In this study, the predictive power of three different machine learning (ML)-based
approaches, namely, multi-gene genetic programming (MGGP), M5 model trees (M5Tree) …

Traffic accidents on urban roads are a major cause of death despite the development of
traffic safety measures. However, the prediction of casualties in urban road traffic accidents …

Background There has been an increased focus on active transport, but the measurement of
active transport is still difficult and error-prone. Sensor data have been used to predict active …

As a first step towards decreasing greenhouse gas emissions originating from
transportation, it is critical that we create efficient systems for monitoring individual travel …

Forecasting travel demand requires a grasp of individual decision-making behavior.
However, transport mode choice (TMC) is determined by personal and contextual factors …

Commercial vehicles have a significant economic effect by moving goods and services
across national borders and around the globe. They are also responsible for most …

The culture of active transportation (walking or cycling) in the Kingdom of Saudi Arabia
(KSA) is less prevalent than in other societies. This study aims to understand the perceptions …

This work presents a novel transportation mode detection algorithm that handles the
recognition of kick-scooters. In 2015, 10 minutes of data from a kick-scooter were considered …

Abstract Human Activity Recognition (HAR) within the context of transportation mode
detection represents a dynamic and essential area of research, reflecting its pivotal role in …

Most transportation mode (ie, train, car) identification methods can only recognize the
activities that were previously seen in the training data. However, they cannot be able to …