Vehicle Trip Pattern Matching Across Detection Zones for 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 customer dissatisfaction due to errors in vehicle identification and billing, especially in open ticket systems without clear entry and exit points.
Innovation Solution
A system and method for determining vehicle trips using predefined detection zones and matching vehicle detection events to the longest trip pattern, verifying travel times within a threshold to define trips, and charging based on trip patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If open ticket toll collection systems are implemented without clear entry and exit points, then infrastructure needs are reduced, but accurately determining vehicle trips becomes challenging
Solution Approach 1:
The roadway is segmented into multiple detection zones along the route, each capable of independently detecting vehicle presence. These segmented detection zones work together to establish entry and exit points dynamically, allowing trip determination without requiring physical barriers or clearly marked toll plazas, thus reducing infrastructure needs while maintaining measurement precision.
2Productivity
If conventional transponder and license plate reading systems are used, then vehicle identification is performed, but error rates range from two percent to ten percent
Solution Approach 1:
The system merges multiple detection methods (transponder reading, license plate recognition, and detection zone tracking) into a unified trip determination framework. By combining these methods and cross-validating their results, the system reduces individual method errors and achieves more reliable vehicle identification and trip characterization.
Solution Approach 2:
The system employs feedback mechanisms where detection zone data is continuously compared against trip pattern definitions and vehicle identification results. When discrepancies are detected, the system adjusts its determination of trips and billing assignments, reducing errors through iterative verification and correction.
3Ease of operation
If fixed amount charging per toll gateway is used, then billing is straightforward, but trip-based billing support is lacking
Solution Approach 1:
The billing system transitions from static fixed-amount charging to dynamic trip-based billing. The system dynamically determines trip characteristics by analyzing sequences of detection zone data, identifies applicable trip patterns, and calculates appropriate charges accordingly. This dynamic approach maintains operational simplicity while enabling versatile trip-based billing for minimum/maximum charge enforcement and accurate traffic modeling.
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.