01659715

Component

https://doi.org/10.1177/0361198118773199

https://doi.org/10.1177/0361198118773199

Connected vehicle (CV) technologies are expected to have a significant influence on the investment decisions of transportation system management and operations (TSMO) in the near future. One of the potential applications is the use of CV data to support various TSMO processes. This study investigates the use of CV data as an alternative to existing data acquisition techniques in providing two critical functions to support TSMO: travel time estimation and incident detection. In support of this investigation, the study develops regression models to estimate the accuracy and reliability of travel time measurement and latency of incident detection as functions of the traffic demand level and the proportion of CV in the traffic stream. The developed regression models are used in conjunction with a prediction of CV proportions in future years to determine when the CV technology can provide sufficient data quality to replace existing data acquisition systems. The results can be used by TSMO programs and agencies to plan their investment in data acquisition alternatives in future years.

18-05941

English

pp 203-212

2018

Transportation Research Record: Journal of the Transportation Research Board

Print

References (41) ; Tables (3)

Accuracy; Connected vehicles; Data collection; Data quality; Estimating; Evaluation and assessment; Incident detection; Methodology; Regression analysis; Transportation system management; Travel time

Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting

TRIS, TRB, ATRI

Jan 8 2018 11:32AM

• A Comparative Analysis of Tree-Based Ensemble Methods for Detecting Imminent Lane Change Maneuvers in Connected Vehicle Environments
• A Comparative Study between Private-Sector and Automated Vehicle Identification System Data through Various Travel Time Reliability Measures
• A Latent Class Pattern Recognition and Data Quality Assessment of Non-Commute Long-Distance Travel in California
• Application of the “Foot-in-the-Door” Compliance Technique for Traveler Intercept Surveys
• Carsharing Trip Characteristic Analysis: Do Users Choose Carsharing Rather Than Taxi to Economize?
• Characteristics and Temporal Stability of Recurring Bottlenecks
• Closing the Loop: Improving Transit through Crowdsourced Information
• Cross-Vendor and Cross-State Analysis of GPS Probe Data Latency
• Discovering Regularity in Mobility Patterns to Identify Predictable Aggregate Supply for Ridesharing
• e-mission: An Open-Source, Smartphone Platform for Collecting Human Travel Data
• Enriching Activity-Based Models using Smartphone-Based Travel Surveys
• Exploring the Relationships between the Non-Work Trip Frequency and Accessibility Based on Mobile Phone Data
• Exploring the Spatial Dependence and Selection Bias of Double Parking Citations Data
• Factors Affecting Interview Duration in Web-Based Travel Surveys
• Identifying Temporal and Spatial Characteristics of Residents’ Trips from Cellular Signaling Data: Case Study of Beijing
• Integrated Incident Decision-Support using Traffic Simulation and Data-Driven Models
• Interstate Speed Profiles
• Is There a Limit to Adoption of Dynamic Ridesharing Systems? Evidence from Analysis of Uber Demand Data from New York City
• Network Level Clearance Assessment using LiDAR to Improve the Reliability and Efficiency of Issuing Over-Height Permits on Highways
• Performance Measures for Characterizing Regional Congestion using Aggregated Multi-Year Probe Vehicle Data
• Profiling Transport Network Company Activity using Big Data
• Reconstructing Vehicle Trajectories to Support Travel Time Estimation
• Resampling Methods for Estimating Travel Time Uncertainty: Application of the Gap Bootstrap
• Using National Performance Management Research Data Set for Corridor Performance Measures: A US-281N Corridor Case Study
• Wind Data Collection and Analysis of Topographical Features along a Highway for Traffic Safety Assessment Based on Mobile Mapping Technology