Dynamic Traffic Light Control for Vulnerable Road User Safety
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Solution Overview
Problem
Current traffic management systems do not effectively prioritize vulnerable road users (VRUs) while maintaining smooth traffic flow, leading to potential accidents and dissatisfaction among both VRUs and vehicle users.
Innovation Solution
A dynamic infrastructure-based monitoring system using multi-modal sensors like cameras, LiDAR, and radio proximity estimation to predict VRU behavior and intent, optimizing traffic light phases to adapt priority and reduce congestion and accidents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traffic lights are optimized for vehicle traffic flow, then traffic flow efficiency is improved, but safety of vulnerable road users deteriorates
Solution Approach 1:
The traffic light system dynamically adjusts signal phases based on real-time detection of vulnerable road users. The controller monitors sensor data (cameras, LiDAR, radio proximity) and adaptively changes traffic light states to prioritize VRU safety when detected, while maintaining efficient vehicle flow when VRUs are absent. This dynamic adaptation resolves the contradiction by making the system responsive to actual conditions rather than fixed optimization.
Solution Approach 2:
The system implements continuous feedback loops where sensors detect VRU presence and behavior, the controller processes this information to determine intent, and traffic light phases are adjusted accordingly. This feedback mechanism ensures that safety considerations are continuously integrated into traffic flow management, resolving the contradiction between efficiency and safety.
2Reliability
If traffic lights provide priority to VRUs, then safety of vulnerable road users is improved, but traffic flow smoothness deteriorates
Solution Approach 1:
The system provides VRU priority only when and where needed, based on dynamic detection of VRU presence, intent, and crossing probability. When no VRUs are detected or their crossing intent is low, the system reverts to normal vehicle-optimized timing, thus maintaining traffic flow smoothness. This conditional, dynamic priority assignment resolves the contradiction between safety improvement and flow maintenance.
Solution Approach 2:
The system applies different control strategies to different traffic light phases and intersections based on local VRU detection. Rather than uniformly prioritizing VRUs across all times and locations, the system locally adapts priority assignment to specific VRU situations, minimizing impact on overall traffic flow while maximizing safety where needed.
3Measurement precision
If multi-modal sensors are deployed to predict VRU behavior, then detection precision is improved, but device complexity increases
Solution Approach 1:
The system segments the complex sensing task across multiple specialized sensors (cameras for visual behavior, LiDAR for depth and motion, radio proximity for near-field detection). Each sensor type handles specific aspects of VRU detection, and the controller integrates these segmented data streams. This segmentation achieves high detection precision while managing complexity through modular sensor architecture.
Solution Approach 2:
The controller serves multiple functions: it processes data from various sensor types, predicts VRU behavior and intent, determines crossing probability, and controls traffic light phases. This multi-functional controller consolidates complexity into a single processing unit that handles all sensing and control tasks, reducing overall system complexity despite using multiple sensor modalities.
Data Source
AI summary
Systems and methods for dynamically controlling an infrastructure item are disclosed. The systems and methods may include receiving environmental data. The environmental data may capture behavior of a crossing user. An intent of the crossing user may be determined based on the environmental data. A setting of the infrastructure item may be changed based on the intent of the crossing user.