Vehicle Data Distribution via Predicted Path Overlap
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Highly automated driving systems face challenges in efficiently distributing data traffic across region servers, leading to network load issues due to the transmission of large volumes of information data, especially when vehicles' routes overlap, and existing methods fail to dynamically adjust to changing traffic conditions.
Innovation Solution
The system predicts vehicles' future routes and registers them with region servers based on predicted path data, allowing only relevant information to be transmitted to vehicles within specific regions, enabling intelligent load distribution and scalability by dynamically adjusting region sizes and server responsibilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If information data are transmitted to all vehicles in a region, then complete information coverage is achieved, but network load increases significantly
Solution Approach 1:
The system transmits information data selectively to vehicles based on their predicted path overlap with the event location, rather than uniformly to all vehicles in a region. Vehicles are categorized into different groups (first group with overlapping paths, second group without overlap), and data transmission is applied locally to only those vehicles in the first group, thereby reducing overall network load while maintaining necessary information coverage.
Solution Approach 2:
The system performs preliminary path prediction for vehicles before transmitting information data about events. By predicting vehicle paths in advance and comparing them with event locations, the system pre-identifies which vehicles will need the information data, allowing selective transmission before the actual event occurs, thus avoiding unnecessary data transmission to vehicles that won't need the information.
2Stability of the object's composition
If region servers are permanently assigned to vehicles, then communication stability is improved, but adaptability to changing traffic conditions deteriorates
Solution Approach 1:
The system dynamically determines region server assignments based on real-time predicted path data rather than using permanent static assignments. Vehicles are temporarily assigned to region servers based on their predicted paths overlapping with event locations, allowing the system to adapt to changing traffic conditions, vehicle routes, and event distributions while maintaining communication stability through consistent server selection during the vehicle's relevant time period.
3Measurement precision
If path prediction is performed for all vehicles, then data distribution accuracy is improved, but computational complexity increases
Solution Approach 1:
The system extracts and processes only the necessary path prediction data for vehicles that are relevant to specific events, rather than performing comprehensive path prediction analysis for all vehicles in the system. By focusing computational resources on vehicles whose predicted paths overlap with event locations, the system achieves accurate data distribution while reducing overall computational complexity through selective processing.
Data Source
AI summary
A system for providing data for vehicles includes a region server for providing information data for vehicles in a region. A first and second of the vehicles predict path data, which indicate at least one route that the first and second vehicles will drive with a probability. The first and second vehicles are registered in the region server if the route of the first and second vehicles indicated by the predicted path data lies in the region. The region server produces the information data in dependence on received sensor data of the first vehicle. The produced information data are sent by the region server to the second vehicle if the predicted path data of the second vehicle overlap with the predicted path data of the first vehicle and the second vehicle is registered in the region server.