Nowadays, machine learning (ML), which is one of the most rapidly growing technical tools,
is extensively used to solve critical challenges in various domains. Vehicular ad hoc network …

We investigates the performance of deep Convolutional Neural Network (CNN) for
recognizing highway traffic congestion state in surveillance camera images. Different from …

Transport sector of Pakistan is one of the highest fossil fuel consumption and carbon dioxide
(CO 2) emission sector. As a key user of fossil fuel energy, Pakistan's transport sector has …

Traffic congestion recognition is essential for road traffic condition monitoring and improving
transportation operation efficiency. Recent works have proposed using computer vision to …

Concerns about cybersecurity have increased along with the Internet of Things'(IoT)
exponential growth in recent years. Artificial intelligence (AI), which is used to create …

Traditional image-based traffic congestion estimation methods generally include two steps,
which first extract the vehicles from the surveillance images, then calculate the congestion …

In order to solve the problem of urban short-term traffic congestion and temporal and spatial
heterogeneity, it is important to scientifically delineate urban traffic congestion response …

Macroscopic fundamental diagram (MFD) characterizes a unimodal and low-scatter
relationship between traffic accumulation and trip completion rate for homogenous urban …

This paper qualitatively classifies the nodes of logistics system as logistics center and
distribution center. For planning a logistics center, the requirement of each demand point is …

This study developed a travel time congestion index (TTCI) keyed to the differences in actual
versus desired travel times for various types of roadways, and found that the TTCI is …