A joint and simultaneous prediction framework of weekday and weekend daily-activity travel pattern using conditional dependency networks
Daily activity pattern (DAP) prediction models within the Activity-based Modelling paradigm
are being currently developed without adequate consideration of the various …
are being currently developed without adequate consideration of the various …
Comparative Analysis of Parametric and Non-Parametric Data-Driven Models to Predict Road Crash Severity among Elderly Drivers Using Synthetic Resampling …
As the global elderly population continues to rise, the risk of severe crashes among elderly
drivers has become a pressing concern. This study presents a comprehensive examination …
drivers has become a pressing concern. This study presents a comprehensive examination …
[HTML][HTML] Spatiotemporal features of traffic help reduce automatic accident detection time
Quick and reliable automatic detection of traffic accidents is of paramount importance to
save human lives in transportation systems. However, automatically detecting when …
save human lives in transportation systems. However, automatically detecting when …
Robust spatiotemporal crash risk prediction with gated recurrent convolution network and interpretable insights from SHapley additive explanations
MT Kashifi - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
The vigorous progress in artificial intelligence and the widespread availability of computing
power and big data have resulted in remarkable achievements in applying deep learning …
power and big data have resulted in remarkable achievements in applying deep learning …
Determining causality in travel mode choice
This article presents one of the pioneering studies on causal modeling in travel mode choice
decision-making using causal discovery algorithms. These models are a major …
decision-making using causal discovery algorithms. These models are a major …
Causation versus Prediction: Comparing Causal Discovery and Inference with Artificial Neural Networks in Travel Mode Choice Modeling
This study compares the performance of a causal and a predictive model in modeling travel
mode choice in three neighborhoods in Chicago. A causal discovery algorithm and a causal …
mode choice in three neighborhoods in Chicago. A causal discovery algorithm and a causal …
Bridging conventional and proactive approaches for road safety analytic modeling and future perspectives
For many years, research has been primarily focused on enhancing our understanding of
the factors that impact the probability of vehicle crashes. The evaluation of safety has …
the factors that impact the probability of vehicle crashes. The evaluation of safety has …
[HTML][HTML] Determining causality in travel mode choice
This article presents one of the pioneering studies on causal modeling in travel mode choice
decision-making using causal discovery algorithms. These models are a major …
decision-making using causal discovery algorithms. These models are a major …
Performance trade offs in IoT-based traffic monitoring and incident detection systems
Traffic monitoring systems are fundamental for making roads safer and more efficient. Newly
proposed traffic monitoring systems enable the use of IoT devices to monitor traffic in a cost …
proposed traffic monitoring systems enable the use of IoT devices to monitor traffic in a cost …
Accident Forecasting using IoT and Deep Learning Techniques
AR Paul, EGM Kanaga - 2023 Second International …, 2023 - ieeexplore.ieee.org
Road accidents are a major cause of injury and death worldwide, and there is a need for
accurate and proactive accident prevention measures. In recent years, Internet of Things …
accurate and proactive accident prevention measures. In recent years, Internet of Things …