Vehicle Speed Monitoring via Hash Table Block Segmentation
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Solution Overview
Problem
Current vehicle speed monitoring systems face delays and data loss when determining if a vehicle is exceeding speed limits, leading to inefficiencies in instant judgment and response.
Innovation Solution
A method and system that segmentally limit vehicle speed by receiving route characteristics, expanding road segments into rectangles, dividing them into blocks, calculating minimum enclosing rectangles, and using a hash table to determine the vehicle's location and compare its speed with segment limits, employing an improved arc length algorithm for real-time judgments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the vehicle monitoring platform uses traditional speed monitoring methods with instant longitude and latitude upload, then the system can monitor vehicle speed, but time delay and data loss occur leading to non-instant judgment
Solution Approach 1:
The patent divides the route into multiple road segments and further segments the data processing into route expansion, rectangle division, block formation, and hash table creation. This segmentation allows the system to pre-process and organize spatial data into manageable units that can be quickly queried during speed monitoring, eliminating the need for real-time complex calculations and reducing judgment delay.
Solution Approach 2:
The system performs preliminary actions by pre-expanding road segments into rectangles, dividing them into blocks, calculating minimum enclosing rectangles, and establishing hash tables before actual speed monitoring begins. This pre-processing of spatial data structures enables instant location determination during operation, eliminating time delays in judgment while maintaining measurement precision.
2Measurement precision
If the system processes complete route data in real-time, then accurate speed judgment is achieved, but memory consumption increases
Solution Approach 1:
The patent segments the route data into road segments, then into rectangles, and further into blocks. Each block contains only the necessary spatial information for a specific segment. This hierarchical segmentation reduces memory usage by storing data in distributed, modular units rather than loading complete route data into memory simultaneously, while maintaining monitoring accuracy through systematic block querying.
Solution Approach 2:
The system extracts only the essential spatial characteristics needed for speed judgment by creating minimum enclosing rectangles from road segments and forming blocks from selected rectangles. This extraction process removes unnecessary data while retaining the critical geometric information required for accurate speed monitoring, thereby reducing memory consumption without sacrificing measurement precision.
3Measurement precision
If the system uses detailed road segment data for location determination, then accurate road segment identification is achieved, but computational complexity increases
Solution Approach 1:
The patent segments detailed road segment data into rectangular representations and further divides these rectangles into blocks. This segmentation simplifies the computational task by transforming complex road geometry into standardized rectangular units with clear boundaries, making location determination through hash table lookup computationally efficient while maintaining the precision needed for accurate road segment identification.
Solution Approach 2:
The system introduces hash tables as an intermediary data structure between the detailed road segment information and the location determination process. The hash table provides a direct mapping mechanism from spatial coordinates to block identifiers, eliminating the need for complex real-time geometric calculations and reducing algorithmic complexity while preserving location determination accuracy.
Data Source
AI summary
The present invention provides a method and system for segmentally limiting the speed of a vehicle. The method comprises: receiving characteristic parameters of a route sent by a vehicle monitoring platform, and respectively expanding a plurality of road segments of the route into a plurality of rectangles; dividing the plurality of rectangles into blocks sequentially; calculating a minimum enclosing rectangle of the at least two rectangles, and counting vertex information of the minimum enclosing rectangle of each block so as to establish a hash table; obtaining an instant longitude and latitude of a moving vehicle, searching in the hash table so as to determine a block where the vehicle is located, and judging a road segment where the vehicle is currently located; and comparing a current speed of the vehicle with a limiting speed of the road segment where the vehicle is currently located, judging whether the vehicle exceeds the limiting speed.