Inference Engine for Dynamic Traffic Intersection Control

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Current traffic control signaling devices at intersections operate on a simple timer-based system, failing to account for real-time traffic density, leading to inefficiencies and wasted resources as vehicles wait unnecessarily for red lights while others are allowed to pass.

Innovation Solution

An intersection management system utilizing sensors to detect traffic conditions, an inference engine processing user-defined traffic control algorithms, and a signal driver to actuate multi-state traffic signaling devices, optimizing vehicular and pedestrian flow based on real-time data and user-defined goals.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If timer-based control strategies are used for traffic signaling devices, then the operation is simple and reliable, but traffic flow efficiency deteriorates and unnecessary time and energy resources are wasted

Engineering Contradiction:

Improvetraffic flow efficiencyVSAvoidvehicle wait time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system employs sensors to detect real-time traffic conditions (vehicle presence, density, movement) and feeds this information back to the inference engine. The inference engine continuously adjusts signaling device operation based on current traffic state, replacing fixed timer-based control with dynamic feedback-driven control that adapts to actual traffic conditions.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system changes the operational parameters of traffic signaling devices dynamically based on detected traffic conditions. Instead of fixed timing cycles, the signaling duration, phase sequencing, and green light allocation are adjusted in real-time according to traffic density and flow characteristics detected by sensors.

Inventive Principle:

Principle #35Parameter changes

2Productivity

If timer-based cycling is used to control traffic flow, then the control mechanism is simple, but energy consumption increases due to unnecessary vehicle waiting

Engineering Contradiction:

Improvetraffic flow efficiencyVSAvoidvehicle energy consumption

Core Design Contradiction:

ProductivityVSUse of energy by moving object

Solution Approach 1:

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system maintains continuous useful action by keeping traffic flowing smoothly through the intersection based on real-time conditions. By detecting vehicle presence and movement continuously, the system minimizes stop-and-go patterns and keeps vehicles moving when possible, reducing idle energy consumption while maintaining efficient throughput.

Inventive Principle:

Principle #20Continuity of useful action

3Productivity

If fixed time-based control is implemented, then the system complexity is low, but adaptability to varying traffic conditions deteriorates

Engineering Contradiction:

Improvetraffic flow efficiencyVSAvoidresponse to traffic density variations

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The system transitions from static fixed-time control to dynamic adaptive control. The inference engine continuously processes sensor data and adjusts signaling device parameters in real-time, allowing the system to adapt its behavior dynamically to changing traffic conditions, vehicle density, and flow patterns.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

Inventive Principle:

Principle #35Parameter changes

4Productivity

If sensors and inference engines are added to traffic control systems, then traffic flow efficiency improves, but device complexity increases

Engineering Contradiction:

Improvetraffic flow efficiencyVSAvoidcontrol system complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system implements self-service by enabling the traffic control system to automatically detect, analyze, and respond to traffic conditions without human intervention. The sensors autonomously monitor traffic state, the inference engine autonomously processes data and determines optimal signaling strategies, and the control system autonomously adjusts signal timing based on real-time conditions.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The inference engine serves multiple functions: it processes sensor data, determines traffic conditions, selects appropriate control strategies, and generates control signals for signaling devices. This multi-functional approach consolidates what could be separate complex systems into a single integrated intelligence layer.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS7973675B2Goal-driven inference engine for traffic intersection management

Publication Date: 2011.07.05 THE BOEING CO

AI summary

A system includes a plurality of sensors that provide information regarding instantaneous traffic conditions incident to an intersection. An inference engine of the system receives the sensor information and processes user-defined traffic control algorithms and weighted management parameters. Control signals are derived in accordance with the processing. Multi-state signaling devices are driven in accordance with the control signals so as to manage vehicular and pedestrian traffic flow at the intersection. Playback of historic traffic information permits analysis and verification of the traffic management strategies implemented by the system.