Applied Dynamics International (United States)

The Integrated Stribeck Friction Model (ISFM) is introduced and compared to the Dahl and LuGre friction models. The Dahl model achieves correct steady-state Coulomb friction but exhibits excess creep in its transient response. The LuGre model can represent an arbitrary Stribeck friction curve, yet also exhibits excess creep in its transient response and displays nonpassive behavior during velocity reversals. The ISFM represents an arbitrary Stribeck curve with a more realistic friction force and creep rate formulation. As a result, it achieves correct steady-state friction, and a realistic transient creep response while remaining passive under all conditions. A basic four-parameter representation of a Stribeck curve is provided for use with the ISFM, which is competitive with the representation typically used with the LuGre model. Unlike the Dahl and LuGre models, the ISFM is designed for compatibility with scenarios where the friction surfaces might lose contact with each other. A literature review indicates it is the simplest existing stateful friction model that remains well defined when contact loads are zero.

Older adults with dementia frequently exhibit hiding and hoarding behaviors resulting in item loss. In long-term care facilities (LTCFs), item loss negatively impacts quality of care and increases stress for both staff and residents. To evaluate the suitability and adaptability of a novel real-time location system (RTLS) tag technology in mitigating item loss within LTCFs to improve care and operational efficiency. 30 semi-structured interviews were conducted with long-term care staff members to assess the frequency and impact of item loss in LTCFs and to understand the adaptations needed to increase the RTLS technology's utility in settings that care for older adults. Findings reveal that the loss of personal belongings and facility-owned items remains a prevalent and persistent challenge in LTCFs. Respondents recognized the RTLS technology's potential to improve item tracking and alleviate the stress associated with item loss. However, significant adaptations to the technology are necessary to meet the specific needs of the LTCF environment. The study corroborates the need for item loss mitigation strategies in LTCFs. The proposed RTLS technology shows promise in addressing this need, with potential benefits for improving care quality and operational efficiency.

Trajectory planning in dynamic environments can be decomposed into two sub-problems: 1) planning a path to avoid static obstacles, 2) then planning a speed profile to avoid dynamic obstacles. This is also called path-speed decomposition. In this work, we present a novel approach to solve the first sub-problem, motion planning with static obstacles. From an optimization perspective, motion planning for autonomous vehicles can be viewed as non-convex constrained nonlinear optimization, which requires a good enough initial guess to start and is often sensitive to algorithm parameters. We formulate motion planning as convex spline optimization. The convexity of the formulated problem makes it able to be solved fast and reliably, while guaranteeing a global optimum. We then reorganize the constrained spline optimization into a recurrent formulation, which further reduces the computational time to be linear in the optimization horizon size. The proposed method can be applied to both trajectory generation and motion planning problems. Its effectiveness is demonstrated in challenging scenarios such as tight lane changes and sharp turns.

Type A acute aortic dissection (TAAAD) represents a surgical emergency requiring intervention regardless of time of day. Whether such a "evening effect" exists regarding outcomes for TAAAD has not been previously studied using a large registry data. Patients with TAAAD were identified from the International Registry of Acute Aortic Dissections (1996-2019). Outcomes were compared between patients undergoing operative repair during the daytime (D), defined as 8 am-5 pm, versus the evening (N), defined as 5 pm-8 am. Four thousand one-hundrd and ninety-seven surgically treated patients with TAAAD were identified, with 1824 patients undergoing daytime surgery (43.5%) and 2373 patients undergoing evening surgery (56.5%). Daytime patients were more likely to have undergone prior cardiac surgery (13.2% vs. 9.5%; p < .001) and have had a prior aortic dissection (4.8% vs. 3.4%; p = .04). Evening patients were more likely to have been transferred from a referring hospital (70.8% vs. 75.0%; p = .003). Daytime patients were more likely to undergo aortic valve sparing root procedures (23.3% vs. 19.2%; p = .035); however, total arch replacement was performed with equal frequency (19.4% vs. 18.8%; p = .751). In-hospital mortality (D: 17.3% vs. N. 16.2%; p = .325) was similar between both groups. Subgroup analysis examining the effect of weekend presentation revealed no significant mortality difference. A majority of TAAAD patients underwent surgical repair at night. There were higher rates of postoperative tamponade in evening patients; however, mortality was similar. The expertise of cardiac-dedicated operative and critical care teams regardless of time of day as well as training paradigms may explain similar mortality outcomes in this high risk population.

Future self-driving cars and current ones with advanced driver assistance systems are expected to interact with other traffic participants, which often are multiple other vehicles. To facilitate the motion planning of the autonomously controlled vehicle in collision avoidance, individual object vehicles with closeness in positions and velocities can be grouped as a single extended moving object. However, due to uncertainties from sensor imperfections and environmental disturbances, the collision avoidance conditions are often expressed as difficult to resolve probabilistic constraints in the motion planning problem. In this paper, we propose a constraint tightening method to transform the probabilistic collision avoidance condition for a vehicle group or an extended object into a deterministic form. This is done via a conservative closed-form transformation of the bivariate integral in the collision probability density function and subsequent computable approximation with logistic functions. Detailed numerical experiments are included to illustrate the workings and the performance of the proposed approach. This method can be incorporated in existing motion planning methods.

This paper investigates two frameworks for interfacing trajectory tracking functions with a computationally tractable nonlinear model predictive trajectory guidance module for an autonomous road vehicle. In the first framework, the predictive trajectory guidance itself is configured in a tracking mode where the control inputs computed by the model predictive control act as targets for some lower-level control system acting on the steering, brakes or engine. In the second framework, the state trajectories computed by the predictive trajectory guidance module are configured to be tracked by a non-predictive state tracking controller derived via input/output linearization. In both frameworks, the main considerations are driven by the time scales selected for computational expediency of the predictive guidance module, its update rate, and for control of the lower-level dynamics. The performance of the two frameworks, including the computational aspects, are compared considering public road driving as well as high performance race line scenarios.