AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
OBJECTIVE While comparative studies have shown that human crash risk is higher at night, especially during the weekend, it has been difficult to quantify crash rates by these temporal dimensions due to a lack of human exposure data, namely vehicle miles traveled (VMT). The objective of this study was to integrate a nov...
This work proposes a 14-dimension highway driving behavioral taxonomy and builds an automated framework to compare naturalistic driving datasets from China and Germany, with every contrast computed within matched traffic states.
Findings supporting a shift from quantity-oriented augmentation to credibility-aware sample acceptance for ADS safety prediction and risk governance support a shift from quantity-oriented augmentation to credibility-aware sample acceptance.
This framework outlines a potential pathway for advancing DSM technology toward more proactive and personalized intelligent assistance, while acknowledging that realizing this transition will require sustained interdisciplinary effort.
Connected-vehicle telemetry for crash-risk reduction and road safety refers to the collection, transmission, and analysis of data from vehicles and roadside sensing to monitor traffic conditions, detect imminent hazards, and support proactive safety interventions within intelligent transportation systems (ITS). By coup...
Third-party evaluations of autonomous vehicle (AV) safety can play a vital role in improving public acceptance, building consumer confidence, and establishing effective safety standards. In Part I of this study, we propose a dedicated third-party testing initiative for systematically evaluating AV behavioral safety. In...
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