely to maximize vehicles per mile, then density is increased, but traffic flow optimization is lost due to exceeding the optimal density point
Solution Approach 1:
The CACC system continuously monitors actual vehicle spacing and speed, comparing it against optimal values calculated from real-time traffic density data. When vehicles deviate from optimal spacing, the system provides feedback through automated adjustments to maintain the optimal density point, preventing both excessive spacing and dangerous overcrowding while maximizing traffic flow.
Solution Approach 2:
The system dynamically adjusts speed and spacing parameters based on real-time traffic conditions. Rather than maintaining fixed spacing intervals, the CACC system continuously modifies vehicle parameters (speed, acceleration, following distance) to maintain optimal density, allowing maximum vehicles per mile to pass through restrictive points without exceeding the flow optimization threshold.
Data Source
AI summary
A system includes a processor configured to determine traffic density over a road segment. The processor is also configured to model traffic parameters to maximize traffic flow over the road segment, based on the traffic density and travel characteristic data received from a plurality of vehicles exiting the road segment. The processor is further configured to determine a speed to density curve, using the model, that would maximize traffic flow and send the speed to density curve to a vehicle entering the road segment.