My heart is racing! Psychophysiological dynamics of skilled racecar drivers

Our purpose was to test the multi-action plan (MAP) model assumptions in which athletes’ psychophysiological patterns differ among optimal and suboptimal performance experiences. Nine professional drivers competing in premier race categories (e.g., Formula 3, Porsche GT3 Cup Challenge) completed the study. Data collection involved monitoring the drivers’ perceived hedonic tone, accuracy on core components of action, posture, skin temperature, respiration rate, and heart rate responses during a 40-lap simulated race. Time marks, gathered at three standardized sectors, served as the performance variable. The A1GP racing simulator (Allinsport, Modena) established a realistic race platform. Specifically, the Barcelona track was chosen due to its inherently difficult nature characterized by intermittent deceleration points. Idiosyncratic analyses showed large individual differences in the drivers’ psychophysiological profile, as well as distinct patterns in regards to optimal and suboptimal performance experiences. Limitations and future research avenues are discussed. Action (e.g., attentional control) and emotion (e.g., biofeedback training) centered applied sport psychology implications are advanced

Driver Control Actions in High-Speed Circular Driving

In this pilot study we investigate driver control actions during high speed cornering with a rear wheel drive vehicle. Six drivers were instructed to perform the fastest maneuvers possible around a marked circle, while trying to retain control of the vehicle and constant turning radius. The data reveal that stabilization of the vehicle is achieved with a combination of steering and throttle regulation. The results show that the drivers used steering control to compensate for disturbances in yaw rate and sideslip angle. Vehicle accustomed drivers had the most consistent performance resulting in reduced variance of task metrics and control inputs

Northeast Community Survey 2008: Final Report

East Anchorage is currently the only site in Alaska under the nationwide Weed and Seed initiative, which is intended to “weed out” criminals who undermine quality of life for community residents in high-crime neighborhoods and to “seed in” positive practices, programs and institutions that contribute to a better quality of life for neighborhoods. The East Anchorage Weed and Seed site, located in a racially and ethnically diverse neighborhood in the northeast part of Anchorage, had an estimated population in 2005 of more than 37,000 people living in about 14,000 households. On behalf of East Anchorage Weed and Seed, the Justice Center conducted a community survey designed to evaluate Northeast community residents’ level of satisfaction with their neighborhood as a place to live, specifically with regards to residents' feelings about neighborhood safety, neighborhood crime levels, criminal victimization, police activity in the neighborhood, and the availability of social services. This report presents results of the survey, to which a total of 209 respondents in the Northeast community responded, and compares its results to those of an identical mailed community survey conducted in the same area in 2002.Executive Summary / Introduction / Method / The Study Sample / Perceptions of Public Safety / Perceived Problems in the Northeast Community / Criminal Victimization / Neighborhood Satisfaction / Evaluation/Perception of Local Police Activity / Resident Participation in the Northeast Community / Conclusion / Endnotes / Appendix A: Survey Instrumen

Design, Analysis, and Verification of an Open-Wheeled Formula-Style Race Car Suspension System

This honors thesis presents the design, measurement, and analysis of an open-wheeled formula racecar suspension system. This racecar is the second iteration of Syracuse University’s Citrus Racing team student competition vehicle. The race car’s suspension system features several designs that enable geometric adjustability to impact the vehicles dynamic performance. The purpose of this research is to find an analytic approach to verifying the correlation between suspension design tunings and their effect on vehicle handling and road holding capacity. This was done by analyzing measured data obtained from a system of damper-mounted travel sensors as the vehicle drives through numerous realistic competition scenarios

A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars

Quantifying vehicle control from physiology in type 1 diabetes

Objective: Our goal is to measure real-world effects of at-risk driver physiology on safety-critical tasks like driving by monitoring driver behavior and physiology in real-time. Drivers with type 1 diabetes (T1D) have an elevated crash risk that is linked to abnormal blood glucose, particularly hypoglycemia. We tested the hypotheses that (1) T1D drivers would have overall impaired vehicle control behavior relative to control drivers without diabetes, (2) At-risk patterns of vehicle control in T1D drivers would be linked to at-risk, in-vehicle physiology, and (3) T1D drivers would show impaired vehicle control with more recent hypoglycemia prior to driving. Methods: Drivers (18 T1D, 14 control) were monitored continuously (4 weeks) using in-vehicle sensors (e.g., video, accelerometer, speed) and wearable continuous glucose monitors (CGMs) that measured each T1D driver’s real-time blood glucose. Driver vehicle control was measured by vehicle acceleration variability (AV) across lateral (AVY, steering) and longitudinal (AVX, braking/accelerating) axes in 45-second segments (N = 61,635). Average vehicle speed for each segment was modeled as a covariate of AV and mixed-effects linear regression models were used. Results: We analyzed 3,687 drives (21,231 miles). T1D drivers had significantly higher overall AVX, Y compared to control drivers (BX = 2.5 × 10−2 BY = 1.6 × 10−2, p \u3c 0.01)—which is linked to erratic steering or swerving and harsh braking/accelerating. At-risk vehicle control patterns were particularly associated with at-risk physiology, namely hypo- and hyperglycemia (higher overall AVX,Y). Impairments from hypoglycemia persisted for hours after hypoglycemia resolved, with drivers who had hypoglycemia within 2–3 h of driving showing higher AVX and AVY. State Department of Motor Vehicle records for the 3 years preceding the study showed that at-risk T1D drivers accounted for all crashes (N = 3) and 85% of citations (N = 13) observed. Conclusions: Our results show that T1D driver risk can be linked to real-time patterns of at-risk driver physiology, particularly hypoglycemia, and driver risk can be detected during and prior to driving. Such naturalistic studies monitoring driver vehicle controls can inform methods for early detection of hypoglycemia-related driving risks, fitness to drive assessments, thereby helping to preserve safety in at-risk drivers with diabetes

2006 Annual Research Symposium Abstract Book

2006 annual volume of abstracts for science research projects conducted by students at Trinity College

Towards T.R.I.C.K. 2.0 – A tool for the evaluation of the vehicle performance through the use of an advanced sensors system

In the last years, the tire technological development has played a fundamental role in motorsport and in automotive industry. The tire contact patch forces have a great influence on the vehicle behavior, so their correct estimation is a crucial task to understand how to improve the car performance. In order to identify the tire interaction characteristic, it is also necessary to use a procedure that allows the correct evaluation of the slip angles in the different operating conditions. This paper presents an evolution of the T.R.I.C.K. tool developed by the UniNa vehicle dynamics research group. In the first version of this tool an 8 degree of freedom vehicle model has been implemented and, starting from the experimental data acquired, the T.R.I.C.K. calculates the interaction forces and the tire slips using the equilibrium equations. Using more car parameters and further data obtained from track sessions and dedicated tests, in the presented release of the tool, new formulations have been developed for a more accurate calculation of the tire-road forces. The effectiveness of the treatments is assessed using experimental data and the simulator outputs. The new formulations introduced in this paper allows, depending on the availability of additional vehicle data and acquisition sensors, to estimate the interaction forces with different and more accurate methodologies than the equilibrium equations, while retaining very reduced simulation times. In this way it is possible to carry out a more precise study of vehicle dynamics with the possibility of investigating and significantly improving performance

Black ads matter: an analysis of black representation in advertising.

During the summer of 2020 Black Lives Matter (BLM) became a rallying cry throughout the United States and the world. At that time, many individuals and organizations reflected on how they could better support the movement for equality, equity, and inclusion, but some of the results were ingenuine, perceived as virtue signaling or woke washing. In this thesis I explore the Black representation in advertising from three prominent car brands from both pre- and post-summer 2020. I analyze ads from Acura, Buick, and Lincoln to determine if they are synergistic and include multi-dimensional Black representation, criteria Burgess et al.’s (2020) set for audience connectedness. To measure synergy, I assess the ad elements and offer a new perspective that considers how ad elements that include Black representation work together to create a message about diversity. I discuss the implications of Black representation, or the lack thereof, using congruity theory and social cognitive theory to determine the impacts on both sales and society