Travelling Support System Predicting Parked Vehicle Duration
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Solution Overview
Problem
Existing travelling support systems cannot predict the duration for which a vehicle will be parked or stopped on a road, making it difficult to provide appropriate travelling support that considers parked or stopped vehicles.
Innovation Solution
A travelling support system that includes a receiving unit to detect parked or stopped vehicles and a predicting unit using a duration predicting model to forecast the duration based on vehicle information and influential factors such as facility type and time, allowing for proactive lane changes and smoother travel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a travelling support system detects parked or stopped vehicles on the road, then the system can identify potential obstacles, but it cannot predict how long these vehicles will remain parked or stopped, making it difficult to plan optimal travel routes and timing
Solution Approach 1:
The system performs preliminary action by predicting the duration before the parked/stopped vehicle actually becomes an obstacle. The duration predicting model estimates how long a vehicle will remain parked or stopped, allowing the traveling vehicle to plan its route and timing in advance, thus preventing time loss from unexpected obstacles.
2Productivity
If the system maintains current travel speed without prediction capability, then the vehicle operates efficiently, but it cannot respond proactively to parked or stopped vehicles, leading to sudden deceleration or route changes
Solution Approach 1:
The system maintains travel efficiency while improving reliability by using the duration predicting model to forecast parked/stopped vehicle durations in advance. This allows the vehicle to plan smooth route changes or speed adjustments proactively, rather than reacting suddenly to obstacles, thus maintaining both productivity and travel smoothness.
3Measurement precision
If the system acquires detailed parked/stopped vehicle information from preceding vehicles and sensors, then detection accuracy improves, but the complexity of processing and analyzing this data increases
Solution Approach 1:
The system uses an automatic driving center as an intermediary to handle complex data processing. The center collects parked/stopped vehicle information from multiple preceding vehicles and sensors, processes this data centrally using the duration predicting model, and provides simplified prediction results to traveling vehicles. This distributes the computational complexity to a centralized system while keeping individual vehicle systems relatively simple.
Data Source
AI summary
A travelling support system includes a receiving unit configured to receive parked/stopped vehicle information indicating a detection of a parked/stopped vehicle on a travelling road from a preceding vehicle which is travelling or a sensor on the travelling road; and a predicting unit that predicts, based on the parked/stopped vehicle information and a duration predicting model that predicts a parked/stopped duration as a duration in which the parked/stopped vehicle continues to park or stop, the parked/stopped duration.