Smart cities (SCs) are becoming highly sophisticated ecosystems at which innovative
solutions and smart services are being deployed. These ecosystems consider SCs as data …

The autonomous vehicles (AVs) in smart city, as intelligent mobile robots, are expected to
provide diversified services to facilitate the life of citizens. However, the attributes of the …

With the increasing presence of online social networks (OSN), there is a growing interest in
accurately predicting user behaviors based on the data collected from OSN. Unlike …

Traffic forecasting is essential in improving and maintaining safety and orderliness in
intelligent transportation systems (ITS). As a deep learning approach, graph neural networks …

Detecting dangerous driving behavior is of great significance for reducing the occurrence of
traffic accidents, and very challenging as it is affected by multiple factors. However, the …

A Sybil attacker is able to obtain more than one identities and disguise as multiple vehicles
in order to interfere the normal operations of the connected vehicle system (CVS). In this …

With the emergence of big geospatial data and the breakthrough of massive data
processing, taxi-sharing offers the public a novel transportation mode with high comfort but …

With the development of online social networks, user behavior prediction based on the data
collected from these social networks has attracted increasing attention. In heterogeneous …

With the advent of the newest emergency call mandates in US and Europe, with the
advances in cellular-based and WiFi-based localization solutions, and with the …

While vehicular federated learning (FL) systems can be used for various purposes including
traffic monitoring and people flow control, since the learning process involves a large variety …