Generic Approaches to Estimating Freeway Traffic State and Percentage of Connected Vehicles With Fixed and Mobile Sensing

Mingming Zhao; Claudio Roncoli; Yibing Wang; Nikolaos Bekiaris-Liberis; Jingqiu Guo; Senlin Cheng

doi:10.1109/TITS.2021.3121181

Generic Approaches to Estimating Freeway Traffic State and Percentage of Connected Vehicles With Fixed and Mobile Sensing

Mingming Zhao, Claudio Roncoli, Yibing Wang^*, Nikolaos Bekiaris-Liberis, Jingqiu Guo^*, Senlin Cheng

^*Corresponding author for this work

Research output: Contribution to journal › Article › Scientific › peer-review

15 Citations (Scopus)

Abstract

Three filtering-based approaches to freeway traffic state estimation are studied using measurements from connected vehicles and also a minimum number of fixed detectors. These approaches are: Method 1 based on EKF and the second-order traffic flow model METANET, Methods 2 and 3 based on KF and the conservation equation that is driven by mean speed data of connected vehicles under a speed-uniformity assumption. Each method is capable of estimating segment traffic flow variables (speeds, densities, and flows) as well as segment market penetration rates (MPRs) of connected vehicles. The three methods are evaluated and compared in depth using NGSIM data with respect to their traffic state estimator design, data requirements, capabilities, limitations in the mixed sensing case. Recommendations are given about the choice of methods over the range of MPR.

Original language	English
Pages (from-to)	13155-13177
Number of pages	23
Journal	IEEE Transactions on Intelligent Transportation Systems
Volume	23
Issue number	8
Early online date	15 Dec 2021
DOIs	https://doi.org/10.1109/TITS.2021.3121181
Publication status	Published - Aug 2022
MoE publication type	A1 Journal article-refereed

Keywords

Computational modeling
connected vehicles
Connected vehicles
Data models
filtering
Freeway traffic state estimation
market penetration rate
Mathematical models
mixed sensing
Real-time systems
Sensors
speed-uniformity assumption.
Traffic control
traffic flow modelling

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10.1109/TITS.2021.3121181

Cite this

@article{5119a94100d0442090a6551f7955b343,

title = "Generic Approaches to Estimating Freeway Traffic State and Percentage of Connected Vehicles With Fixed and Mobile Sensing",

abstract = "Three filtering-based approaches to freeway traffic state estimation are studied using measurements from connected vehicles and also a minimum number of fixed detectors. These approaches are: Method 1 based on EKF and the second-order traffic flow model METANET, Methods 2 and 3 based on KF and the conservation equation that is driven by mean speed data of connected vehicles under a speed-uniformity assumption. Each method is capable of estimating segment traffic flow variables (speeds, densities, and flows) as well as segment market penetration rates (MPRs) of connected vehicles. The three methods are evaluated and compared in depth using NGSIM data with respect to their traffic state estimator design, data requirements, capabilities, limitations in the mixed sensing case. Recommendations are given about the choice of methods over the range of MPR.",

keywords = "Computational modeling, connected vehicles, Connected vehicles, Data models, filtering, Freeway traffic state estimation, market penetration rate, Mathematical models, mixed sensing, Real-time systems, Sensors, speed-uniformity assumption., Traffic control, traffic flow modelling",

author = "Mingming Zhao and Claudio Roncoli and Yibing Wang and Nikolaos Bekiaris-Liberis and Jingqiu Guo and Senlin Cheng",

note = "Publisher Copyright: IEEE",

year = "2022",

month = aug,

doi = "10.1109/TITS.2021.3121181",

language = "English",

volume = "23",

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journal = "IEEE Transactions on Intelligent Transportation Systems",

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AU - Zhao, Mingming

AU - Roncoli, Claudio

AU - Wang, Yibing

AU - Bekiaris-Liberis, Nikolaos

AU - Guo, Jingqiu

AU - Cheng, Senlin

N1 - Publisher Copyright: IEEE

PY - 2022/8

Y1 - 2022/8

N2 - Three filtering-based approaches to freeway traffic state estimation are studied using measurements from connected vehicles and also a minimum number of fixed detectors. These approaches are: Method 1 based on EKF and the second-order traffic flow model METANET, Methods 2 and 3 based on KF and the conservation equation that is driven by mean speed data of connected vehicles under a speed-uniformity assumption. Each method is capable of estimating segment traffic flow variables (speeds, densities, and flows) as well as segment market penetration rates (MPRs) of connected vehicles. The three methods are evaluated and compared in depth using NGSIM data with respect to their traffic state estimator design, data requirements, capabilities, limitations in the mixed sensing case. Recommendations are given about the choice of methods over the range of MPR.

AB - Three filtering-based approaches to freeway traffic state estimation are studied using measurements from connected vehicles and also a minimum number of fixed detectors. These approaches are: Method 1 based on EKF and the second-order traffic flow model METANET, Methods 2 and 3 based on KF and the conservation equation that is driven by mean speed data of connected vehicles under a speed-uniformity assumption. Each method is capable of estimating segment traffic flow variables (speeds, densities, and flows) as well as segment market penetration rates (MPRs) of connected vehicles. The three methods are evaluated and compared in depth using NGSIM data with respect to their traffic state estimator design, data requirements, capabilities, limitations in the mixed sensing case. Recommendations are given about the choice of methods over the range of MPR.

KW - Computational modeling

KW - connected vehicles

KW - Connected vehicles

KW - Data models

KW - filtering

KW - Freeway traffic state estimation

KW - market penetration rate

KW - Mathematical models

KW - mixed sensing

KW - Real-time systems

KW - Sensors

KW - speed-uniformity assumption.

KW - Traffic control

KW - traffic flow modelling

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DO - 10.1109/TITS.2021.3121181

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SN - 1524-9050

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EP - 13177

JO - IEEE Transactions on Intelligent Transportation Systems

JF - IEEE Transactions on Intelligent Transportation Systems

IS - 8

ER -

Generic Approaches to Estimating Freeway Traffic State and Percentage of Connected Vehicles With Fixed and Mobile Sensing

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Keywords

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ULTRA: Ubiquitous Localization, communication, and sensing infrastrucTuRe for Autonomous systems

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Generic Approaches to Estimating Freeway Traffic State and Percentage of Connected Vehicles With Fixed and Mobile Sensing

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