Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …

Social networks play a key role in providing a new approach to collecting information
regarding mobility and transportation services. To study this information, sentiment analysis …

The main aim of this study was to compare the performances of the hybrid approaches of
traditional bivariate weights of evidence (WoE) with multivariate logistic regression (WoE …

Crash Detection is essential in providing timely information to traffic management centers
and the public to reduce its adverse effects. Prediction of crash risk is vital for avoiding …

Traffic accident management is a critical issue for advanced intelligent traffic management.
The increasingly abundant crowdsourcing data and floating car data provide new support for …

The present study aims to develop an applicable, robust, and generalizable approach
building on the integration of machine learning classifiers into dust source susceptibility …

Intelligent Transportation Systems (ITSs) utilize a sensor network-based system to gather
and interpret traffic information. In addition, mobility users utilize mobile applications to …

Landslides and other disastrous natural catastrophes jeopardise natural resources, assets,
and people's lives. As a result, future resource management will necessitate landslide …

This paper intends to analyze the Light Detection and Ranging (Lidar) sensor performance
on detecting pedestrians under different weather conditions. Lidar sensor is the key sensor …

The prediction of short-term volatile traffic becomes increasingly critical for efficient traffic
engineering in intelligent transportation systems. Accurate forecast results can assist in …