Data-driven transfer learning framework for estimating on-ramp and off-ramp traffic flows

X Ma, A Karimpour, YJ Wu - Journal of Intelligent Transportation …, 2024 - Taylor & Francis
To develop the most appropriate control strategy and monitor, maintain, and evaluate the
traffic performance of the freeway weaving areas, state and local Departments of …

An automatic image processing algorithm based on crack pixel density for pavement crack detection and classification

N Safaei, O Smadi, A Masoud, B Safaei - International Journal of …, 2022 - Springer
Nowadays, there is a massive necessity to develop fully automated and efficient distress
assessment systems to evaluate pavement conditions with the minimum cost. Due to having …

Understanding how relationships between crash frequency and correlates vary for multilane rural highways: Estimating geographically and temporally weighted …

A Mohammadnazar, I Mahdinia, N Ahmad… - Accident Analysis & …, 2021 - Elsevier
Abstract Safety Performance Functions (SPFs) are critical tools in the management of
highway safety projects. SPFs are used to predict the average number of crashes per year at …

[HTML][HTML] A dynamic approach to predict travel time in real time using data driven techniques and comprehensive data sources

H Taghipour, AB Parsa, AK Mohammadian - Transportation Engineering, 2020 - Elsevier
Having access to accurate travel time is of great importance for both highway network users
and traffic engineers. The travel time which is currently reported on highways is usually …

Estimating cycle-level real-time traffic movements at signalized intersections

N Mahmoud, M Abdel-Aty, Q Cai… - Journal of intelligent …, 2022 - Taylor & Francis
Real-time traffic movements at intersections is vital for transportation and traffic engineering.
It helps in providing intersection traffic data and optimizing signal control plans. This study …

A deep learning model for off-ramp hourly traffic volume estimation

A Nohekhan, S Zahedian… - Transportation Research …, 2021 - journals.sagepub.com
This paper addresses estimation of traffic volume of freeway off-ramps. Freeways are the
transportation network's main corridors, serving a large portion of the traffic volume. This …

A new framework for regional traffic volumes estimation with large-scale connected vehicle data and deep learning method

S Khadka, PS Wang, PT Li, FJ Torres - Journal of Transportation …, 2023 - ascelibrary.org
Connected vehicle (CV) data in this paper refer to the in-vehicle telematic data, including
trajectories and driving events (eg, hard braking) collected by vehicle manufacturers when …

Identifying the Impact Area of a Traffic Event Through k-Means Clustering

S Mamdoohi, E Miller-Hooks - Journal of big data analytics in …, 2022 - Springer
Nonrecurring traffic events, including improvement actions and vehicular accidents, cause
traffic congestion and travel delay. The impact of a traffic event, even when the event is …

Machine learning and reverse methods for a deeper understanding of public roadway improvement action impacts during execution

S Mamdoohi, E Miller-Hooks - Journal of Advanced …, 2022 - Wiley Online Library
The execution of public roadway maintenance, rehabilitation, and restoration activities
disturb normal traffic flows, resulting in roadway capacity reduction, inducing travel time …

Discrete wavelet transform application for bike sharing system check-in/out demand prediction

Y Chen, W Wang, X Hua, W Yu, J Xiao - Transportation Letters, 2024 - Taylor & Francis
The rebalancing of bikes and demand prediction at the station level plays a fundamental
role in the regular operation and maintenance of bike-sharing systems (BSSs). In this paper …