Developing Novel Performance Measures for Traffic Congestion Management and Operational Planning Based on Connected Vehicle Data

Journal Article · 31 May 2022 · Journal of Urban Planning and Development

DOI: https://doi.org/10.1061/(asce)up.1943-5444.0000835 · OSTI ID:1855584

Khadka, Swastik  ^[1]; Li, Pengfei “Taylor”  ^[1]; Wang, Qichao  ^[2]

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1. Univ. of Texas, Arlington, TX (United States)
2. National Renewable Energy Lab. (NREL), Golden, CO (United States)

In this study, the authors present their efforts in exploring a new type of traffic data, referred to as internet-connected vehicle (ICV) data, for traffic congestion management and operational planning. Most currently manufactured vehicles contain onboard GPS and cellular modules, and they constantly connect to automobile manufacturers' clouds via cellular networks and upload their status. Some automobile manufacturers have recently redistributed the nonpersonal part of such data, such as geolocation, to third-party organizations for innovative applications. Compared with the traditional vehicle GPS data, the ICV data contain high-resolution GPS waypoints accompanied with the vehicles' abnormal moving events (e.g., hard braking). The ICV data also have huge potential in congestion management and operational planning. They explore to identify and analyze traffic congestion on both freeways and arterials using the ICV data. The ICV data adopted for this research are redistributed by Wejo Data Service, representing 10%-15% of all moving vehicles in the Dallas-Fort Worth (DFW) area in Texas. Through one case study for a freeway segment and one for an arterial segment, new traffic performance metrics based on the characteristics of ICV data have been presented. The highlights of these efforts are as follows: (I) queue length and propagation at freeway bottlenecks can be directly measured based on where and when most internet-connected vehicles slow down and join the queue; (II) an internet-connected vehicle's actual delay time on arterials can be directly measured according to its slow movement percentage, without assuming the nondelay travel speed; and (III) the ICV data set are also combined with the high-resolution traffic signal events to generate a ground-truth time-space diagram (TSD) on arterials - a common visualization of arterial signal performance for transportation planning and operations.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE); U.S. Department of Transportation (DOT), UTC Center, Center for Transportation Equity, Decisions, and Dollars (CTEDD)
• Grant/Contract Number: AC36-08GO28308
• OSTI ID: 1855584
• Report Number(s): NREL/JA-2C00-81377; MainId:82150; UUID:0f921728-09f2-41a9-882d-73b19d31bcaa; MainAdminID:64057
• Journal Information: Journal of Urban Planning and Development, Journal Name: Journal of Urban Planning and Development Journal Issue: 2 Vol. 148; ISSN 0733-9488
• Publisher: American Society of Civil Engineers (ASCE)Copyright Statement
• Country of Publication: United States
• Language: English