Safety

This article introduces the Pareto Control Barrier Function (PCBF) algorithm to maximize the inner safe set of dynamical systems under input constraints. Traditional Control Barrier Functions (CBFs) ensure safety by maintaining system trajectories within a safe set but often fail to account for realistic input constraints. To address this problem, we leverage the Pareto multi-task learning framework to balance competing objectives of safety and safe set volume. The PCBF algorithm is applicable to high-dimensional systems and is computationally efficient. We validate its effectiveness...

Middleware has emerged as an important architectural component in supporting distributed applications. The role of middleware is to present a unified programming model to application writers and to mask out problems of heterogeneity and distribution. Mobile sensors fall into the space of distributed systems that suffer from isolated data sources, heterogeneous communication infrastructure and varying application requirements. In this report, we provide a middleware architecture that addresses the needs of a distributed system made of mobile sensors in general and discuss the implementation...

Findings from previous studies indicate that a freeway traffic collision is more likely to occur in close physical proximity to the tail of a queue. The implication is that collision likelihood increases when drivers abruptly alter their trajectories (e.g., by decelerating or changing lanes) on encountering the queue. The implication is supported and bolstered with new and detailed data that were painstakingly extracted from two freeway stretches in California. These data show how the likelihood of collision increases as both the spatial and the temporal proximities to the tail of an...

The role that human capital and occupational factors play in influencing driver safety outcomes has gained increased attention from trucking firms and policy-makers. This paper examines the role of these factors, in addition to demographic factors, in influencing crash frequency at the driver level. A unique driver-level dataset from a large truckload firm collected over a period of 26 months is used for estimating regression models of crash counts. Based on estimates from a zero inflated Poisson regression model, results suggest that human capital and occupational factors, such as...