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

With the trend of global warming and destructive human activities, the frequent occurrences
of catastrophes have posed devastating threats to human life and social stability worldwide …

In recent times, hurricanes Matthew, Harvey, and Irma have disrupted the lives of millions of
people across multiple states in the United States. Under hurricane evacuation, efficient …

We present a physics-informed deep learning (PIDL) approach to tackle the challenge of
data sparsity and sensor noise in traffic state estimation (TSE). PIDL strengthens a deep …

Proactive evacuation traffic management largely depends on real-time monitoring and
prediction of traffic flow at a high spatiotemporal resolution. However, evacuation traffic …

Ensuring safer mobility for evacuee drivers during a hurricane evacuation has always been
a major concern for traffic managers. That concern has grown further, particularly after recent …

Natural hazards, such as wildfires, pose a significant threat to communities worldwide. Real-
time forecasting of travel demand during wildfire evacuations is crucial for emergency …

Noise is inevitable in the collection of traffic data, which may cause accuracy and stability
issues in smart mobility applications. In the literature, most of the existing studies on traffic …

Artificial intelligence (AI) can improve operational processes by utilizing faster computational
capabilities, data, and innovative algorithms. This article reviews the latest research on the …

Optimal traffic control and signal planning can significantly reduce traffic congestion and
potential delays at intersections. However, a major challenge to optimize traffic signal timing …