Automatic Driving Assist Using Preceding Vehicle Width Data in Snow
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Solution Overview
Problem
In snowy conditions, automatic driving systems face challenges in maintaining continuous operation due to reduced visibility and mismatch between high-accuracy road maps and actual road conditions, leading to increased driver burden as on-board sensors struggle to detect lane markers and road shapes.
Innovation Solution
An automatic driving assist system that aggregates vehicle width and position information from preceding vehicles using a cloud server, generating travelable width data to determine if the own vehicle can pass through measurement points by automatic driving, even in situations where on-board sensors are ineffective, by shifting the target travel path to accommodate provisional lanes formed by snow removal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If on-board peripheral monitoring sensors (camera, laser scanner) are used to detect lane markers and road shape, then automatic driving control can be implemented with redundancy, but in snowy conditions the sensors cannot detect lane markers due to accumulated snow, reducing reliability and forcing manual driving takeover
Solution Approach 1:
The patent introduces cloud-based road information (high-accuracy road map) as an intermediary data source that provides predetermined road shape information independent of on-board sensor detection. This mediator supplys lane and road width data from external sources, allowing the system to maintain automatic driving functionality when on-board sensors fail due to snow accumulation.
Solution Approach 2:
The patent shifts from relying solely on on-board sensor detection (spatial dimension at vehicle level) to incorporating cloud-based road information (spatial dimension at map level). By aggregating position information and vehicle width information from multiple preceding vehicles across different time points, the system constructs travelable width data in a higher-dimensional space that compensates for sensor failures.
2Adaptability or versatility
If high-accuracy road map information is used for automatic driving control, then the system can operate without on-board sensor detection, but the road map does not reflect real-time changes in road conditions such as snow removal creating provisional lanes
Solution Approach 1:
The patent implements a feedback mechanism where position information and vehicle width information from preceding vehicles are continuously aggregated and used to update travelable width information. This feedback loop allows the system to detect actual road conditions (including snow removal areas) and adjust the target travel path accordingly, bridging the gap between static road maps and dynamic real-world conditions.
Solution Approach 2:
The patent performs preliminary aggregation of position information and vehicle width information from multiple preceding vehicles before the own vehicle reaches a measurement point. By calculating travelable width in advance based on aggregated data from vehicles that have already passed through the area, the system prepares updated road condition information that reflects current conditions including snow removal, allowing the own vehicle to adapt its path before encountering the actual road condition.
3Measurement precision
If the system requires detection of lane markers by on-board sensors to maintain redundancy, then measurement precision is maintained, but in snowy conditions the detection fails and automatic driving must be canceled, increasing driver burden
Solution Approach 1:
The patent uses cloud-based road information as a copy or replica of the physical road structure, storing predetermined lane positions and road width data. Instead of requiring on-board sensors to directly detect and measure lane markers, the system references this copied road model, which can be updated with real-time conditions from preceding vehicle data. This copying approach maintains measurement precision while eliminating the need for direct sensor detection in snowy conditions.
4Reliability
If the system uses aggregated position information from preceding vehicles to determine travelable width, then automatic driving can continue in snowy conditions, but the system complexity increases due to data aggregation and processing requirements
Solution Approach 1:
The patent creates a universal road information system that serves multiple functions: it provides high-accuracy road map data for normal conditions, aggregates real-time position and vehicle width information from preceding vehicles for updated conditions, and supplies this integrated information to multiple vehicles. This multi-functional road information system reduces individual vehicle complexity while maintaining high reliability through shared infrastructure.
Data Source
AI summary
The automatic driving assist system includes a traveling information acquirer that acquires vehicle width information, passing date and time, and position information when passing the measurement point, on preceding vehicles, from the preceding vehicle passing through the measurement point for each measurement, a traveling environment information acquirer that acquires traveling environment information at each measurement point, a calculator that acquires a travelable width at the measurement point based on information of the preceding vehicles and the traveling environment information, and a determiner that determines whether the own vehicle can travel to pass through the measurement point by automatic driving by comparing the travelable width with an own-vehicle travelable width. The calculator aggregates the position information and the vehicle width information acquired during a period from when the own vehicle is expected to pass the measurement point until before a predetermined time, to acquire the travelable width.