Is Third-Party Provided Travel Time Helpful to Estimate Freeway Performance Measures?

TL;DR

This study proposes a hybrid approach combining third-party probe data with traditional point detector data to improve the accuracy of freeway performance measures estimation, especially during high-demand scenarios.

Contribution

It introduces a novel data fusion framework that integrates third-party travel times with point detector data for better freeway performance assessment.

Findings

Fusing third-party and point detector data improves estimation accuracy.

The hybrid method outperforms traditional point detector-based estimates during peak demand.

Scenario analysis shows benefits are most significant during high traffic demand periods.

Abstract

Transportation agencies monitor freeway performance using various measures such as VMT (Vehicle Miles Traveled), VHD (Vehicle Hours of Delay), and VHT (Vehicle Hours Traveled). Public transportation agencies typically rely on point detector data to estimate these freeway performance measures. Point detectors, such as inductive loops cannot capture the travel time for a corridor, which can lead to inaccurate performance measure estimation. This research develops a hybrid method, which estimates of freeway performance measures using a mix of probe data from third-parties and data from traditional point detectors. Using a simulated I-210 model, the overall framework using multiple data sources is evaluated, and compared with the traditional point detector-based estimation method. In the traditional method, point speeds are estimated with the flow and occupancy values using the g-factors. Data from 5% of the total vehicle are used to generate the third-party vendor provided travel time data. The analysis is conducted for multiple scenarios, including peak and off-peak periods. Findings suggest that fusing data from both third-party vendors and point detectors can help estimate performance measures better, compared to the traditional method, in scenarios that have noticeable traffic demand on freeways.