Traffic Volume Estimation Using Spatiotemporal Point Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional methods for estimating traffic volume are costly, labor-intensive, and limited to specific locations, making it difficult to determine traffic volumes on-demand for various locations.
Innovation Solution
A traffic volume estimation system that uses scant data and known volume-to-concentration ratios to determine estimated traffic volumes, leveraging spatiotemporal and geographic data, and providing recommendations for transportation engineering and zoning without the need for manual counting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional electronic traffic recording devices are installed to automatically count traffic, then traffic volume measurement accuracy is improved, but installation cost and maintenance cost increase
Solution Approach 1:
The patent uses mobile devices (smartphones, tablets, laptops) as copies of traditional traffic counting systems. These devices run applications that replicate traffic volume measurement functionality without requiring specialized hardware installation. The mobile devices capture location data, timestamps, and device identifiers to estimate traffic volumes, providing a cost-effective alternative to electronic recording devices while maintaining measurement capability.
Solution Approach 2:
The patent replaces the mechanical/electronic traffic recording device system with an information-based system using mobile computing devices. Instead of physical sensors and counters installed on roads, the system uses software applications on mobile devices that leverage existing GPS, accelerometer, and network capabilities to perform traffic estimation, eliminating installation and maintenance costs associated with traditional devices.
2Productivity
If manual counting by observers is used to estimate traffic volume, then labor costs are incurred, but location flexibility is limited
Solution Approach 1:
The patent implements a self-service system where mobile devices automatically perform traffic volume estimation without requiring human observers. The system autonomously collects location data, timestamps, and device identifiers from mobile devices in the area, processes this data through algorithms to estimate traffic volumes, and generates reports automatically. This eliminates the need for manual counting labor while providing continuous, on-demand traffic information.
Solution Approach 2:
The patent introduces a computational intermediary system that processes raw mobile device data into traffic volume estimates. This intermediary layer consists of servers and algorithms that aggregate location data from multiple mobile devices, apply statistical methods to estimate traffic volumes, and deliver results to users. This intermediary system replaces human observers by automatically performing the data collection, processing, and analysis functions.
3Loss of information
If counting facilities are installed at specific locations to measure traffic, then traffic data is available at those locations, but traffic volumes at other locations cannot be determined
Solution Approach 1:
The patent creates a universal traffic estimation system that can determine traffic volumes at any location without requiring physical counting facilities. The system uses mobile devices that continuously report their locations and characteristics, allowing traffic estimation at any geographic point where mobile devices are present. This universal approach eliminates the need for location-specific installation while providing flexible, on-demand traffic information anywhere in the service area.
Solution Approach 2:
The patent transitions from fixed-point measurement (traditional counting facilities at specific locations) to spatially-distributed measurement (mobile devices moving throughout the area). By adding the dimension of mobile device movement and using location data from multiple moving sources, the system can estimate traffic volumes at any location in the service area, not just at predetermined counting sites. This dimensional shift from static to dynamic measurement enables location flexibility.
Data Source
AI summary
As described herein, systems and methods for estimating traffic volume provide the ability to identify an area of interest in which to determine an estimated traffic volume, obtain point data associated with the area of interest, determine a concentration of the area of interest based on the point data, obtain one or more known volume-to-concentration ratios, and determine the estimated traffic volume for the area of interest based the concentration of the area of interest and the one or more known volume-to-concentration ratios. The point data includes at least spatiotemporal data and geographic information data. In some cases, the estimated traffic volume is provided to an end user. In some cases, at least one traffic element recommendation for the area of interest based on the estimated traffic volume can be determined and provided to an end user.