Monitoring Plan Evaluation System for Toll Billing
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Solution Overview
Problem
In autonomous toll billing systems, detecting and preventing cheating vehicles without on-board units is challenging due to the lack of external monitoring capabilities, leading to inefficiencies in identifying and addressing cheating behaviors, which vary by location and time.
Innovation Solution
A monitoring plan evaluation system that includes a vehicle monitoring information acquisition unit, a movement information acquisition unit, and a passage extent information generator to predict optimal monitoring locations and times for detecting cheating vehicles by analyzing vehicle movement and monitoring data, generating passage extent information to identify high-risk areas and times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If on-board units autonomously perform billing processes, then billing can be performed without road-side facilities and billing conditions can be flexibly set, but cheating detection capability deteriorates because external monitoring becomes impossible
Solution Approach 1:
The patent introduces road-side monitoring facilities as an intermediary component that works in conjunction with on-board units. The road-side facility captures images of vehicles and transmits them to a server, which then determines whether cheating has occurred. This mediator enables external monitoring capability while preserving the autonomous billing functionality of on-board units, thus resolving the contradiction between billing flexibility and cheating detection capability
Solution Approach 2:
The patent combines the autonomous billing function of on-board units with the external monitoring function of road-side facilities into an integrated system. The on-board unit performs autonomous billing based on GPS position information, while the road-side facility simultaneously performs image capture and cheating detection. The server merges these two functions by receiving data from both sources and making comprehensive billing decisions, thus achieving both billing flexibility and reliable cheating detection
2Ease of operation
If monitoring is performed at fixed locations and times, then monitoring operations are simple to manage, but detection efficiency deteriorates because cheating situations vary by place and time
Solution Approach 1:
The patent implements dynamic monitoring point selection by the server based on analyzed cheating patterns and vehicle data. Instead of fixed monitoring locations, the server dynamically determines which road-side facilities should be activated and where monitoring points should be positioned, adapting to varying cheating situations different places and times. This dynamic approach maintains operational simplicity while significantly improving detection efficiency
Solution Approach 2:
The patent changes the parameters of monitoring operations (location, time, target vehicles) based on data analysis results. The server analyzes cheating patterns and adjusts monitoring parameters dynamically, selecting optimal monitoring points and times rather than using fixed schedules. This allows the system to adapt to varying cheating situations while keeping the management process simple through automated parameter adjustment
3Reliability
If all vehicles are monitored continuously, then cheating detection coverage is maximized, but system complexity and cost increase significantly
Solution Approach 1:
The patent applies local quality by focusing monitoring resources on specific vehicles and locations where cheating is most likely to occur. The server analyzes data to identify high-risk vehicles and routes, then directs monitoring efforts to those specific areas rather than uniformly monitoring all vehicles everywhere. This selective approach maintains high detection coverage while reducing overall system complexity
Solution Approach 2:
The patent implements partial monitoring action by selectively monitoring only those vehicles and locations that require attention based on risk assessment. Rather than continuously monitoring all vehicles, the system applies monitoring resources partially to high-priority targets identified through data analysis, achieving effective cheating detection with reduced system complexity and lower costs
Data Source
AI summary
This monitoring plan evaluation system includes a vehicle monitoring information acquisition unit which acquires vehicle monitoring information indicating a result of monitoring of a vehicle, the vehicle monitoring information including monitoring execution condition information indicating at least one of a monitoring place and a monitoring time of the vehicle and information of the vehicle that has been subjected to monitoring at the monitoring place or the monitoring time, a movement information acquisition unit which acquires vehicle movement information regarding movement of each of a plurality of vehicles, and a passage extent information generator which generates passage extent information, which indicates an extent of passage of a vehicle that is to be monitored in a condition indicated by a candidate monitoring execution condition including at least one of a place and a time where and when to monitor vehicles, on the basis of the vehicle movement information and the vehicle monitoring information.