Recent years have seen a significant amount of transportation data collected from multiple
sources including road sensors, probe, GPS, CCTV and incident reports. Similar to many …

Abstract In recent years, Intelligent Transportation Systems (ITS) have seen efficient and
faster development by implementing deep learning techniques in problem domains which …

The proper planning of rest periods in response to the availability of parking spaces at rest
areas is an important issue for haulage companies as well as traffic and road …

A traffic monitoring system is an integral part of Intelligent Transportation Systems (ITS). It is
one of the critical transportation infrastructures that transportation agencies invest a huge …

Automated pavement distresses detection using road images remains a challenging topic in
the computer vision research community. Recent developments in deep learning have led to …

Recent improvements in machine vision algorithms have led to closed-circuit television
(CCTV) cameras emerging as an important data source for determining of the state of traffic …

Vehicle Classification (VC) is a key element of Intelligent Transportation Systems (ITS).
Diverse ranges of ITS applications like security systems, surveillance frameworks, fleet …

To solve the demand for road damage object detection under the resource-constrained
conditions of mobile terminal devices, in this paper, we propose the YOLO-LWNet, an …

Activity-based modelling is a modern agent-based approach to travel demand modelling, in
which the transport demand is derived from the agent's needs to perform certain activities at …

Proactive traffic management is a subset of smart mobility applications in which traffic control
strategies are implemented in advance to respond to anticipated roadway conditions …