Pre-Emptive Vehicular-to-Pedestrian Detection With Dynamic VRU Zones
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Solution Overview
Problem
Existing technologies lack solutions for dynamic VRU zone creation and advanced V2P detection to track UE mobility and provide timely alerts and communication configuration for potential vehicle-pedestrian collisions, especially in scenarios like school bus stops and cyclist routes.
Innovation Solution
Implementing V2P detection with edge or cloud servers to provide pre-emptive alerts and configure V2P communication parameters using V2P policies that adjust VRU zones based on UE mobility and data analytics, enabling direct device-to-device communication and network resource management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If V2P detection is implemented with edge or cloud servers to provide pre-emptive alerts and configure V2P communication parameters, then pedestrian safety is improved, but device complexity increases
Solution Approach 1:
The patent introduces edge servers or cloud servers as intermediary components between vehicular UEs and pedestrian UEs. These servers act as mediators that receive location data from UEs, perform V2P detection algorithms, and send alerts to relevant parties. This intermediary approach distributes system complexity to centralized servers rather than requiring complex processing capabilities in individual mobile devices, thereby improving safety while managing device complexity.
Solution Approach 2:
The system performs V2P detection and alert generation in advance before potential collisions occur. By continuously monitoring location data and predicting potential conflict scenarios, the system sends advance notifications to both vehicular and pedestrian UEs. This preliminary action allows time for preventive measures to be taken, improving safety outcomes while the server-based architecture manages complexity through centralized pre-computation.
2Measurement precision
If dynamic VRU zone creation and adjustment based on UE mobility is implemented, then detection accuracy is improved, but loss of time increases
Solution Approach 1:
The system implements periodic location updates where UEs transmit their positions at configured intervals rather than continuously. The edge or cloud servers process these periodic location data to update VRU zones and detect potential conflicts. This periodic approach maintains detection accuracy by receiving regular position information while significantly reducing processing time and network overhead compared to continuous monitoring.
Solution Approach 2:
The VRU zones are made dynamic, automatically adjusting their boundaries and locations based on real-time UE mobility data. When UEs move into or out of designated areas, the zones dynamically reconfigure to follow their paths. This dynamic adaptation maintains high detection accuracy for moving targets while the server-based processing manages time consumption through efficient spatial algorithms and prioritized updates.
3Reliability
If location reporting configuration and tracking of UE mobility is implemented, then V2P detection capability is improved, but use of energy by moving object increases
Solution Approach 1:
Instead of continuous location tracking, the system configures periodic location reporting where UEs transmit position data at predetermined intervals. This periodic approach maintains sufficient V2P detection capability to identify potential conflicts while dramatically reducing energy consumption compared to continuous transmission. The period duration can be adjusted based on mobility patterns and risk levels to optimize the balance between detection accuracy and energy usage.
Solution Approach 2:
The system allows configuration of location reporting parameters such as update frequency, trigger conditions, and reporting thresholds. These parameters can be adjusted dynamically based on the operational context, mobility speed, and risk assessment. By optimizing these parameters, the system maintains adequate V2P detection capability while minimizing unnecessary energy consumption during low-risk periods.
Data Source
AI summary
Disclosed herein are methods and systems for pre-emptive vehicular to pedestrian detection. A VAE client may receive a first request from an application client on a UE to enable VRUP services associated with the UE. The VAE client may send a second request to a VAE server to create a V2P policy. The VAE client may receive a first response to the second request indicating the status of the second request, the first response comprising information of the V2P policy that applies to the UE. The VAE client may send a second response to the first request indicating the status of the first request.