Dynamic Vehicle Position Reporting Interval for Cloud Bandwidth Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cloud-based unicast communication systems for vehicles within road networks face inefficiencies due to high bandwidth requirements for frequent position updates, as vehicles report their positions frequently to ensure accurate message routing, leading to unnecessary data traffic and bandwidth usage.
Innovation Solution
A method that determines the optimal reporting interval for vehicle position updates based on the most probable path and its complexity within the road network, using a look-up table and adjusting intervals according to speed and road conditions, to minimize data traffic while maintaining accurate position tracking and prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frequent position reporting is implemented to keep vehicle location up-to-date, then location accuracy is improved, but bandwidth usage increases significantly
Solution Approach 1:
The system dynamically adjusts the position reporting interval based on the vehicle's current situation, road network complexity, and predicted path. Instead of using a fixed reporting frequency, the interval is adapted in real-time to balance location accuracy requirements with bandwidth conservation, reporting more frequently when precision is critical and less frequently when the vehicle's position is stable and predictable.
Solution Approach 2:
The system changes the reporting parameter (time interval) based on varying conditions. The reporting interval is modified according to road network complexity, vehicle speed, and location accuracy requirements, allowing the system to optimize bandwidth usage while maintaining sufficient location precision for different operational contexts.
2Loss of information
If unicast messaging is used to route information only to relevant vehicles, then data relevance is improved, but system complexity increases due to required position tracking and routing logic
Solution Approach 1:
The system performs preliminary actions by determining the vehicle's most probable path in advance and pre-calculating which vehicles will be relevant for upcoming events. This allows the routing logic to be simplified, as vehicles can be subscribed to relevant data streams based on their predicted trajectory rather than requiring complex real-time position tracking and dynamic routing decisions.
Solution Approach 2:
The system introduces an intermediary layer (the server) that manages the complexity of routing and relevance determination. Instead of requiring complex routing logic in each vehicle or peer-to-peer coordination, the server acts as a mediator that receives position reports, determines relevance based on predicted paths and event locations, and routes information appropriately, simplifying the overall system architecture.
3Reliability
If broad area broadcasting is used to ensure all vehicles receive relevant data, then data delivery completeness is improved, but bandwidth efficiency deteriorates due to irrelevant data transmission
Solution Approach 1:
The system segments the vehicle population into different groups based on their predicted paths, current locations, and relevance to specific events. Instead of broadcasting to all vehicles in a broad area, information is targeted to specific segments of vehicles that are actually relevant, maintaining data delivery completeness for the appropriate audience while eliminating wasteful transmissions to irrelevant vehicles.
Solution Approach 2:
The system applies local quality by tailoring the data delivery approach to each vehicle's specific context and needs. Rather than using a uniform broadcast approach, the system determines which vehicles should receive which information based on their individual predicted paths and locations, ensuring that each vehicle receives complete and relevant data without the overhead of broadcasting to all vehicles in the area.
Data Source
Figure 1
Figure 2
AI summary
Disclosed herein is a method and system for minimizing the required bandwidth for a cloud (3) based unicast communication with a vehicle (2) operating within a road network (1), where the cloud (3) comprises a cloud logic (5) and the vehicle comprises a vehicle internal logic (7). The method comprising the steps of: determining a current position with direction of the vehicle (2) within the road network (1); setting an interval at which the vehicle (2) is to report an update on its position based on a most probable path (4) of the vehicle (2) and the complexity thereof, where the most probable path (4) is a set of possible paths a predetermined distance ahead of the vehicle (2) that it is most probable to travel along given its current position with direction within the road network (1); communicating the set interval to the vehicle internal logic (7); and reporting an updated current position of the vehicle (2) to the cloud (3) with the set reporting interval.