Recently, the deep learning schemes have been well investigated for improving the driving
safety and efficiency in the transportation systems. In this paper, a probabilistic model …

Accidents caused by drivers who exhibit unusual behavior are putting road safety at ever-
greater risk. When one or more vehicle nodes behave in this way, it can put other nodes in …

In recent years, the rapid improvement of sensor and wireless communication technologies
powerfully impels the development of advanced cooperative driving systems, generating the …

The TrafficRiskClassifier model introduced in this study adopts an innovative approach that
incorporates migration learning, image classification, and self-supervised learning, aiming to …

This study aims to improve the accuracy of predicting the severity of traffic accidents by
developing an innovative traffic accident risk prediction model—StackTrafficRiskPrediction …

There is a growing interest in the development of smart environments through predicting the
behaviors of inhabitants of smart spaces in the recent past. Various smart services are …

abstract The TrafficRiskClassifier model introduced in this study adopts an innovative
approach that incorporates migration learning, image classification, and self-supervised …

In this paper we analyse several proposed context-aware system architectures and identify a
set of requirements for building a unifying architecture model that support the development …

Intelligent transport system is the new aspect of smart city design under the purview of digital
India. Conventional approaches like rerouting from congested paths, predictive control …

School zones are areas close to schools in which crossing vehicles represent a threat to
school children. Due to various reasons, drivers might not be aware that they are …