A survey of methods and technologies for congestion estimation based on multisource data fusion

D Cvetek, M Muštra, N Jelušić, L Tišljarić - Applied Sciences, 2021 - mdpi.com
Traffic congestion occurs when traffic demand is greater than the available network capacity.
It is characterized by lower vehicle speeds, increased travel times, arrival unreliability, and …

Physics-informed neural networks for integrated traffic state and queue profile estimation: A differentiable programming approach on layered computational graphs

J Lu, C Li, XB Wu, XS Zhou - Transportation Research Part C: Emerging …, 2023 - Elsevier
This paper presents an integrated framework for physics-informed joint traffic state and
queue profile estimation (JSQE) on freeway corridors, utilizing heterogeneous data sources …

Traffic light optimization with low penetration rate vehicle trajectory data

X Wang, Z Jerome, Z Wang, C Zhang, S Shen… - Nature …, 2024 - nature.com
Traffic light optimization is known to be a cost-effective method for reducing congestion and
energy consumption in urban areas without changing physical road infrastructure. However …

Traffic state estimation near signalized intersections

H Maripini, A Khadhir, L Vanajakshi - Journal of Transportation …, 2023 - ascelibrary.org
The primary goal with which any transportation system is designed is to make efficient use of
the available infrastructure to achieve better level of service (LoS). However, LoS is …

Learning the max pressure control for urban traffic networks considering the phase switching loss

X Wang, Y Yin, Y Feng, HX Liu - Transportation Research Part C: Emerging …, 2022 - Elsevier
Previous studies have shown that the max pressure control is a throughput-optimal policy
that can stabilize the store-and-forward traffic network when the demand is within the …

Adaptive and multi-path progression signal control under connected vehicle environment

Q Wang, Y Yuan, XT Yang, Z Huang - Transportation Research Part C …, 2021 - Elsevier
Through wireless communications, enriched information from connected vehicles (CVs) can
describe traffic information near an intersection and would supplement a data source for an …

Uncertainty estimation of connected vehicle penetration rate

S Jia, SC Wong, W Wong - Transportation Science, 2023 - pubsonline.informs.org
Knowledge of the connected vehicle (CV) penetration rate is crucial for realizing numerous
beneficial applications during the prolonged transition period to full CV deployment. A recent …

Network-wide identification of turn-level intersection congestion using only low-frequency probe vehicle data

Z He, G Qi, L Lu, Y Chen - Transportation Research Part C: Emerging …, 2019 - Elsevier
Locating the bottlenecks in cities where traffic congestion usually occurs is essential prior to
solving congestion problems. Therefore, this paper proposes a low-frequency probe vehicle …

A general framework for combining traffic flow models and Bayesian network for traffic parameters estimation

S Wang, AUZ Patwary, W Huang - Transportation research part C …, 2022 - Elsevier
This work focuses on traffic parameters estimation based on trajectory data in an arterial
corridor with multiple signalized intersections. We develop a general framework that can …

Maximum likelihood estimation of probe vehicle penetration rates and queue length distributions from probe vehicle data

Y Zhao, W Wong, J Zheng… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Queue length estimation plays an important role in traffic signal control and performance
measures of signalized intersections. Traditionally, queue lengths are estimated by applying …