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This paper frames recent publications from Waymo within the broader context of the safety readiness determination for an Automated Driving System (ADS). Starting from a brief overview of safety performance outcomes reported by Waymo (i.e.,…
From biotechnology to cyber-risks, most extreme technological risks cannot be reliably estimated from historical statistics. Therefore, engineers resort to predictive methods, such as fault/event trees in the framework of probabilistic…
In recent years, car makers and tech companies have been racing towards self driving cars. It seems that the main parameter in this race is who will have the first car on the road. The goal of this paper is to add to the equation two…
The advancement of safety-critical research in driving behavior in ADAS-equipped vehicles require real-world datasets that not only include diverse traffic scenarios but also capture high-risk edge cases such as near-miss events and system…
Real-time safety metrics are important for the automated driving system (ADS) to assess the risk of driving situations and to assist the decision-making. Although a number of real-time safety metrics have been proposed in the literature,…
We present BADAS-2.0, the second generation of our collision anticipation system, building on BADAS-1.0, which showed that fine-tuning V-JEPA2 on large-scale ego-centric dashcam data outperforms both academic baselines and production ADAS…
Safety is a central requirement for automated vehicles. As such, the assessment of risk in automated driving is key in supporting both motion planning technologies and safety evaluation. In automated driving, risk is characterized by two…
Driver assistance systems, also called automated driving systems, allow drivers to immerse themselves in non-driving-related tasks. Unfortunately, drivers may not trust the automated driving system, which prevents either handing over the…
In light of the recent humongous growth of the human population worldwide, there has also been a voluminous and uncontrolled growth of vehicles, which has consequently increased the number of road accidents to a large extent. In lieu of a…
Vehicles with a safety function for anticipating crashes in advance can enhance drivers' ability to avoid crashes. As dashboard cameras have become a low-cost sensor device accessible to almost every vehicle, deep neural networks for crash…
As autonomous vehicles have benefited the society, understanding the dynamic change of humans' trust during human-autonomous vehicle interaction can help to improve the safety and performance of autonomous driving. We designed and conducted…
Automated Vehicles (AV) hold potential to reduce or eliminate human driving errors, enhance traffic safety, and support sustainable mobility. Recently, crash data has increasingly revealed that AV behavior can deviate from expected safety…
Traffic incidents remain a critical public safety concern worldwide, with Australia recording 1,300 road fatalities in 2024, which is the highest toll in 12 years. Similarly, the United States reports approximately 6 million crashes…
Urban traffic safety is a pressing concern in modern transportation systems, especially in rapidly growing metropolitan areas where increased traffic congestion, complex road networks, and diverse driving behaviors exacerbate the risk of…
Timely and accurate conflict event data are essential for real-time monitoring, forecasting, and policy response. Yet near-real-time conflict datasets such as the Armed Conflict Location \& Event Data Project (ACLED) are subject to…
When autonomous robots interact with humans, such as during autonomous driving, explicit safety guarantees are crucial in order to avoid potentially life-threatening accidents. Many data-driven methods have explored learning probabilistic…
Autonomous vehicles (AVs) are envisioned to revolutionize our life by providing safe, relaxing, and convenient ground transportation. The computing systems in such vehicles are required to interpret various sensor data and generate…
This paper develops a test scenario specification procedure using crash sequence analysis and Bayesian network modeling. Intersection two-vehicle crash data was obtained from the 2016 to 2018 National Highway Traffic Safety Administration…
In recent years, automotive technology has made a steady progress. In particular, Advanced Driver Assistance System (ADAS) has enabled many safety features in commercial vehicles, for instance, pedestrian detection, lane keeping assist,…
In the automotive industry there is a need to handle broad quality deficiencies, eg, performance, maintainability, cybersecurity, safety, and privacy, to mention a few. The idea is to prevent these issues from reaching end-users, ie, road…