Vehicle Trip Pattern Matching for Accurate Open-Road Toll Billing
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Solution Overview
Problem
Existing toll collection systems face challenges in accurately determining vehicle trips on roadways, leading to inefficiencies, revenue loss, and incorrect billing due to errors in transponder and license plate reading, especially in open ticket systems without clear entry and exit points, and lack support for trip-based billing.
Innovation Solution
A system and method for determining vehicle trips on a roadway by using predefined trip patterns and vehicle detection events, matching these events to the longest corresponding pattern, and verifying travel times within a threshold to define trips, allowing for trip-based billing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If transponder and license plate reading systems are used to identify vehicles, then vehicle identification can be performed, but error rates range from two percent to ten percent leading to incorrect billing and revenue loss
Solution Approach 1:
The system segments vehicle identification into multiple independent detection zones along the roadway. Each zone independently detects vehicles, and the system aggregates these detections to form comprehensive trip records. This segmentation allows cross-validation of identification data across multiple zones, reducing errors in single-point identification while maintaining billing accuracy.
Solution Approach 2:
The system introduces detection zones as intermediary elements between vehicles and the billing system. These zones collect vehicle passage data and transmit it to a central processing system that aggregates and validates the information. This intermediary layer filters out errors and inconsistencies before billing occurs, improving both identification accuracy and billing reliability.
2Ease of manufacture
If open ticket toll collection systems are used with toll gateways along mainline roadways, then infrastructure needs are reduced, but accurately determining when vehicles enter and exit the roadway becomes challenging
Solution Approach 1:
The system divides the roadway into multiple detection zones that segment the continuous travel path into discrete measurable segments. Each zone independently detects vehicle passages, and the system aggregates these segmented detections to accurately determine entry and exit points. This segmentation transforms the continuous open ticket system into a series of measurable discrete events, maintaining infrastructure simplicity while improving detection precision.
Solution Approach 2:
The system performs preliminary detection and recording of vehicle passages at multiple zones before final trip determination. By pre-collecting data from multiple detection zones along the roadway, the system builds a comprehensive record of vehicle movement patterns. This preliminary action enables accurate retroactive determination of entry and exit points without requiring complex real-time infrastructure modifications.
3Ease of operation
If conventional fixed amount charging per toll gateway is used, then billing is straightforward, but trip-based billing support is lacking preventing accurate traffic modeling and revenue optimization
Solution Approach 1:
The system transitions from static fixed-amount charging to dynamic trip-based billing. The billing amount is no longer fixed but dynamically calculated based on the actual trip pattern detected by multiple detection zones. The system adapts billing to the specific circumstances of each trip, enabling trip-based billing capability while maintaining operational simplicity through automated pattern recognition and calculation.
Solution Approach 2:
The system enables self-service trip determination by automatically detecting, aggregating, and validating vehicle passage data from multiple zones. The system performs self-validation of trip patterns and automatically determines billing amounts without manual intervention. This self-service approach maintains billing simplicity while providing sophisticated trip-based billing capability through automated processing.
Data Source
AI summary
A system, and method thereof, is provided for determining a vehicle trip on a roadway. The system may include a plurality of detection zones and a computer program product residing on a non-transitory computer readable medium and executable by one or more processors to direct performance of operations comprising: receiving one or more vehicle detection events corresponding to a given vehicle, each of the one or more vehicle detection events associated with one of a plurality of detection zones; storing a plurality of predefined trip patterns, each of the plurality of predefined trip patterns including at least one detection zone of the plurality of detection zones; and matching the one or more vehicle detection events to a longest matching trip pattern of the plurality of predefined trip patterns to define a trip.