Real-Time Driver Safety Scoring Through Inverse Crash Probability Modeling

arXiv:2603.14841 · cs.LG, cs.AI, cs.DC, cs.ET · Submitted 2026-03-16 · Read on arXiv

cs.LG, cs.AI, cs.DC, cs.ET

Submitted: 2026-03-16

Updated: 2026-09-08

Comments: 12 pages, published in the 2026 IEEE International Conference on Electro Information

Journal ref: 2026 IEEE International Conference on Electro Information Technology (eIT), pp. 1-12, 2026

DOI: 10.1109/eIT68936.2026.11670411

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Calibration — 20× in this paper · explained in 7 episodes
• AUC — 17× in this paper · explained in 2 episodes
• Ablation — 11× in this paper · explained in 1 episode
• Accuracy — 8× in this paper · explained in 1 episode
• Interpretability — 8× in this paper · explained in 15 episodes
• Ablation study — 5× in this paper · explained in 1 episode
• Random Forest — 5× in this paper
• Waymo Open Motion Dataset — 5× in this paper
• Core — 4× in this paper · explained in 2 episodes
• National Highway Traffic Safety Administration — 4× in this paper
• Feature Engineering — 3× in this paper · explained in 3 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• SHAP values — 2× in this paper · explained in 2 episodes
• World Health Organization — 2× in this paper
• Adaptation — 1× in this paper · explained in 1 episode
• Agentic System — 1× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Average Precision — 1× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Ensemble Learning — 1× in this paper · explained in 2 episodes
• External Validation — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Longitudinal Data — 1× in this paper · explained in 2 episodes
• NHTSA Crash Report Sampling System — 1× in this paper
• Robustness — 1× in this paper · explained in 5 episodes
• Shapley values — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks