The inevitable upcoming technology of autonomous vehicles (AVs) will affect our cities and
several aspects of our lives. The widespread adoption of AVs repose at crossing distinct …

Convolutional neural networks are a promising tool for solving the problem of pattern
recognition. Most well-known convolutional neural networks implementations require a …

The most salient problems of transit vehicle service in Latin American intermediate cities
include: the high number of passengers involved in traffic accidents; traffic congestion …

Vehicle detection and classification are the most significant and challenging activities of an
intelligent traffic monitoring system. Traditional methods are highly computationally …

Vehicle identification and classification are essential for Intelligent Transportation Systems,
although current approaches may face challenges due to data collection discrepancies. This …

Optimal operation configuration of a Wireless Sensor Network (WSN) can be determined by
utilizing exact mathematical programming techniques such as Mixed Integer Programming …

In direct line with the evolution of technology, but also with the density of vehicles that create
congestion and often road accidents, traffic monitoring systems are parts that integrate …

Convolutional neural networks (CNNs) represent deep learning architectures that are
currently used in a wide range of applications, including computer vision, speech …

Anthropogenic is defined as one of the influencing factors of the climatic phenomenon,
called Urban Heat Island (UHI), in which urban areas have higher air temperatures than …

The rapid increase in population has increased the traffic density in urban areas. In current
scenario, the major challenges faced by transportation systems are congestion, accidents …