Probe Vehicle Traffic Congestion Mapping From Speed Change Data
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Solution Overview
Problem
Existing congestion prediction systems rely on sparse roadside sensors that provide insufficiently granular traffic data, leading to inaccurate analysis of traffic congestion and incomplete road network coverage, which can prolong travel times and increase collision risks.
Innovation Solution
A system that utilizes probe data and map data to generate accurate traffic congestion data by determining speed changes, congestion duration, and classification of recurring or non-recurring congestion, enabling real-time navigation assistance and congestion warnings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If roadside sensors are used to measure traffic data, then traffic congestion data can be obtained, but the sensors are spaced at least half miles apart and don't provide information granular enough to produce accurate traffic data
Solution Approach 1:
The patent uses probe vehicles as intermediary carriers to collect traffic data. These vehicles are equipped with sensors that measure speed, location, and other traffic parameters, effectively distributing the measurement function across the vehicle fleet rather than requiring dense roadside sensor deployment. This intermediary approach enables high-resolution traffic data collection without the complexity of dense infrastructure sensing.
Solution Approach 2:
The system creates virtual copies of physical sensors by deploying sensing capabilities within probe vehicles. Instead of having fixed roadside sensors at every location, the patent replicates sensor functionality across multiple moving vehicles, allowing traffic conditions to be measured from multiple perspectives and locations simultaneously, thereby achieving fine-grained spatial resolution.
2Area of stationary object
If roadside sensors are deployed to cover the road network, then traffic congestion data can be collected, but from economic perspective, the roadside sensors may unlikely provide full road network coverage
Solution Approach 1:
The patent implements a self-service model where vehicles themselves perform the data collection function traditionally requiring roadside infrastructure. Probe vehicles autonomously measure their own speed, location, and traffic conditions, eliminating the need for expensive roadside sensor deployment while achieving comprehensive road network coverage through the natural movement of the vehicle fleet.
Solution Approach 2:
The probe vehicles serve multiple functions: they are normal operational vehicles for transportation while simultaneously acting as mobile sensor platforms for traffic data collection. This multi-functionality eliminates the need for dedicated sensing infrastructure, reducing deployment costs while achieving extensive road network coverage through the vehicles' existing operational routes.
3Loss of information
If sparse sensor data is used for congestion analysis, then some traffic information can be obtained, but actual speed changes for the traffic congestion may not be analyzed
Solution Approach 1:
The patent ensures continuous measurement of traffic parameters by having probe vehicles constantly record speed, location, and other relevant data during their normal operation. This continuous data collection captures actual speed changes as they occur, unlike periodic or event-triggered sampling that might miss transient congestion events. The continuous action of data collection by moving vehicles ensures no information is lost.
Solution Approach 2:
The system transitions from static roadside sensing to dynamic mobile sensing. Probe vehicles move with the traffic flow, enabling measurements that adapt to changing traffic conditions. This dynamic approach captures speed changes and congestion development in real-time as vehicles experience them, providing accurate information about actual traffic dynamics rather than inferred conditions.
Data Source
AI summary
A system, a method, and a computer program product may be provided for generating traffic congestion data for a road in a region. The system may include a memory configured to store computer executable instructions and a processor configured to execute the computer executable instructions to obtain probe data and map data. The processor may be further configured to generate traffic condition data for the road. The processor may be further configured to determine speed changes data associated with one or more vehicles. The processor may be further configured to calculate congestion length, time period, congestion speed for the one or more vehicles to reach a non-congestion state from a congestion state. The processor may be further configured to generate the traffic congestion data, based on the speed changes data, congestion length, a time period and congestion speed associated with the one or more vehicles on the road.