Assessing Connected Vehicle Data Coverage on New Jersey Roadways

TL;DR

This study evaluates the coverage and temporal resolution of Wejo connected vehicle data in New Jersey, finding consistent but low market penetration that could still support various traffic analytics applications.

Contribution

It provides an assessment of Wejo vehicle movement data coverage and temporal consistency across New Jersey roadways, informing its potential for transportation analytics.

Findings

Market penetration rates are below 5% across road types.

Temporal resolution is consistent across locations.

Data shows uniform spatial distribution of equipped vehicles.

Abstract

The connected vehicle data (CVD) is one of the most promising emerging mobility data that greatly increases the ability to effectively monitor transportation system performance. A commercial vehicle trajectory dataset was evaluated for market penetration and coverage to establish whether it represents a sufficient sample of the vehicle volumes across the statewide roadway network of New Jersey. The dataset (officially named Wejo Vehicle Movement data) was compared to the vehicle volumes obtained from 46 weight-in-motion (WIM) traffic count stations during the corresponding two-month period. The observed market penetration rates of the Movement data for the interstate highways, non-interstate expressways, major arterials, and minor arterials are 2.55% (std. dev. 0.76%), 2.31% (std. dev. 1.07%), 3.25% (standard deviation 1.48%), and 4.39% (standard deviation 2.65%), respectively. Additionally, the temporal resolution of the dataset (i.e., the time interval between consecutive Wejo vehicle trips captured at a given roadway section, time-of-day variation, day-of-month variation) was also found to be consistent among the evaluated WIM locations. Although relatively low (less than 5%), the consistent market penetration, combined with uniform spatial distribution of equipped vehicles within the traffic flow, could enable or enhance a wide range of traffic analytics applications.