As an effective public transportation system, a Shared Taxi Mobility-on-Demand (STMoD) provides passengers with door-to-door shared taxi service. This study proposes a dynamic occupancy rate rebalancing approach with centralised dispatching for …

This study examines how buffer time impacts the behaviors of 20 young drivers in terms of takeover duration and quality, visual attention and cognitive effort, and emotional states preceding, during, and subsequent to take over requests (TORs) …

This study introduces a novel model aimed at identifying traffic congestion, accidents, and other irregularities within transportation networks by leveraging a combination of unsupervised machine learning techniques and statistical models applied …

Accurate arrival time predictions for bus services significantly enhance their usability, reducing wait times and increasing user satisfaction, which in turn encourages public transport use. In densely populated and developing countries, such as …

Usage-Based Insurance (UBI) revolutionizes traditional coverage by utilizing technology to tailor insurance premiums to individual driving behaviour. Road rage and Aggressive driving behaviour Detection (RAD) is pivotal for enhancing the precision …

Traffic data plays an essential role in Intelligent Transportation Systems (ITS) and offers numerous advantages, including efficient traffic control and system performance improvement. However, due to the scarcity of data collection systems …

This paper describes a graph-based methodology for analysing and optimising road networks that combines traditional algorithms, AI search, and a learning algorithm. The primary goal is to find the shortest and most efficient paths between vertices …

Traffic prediction is a task where the goal is to determine the number and type of vehicles, or some other traffic related metric, at certain time point. In addition to predicting the short-term evolution of traffic, prediction can be done for …

Edge computing is used in intelligent transportation systems to handle data faster and with less delay. Implementing the proposed system in edge computing improves security in intelligent transportation systems. Video surveillance has played an …

Vehicle-to-Everything (V2X) infrastructure generates a vast amount of data from sensor-equipped vehicles and road infrastructure. The availability of such data provides new opportunities to explore and understand drivers' behaviors in diverse …

This study addresses the lack of computer vision techniques for counting traffic at motorcycle-dominated intersections by developing an integrated framework. Three models are proposed: a detection model with a large visual dataset, a tracking …

This research showcases the innovative integration of Large Language Models into machine learning workflows for traffic incident management, focusing on the classification of incident severity using accident reports. By leveraging features …

The trajectory and motion prediction of autonomous vehicles stands as a pivotal element in guaranteeing the safety and effectiveness of self-driving systems. Yet, current models frequently encounter challenges in providing precise forecasts of the …

Heavy braking is a common driving behaviour that indicates a possible traffic hazard. To avoid traffic accidents, detecting and predicting braking events are essential to inform the driver to take action beforehand. Recently, machine learning …

Moving towards sustainable transportation is essential in mitigating environmental effects and achieving worldwide sustainability targets. Explore the impact of green mobility and sustainable transportation. This study investigates how the …

Anomaly detection is critical in Intelligent Transportation Systems (ITS) due to its significant impact on safety. This paper introduces a Bayesian probabilistic framework for identifying anomalous trajectories without explicitly modeling …

The emergence of autonomous vehicles (AVs) as a solution to various traffic externalities, including safety concerns such as crashes, has been promising. However, existing research primarily focuses on AVs plying in homogeneous traffic conditions …

Even though the number of motorcycle crash accidents in Japan has trended downward over the past decade, there persists a necessity to propose effective safety measures targeting factors associated with fatal crash accidents. Previous studies have …

With the rapid development of intelligent transportation systems, the amount of data is growing exponentially, which puts higher demands on real-time processing and storage of data. In view of the limitations of the traditional centralized data …

In torrential rain disasters, affected areas are identified through reporting and patrolling; however, traffic monitoring remains a challenge. This study establishes a traffic anomaly detection method during heavy rain disasters. Using probe …