An integrated modeling framework for active traffic management and its applications in the Washington, DC area

Xiong, Chenfeng; Yang, Xianfeng; Zhang, Lei; Lee, Minha; Zhou, Weiyi; Raqib, Mohammed

doi:10.1080/15472450.2021.1878891

Cited by 8 publications

(2 citation statements)

References 27 publications

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“…Such a system includes consideration of peak-hour traffic, the detection of and response to incidents, and the reduction of waiting time due to congestion and incidents. Thus the system enhances the local transportation network performance in terms of safety, efficiency, reliability, scalability, and sustainability [128].…”

Section: A Local Scalementioning

confidence: 99%

Street Smart in 5G: Vehicular Applications, Communication, and Computing

et al. 2022

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Recent advances in information technology have revolutionized the automotive industry, paving the way for next-generation smart vehicular mobility. Specifically, vehicles, roadside units, and other road users can collaborate to deliver novel services and applications that leverage, for example, big vehicular data and machine learning. Relatedly, fifth-generation cellular networks (5G) are being developed and deployed for low-latency, high-reliability, and high bandwidth communications. While 5G adjacent technologies such as edge computing allow for data offloading and computation at the edge of the network thus ensuring even lower latency and context-awareness. Overall, these developments provide a rich ecosystem for the evolution of vehicular applications, communications, and computing. Therefore in this work, we aim at providing a comprehensive overview of the state of research on vehicular computing in the emerging age of 5G and big data. In particular, this paper highlights several vehicular applications, investigates their requirements, details the enabling communication technologies and computing paradigms, and studies data analytics pipelines and the integration of these enabling technologies in response to application requirements.

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Section: A Local Scalementioning

confidence: 99%

Street Smart in 5G: Vehicular Applications, Communication, and Computing

et al. 2022

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“…Examples of these active traffic management (ATM) systems and transportation systems management and operations (TSMO) strategies include ramp metering, queue warning, variable speed limits, smart work zones, methods for incident management, and automatic road enforcement. (1)(2)(3)(4). The general goals of these systems are to improve safety on a microscopic level and to reduce congestion at the macroscopic level.…”

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confidence: 99%

Data-Driven Evaluation Methodology for Active Traffic Management Systems Utilizing Sparse Speed Data

Robbennolt

Hourdos

2023

Transportation Research Record: Journal of the Transportation R

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Many active traffic management systems and transportation systems management and operations strategies have been evaluated for safety based on crash reduction over time. These long-term studies are effective in showing the safety benefits of new systems, but do not often quantify other factors such as travel time, the extent of congestion, or the environmental impacts. Building on previous research into spatiotemporal interpolation of speed data, this methodology developed a mathematical representation of the speed and acceleration potential of the traffic stream given the sparse speed data from point sensors. This high-resolution estimate of traffic state could be used to construct trajectories of vehicles the could include data on vehicle speed and acceleration at each location in space and point in time. This methodology is general, and the trajectories could be used to evaluate traffic flow in several different ways. In the case study provided, trajectories were used to evaluate the ability of a queue warning algorithm to detect and warn drivers about unsafe conditions. Other potential applications include utilizing these trajectories to calculate fuel consumption, travel times, and speed variability to determine how new systems affect fundamental traffic characteristics.

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Enhancing multi-scenario applicability of freeway variable speed limit control strategies using continual learning

Zhang,

Xu,

et al. 2024

Accident Analysis & Prevention

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An integrated modeling framework for active traffic management and its applications in the Washington, DC area

Cited by 8 publications

References 27 publications

Street Smart in 5G: Vehicular Applications, Communication, and Computing

Street Smart in 5G: Vehicular Applications, Communication, and Computing

Data-Driven Evaluation Methodology for Active Traffic Management Systems Utilizing Sparse Speed Data

Enhancing multi-scenario applicability of freeway variable speed limit control strategies using continual learning

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