Improving safety at railway level crossings is an important issue for the Australian transport system. Governments, the rail industry and road organisations have tried a variety of countermeasures for many years to improve railway level crossing safe...
Computational intelligence and neuroscience
Feb 8, 2015
In recent years, research on vehicle network location service has begun to focus on its intelligence and precision. The accuracy of space-time information has become a core factor for vehicle network systems in a mobile environment. However, difficul...
This study examined workload classification models and their application in adaptive in-vehicle systems. A meta-analysis of 31 studies assessed how predictor types (e.g., physiological data), experimental settings (simulator vs. on-road), and device ...
Unprotected left turns present challenges to drivers, as they must manage potential conflicts at intersections, which requires a decision-making process different from that in other driving scenarios. While many studies have modeled human decision-ma...
Roundabout safety evaluation in non-lane-based, heterogeneous traffic conditions in low-middle-income countries brings challenges due to unavailable/unreliable crash data, thereby switching to the utilization of safety surrogates. This study employed...
Neural networks' insufficient interpretability can lead to unguaranteed Safety of the Intended Functionality (SOTIF) issues when perceptual results are not always met in autonomous driving applications. To address the safety shortcomings in the curre...
High-fidelity simulators and sensors are commonly used in research to create immersive environments for studying real-world problems. This setup records detailed data, generating large datasets. In driving research, a full-scale car model repurposed ...
Recent advancements in artificial intelligence (AI) and traffic sensing technologies provide significant opportunities for real-time crash risk forecasting. While forecasting based on historical crash data yields macroscopic insights into future cras...
Accurate risk identification is crucial for ensuring the safe operation of Host vehicles (HoVs) in environments shared with Neighboring vehicles (NeVs). Traditional risk identification mechanisms typically rely on large amounts of precise numerical d...
There are safety risks when drivers take over the control of autonomous driving vehicles, and reducing unnecessary takeovers is essential to improve driving safety. This study seeks to develop an interpretable system framework for collision risk pred...
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