Assessing Pedestrian Safety Conditions on Campus

Pedestrian-related crashes are a significant safety issue in the United States and cause considerable amounts of deaths and economic cost. Pedestrian safety is an issue that must be uniquely evaluated in a college campus, where pedestrian volumes are dense. The objective of this research is to identify issues at specific locations around UCF and suggest solutions for improvement. To address this problem, a survey that identifies pedestrian safety issues and locations is distributed to UCF students and staff, and an evaluation of drivers reactions to pedestrian to vehicle (P2V) warning systems is studied through the use of a NADS MiniSim driving simulator. The survey asks participants to identify problem intersections around campus and other issues as pedestrians or bicyclists in the UCF area. Univariate probit models were created from the survey data to identify which factors contribute to pedestrian safety issues, based off the pedestrian\u27s POV and the driver\u27s POV. The models indicated that the more one is exposed to traffic via walking, biking, and driving to campus contributes to less safe experiences. The models also show that higher concerns with drivers not yielding, unsafety of crossing the intersections, and the number of locations to cross, indicate less safe pedestrian experiences from the point of view of pedestrians and drivers. A promising solution for pedestrian safety is Pedestrian to Vehicle (P2V) communication. This study simulates P2V connectivity using a NADS MiniSim Driving Simulator to study the effectiveness of the warning system on drivers. According to the results, the P2V warning system significantly reduced the number of crashes in the tested pre-crash scenarios by 88%. Particularly, the P2V warning system can help decrease the driver\u27s reaction time as well as impact velocity if the crash were to occur

Integration of body sensor networks and vehicular ad-hoc networks for traffic safety

The emergence of Body Sensor Networks (BSNs) constitutes a new and fast growing trend for the development of daily routine applications. However, in the case of heterogeneous BSNs integration with Vehicular ad hoc Networks (VANETs) a large number of difficulties remain, that must be solved, especially when talking about the detection of human state factors that impair the driving of motor vehicles. The main contributions of this investigation are principally three: (1) an exhaustive review of the current mechanisms to detect four basic physiological behavior states (drowsy, drunk, driving under emotional state disorders and distracted driving) that may cause traffic accidents is presented; (2) A middleware architecture is proposed. This architecture can communicate with the car dashboard, emergency services, vehicles belonging to the VANET and road or street facilities. This architecture seeks on the one hand to improve the car driving experience of the driver and on the other hand to extend security mechanisms for the surrounding individuals; and (3) as a proof of concept, an Android real-time attention low level detection application that runs in a next-generation smartphone is developed. The application features mechanisms that allow one to measure the degree of attention of a driver on the base of her/his EEG signals, establish wireless communication links via various standard wireless means, GPRS, Bluetooth and WiFi and issue alarms of critical low driver attention levels.Peer ReviewedPostprint (author's final draft

The Impact of Weather Conditions and Infrastructure Design on the Mobility of People with Impaired Vision

University of Minnesota M.S. thesis. July 2019. Major: Design. Advisor: Gordon Legge. 1 computer file (PDF); viii, 104 pages.Nineteen normally-sighted, low vision, and blind pedestrians provided self-reported effects of environmental, infrastructural, and social factors influencing outdoor mobility in the Minnesota’s Twin-Cities metropolitan area. Focus groups and interviews were conducted to gather data on challenges associated with year-round, independent outdoor navigation emphasizing winter pedestrian mobility. Study themes included weather pressures (e.g., precipitation, temperature), infrastructural/engineering features (e.g., street, sidewalk, intersection design and maintenance), and safety concerns related to motorists and obstacles. Results identify pedestrian hazard impacts on quality of life and behavioral adaptations visually-impaired pedestrians create to increase safety and efficiency during mobility. Conclusions prompt considerations for urban planners, engineers, community activists, and stakeholders concerning mobility issues for visually-impaired pedestrians. Recommendations are provided to promote equity and wellbeing in pedestrian mobility

Assigning Liability in an Autonomous World

Liability laws currently in use rely on a fault-based system that focuses on a causal connection between driver actions and the resulting road accident. The role of the driver is set to reduce with the emergence of autonomous vehicles, so how will liability adapt to meet the needs of an autonomous world? The paper discusses possible frameworks of liability that could be implemented in the future, and accentuates the importance of the causal aspects of the current framework in the new system

Internet of Things (IoT) Applications With Diverse Direct Communication Methods

Title from PDF of title page viewed August 28, 2017Dissertation advisor: Baek-Young ChoiVitaIncludes bibliographical references (pages 124-138)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2016Internet of Things (IoT) is a network of physical objects or things that are embedded with electronics, software, sensors, and network connectivity - which enable the object to collect and exchange data. Rapid proliferation of IoT is driving the intelligence in things used daily in homes, workplaces and industry. The IoT devices typically communicate via radio frequency (RF), such as WiFi and Bluetooth. In this dissertation we deeply analyze the various characteristics of different wireless communication methods in terms of range, energy-efficiency, and radiation pattern. We find that a well-established communication method might not be the most efficient, and other alternate communication methods with the desired properties for a particular application could exist. We exploit radically alternative, innovative, and complimentary wireless communication methods, including radio frequency, infrared (IR), and visible lights, through the IoT applications we have designed and built with those. We have developed various IoT applications which provide security and authentication, enable vehicular communications with smartphones or other smart devices, provide energy-efficient and accurate positioning to smart devices, and enable energy-efficient communications in Industrial Internet of Things (IIoT).Introduction -- Optical wireless authentication for SMART devices using an onboard ambient light sensor -- Smartphome based CAR2X-communication with wifi beacon stuffing for vulnerable road user safety -- Energy-efficient cooperative opportunistic positioning heterogeneous Smart devices -- Reducing and balancing energy consumption in Indistrial Internet of Things (IIoT) -- Optical wireless unlocking for Smart door locks using Smartphones -- Summary and future direction

Tennessee Highway Safety Office 2016 Annual Report

https://digitalcommons.memphis.edu/govpubs-tn-safety-homeland-security-highway-safety-office/1012/thumbnail.jp

Understanding the influence of weather and warning information on trip and activity decisions, behaviour, and risk outcomes

Winter storms present challenges to the safe design, operation and maintenance of transportation systems. Weather warning information, often originating from publicly funded meteorological services, is intended to support decision making in ways that reduce risk and disruption. Among the general public, the most frequent weather-sensitive decisions are those associated with personal mobility—routine trips that serve or facilitate social interaction, employment, business, shopping, recreation and leisure activities. While existing research examines hazard perceptions, driver adjustments, and the effects of weather on mobility and safety outcomes, few studies have explicitly investigated how weather and related warnings affect trip and activity decisions and behaviour, and risk outcomes, during winter storms. Gaps in the literature remain regarding: non-auto modes of winter mobility; dynamic aspects of individual hazard perception, information use, and trip and activity behaviour; effects of research design, method and measurement choices on insights about warning efficacy; and the applicability of current behavioural theory to enhance understanding. These concerns were addressed in this dissertation using a mixed-methods approach that included: formal risk analysis of large secondary motor vehicle collision and fall injury data sets; semi-structured interviews with a purposive sample of households with high levels of everyday travel; experience sampling of the same cohort during multiple winter storms in near real-time; and analysis, evaluation, and interpretation of the Theory of Planned Behaviour. The research resulted in several important empirical findings, theoretical considerations, and methodological contributions. Empirical analyses showed that falls account for a greater proportion of the excess injury burden during winter storms than motor vehicle collisions. Further, no official government warning was issued in almost two-thirds of winter storm events that produced excess injuries. The interviews and winter storm surveys exposed more nuanced and detailed interpretations of factors thought to affect trip behaviour, including variable definitions and perceptions of winter storm hazards and a complex arrangement of elements that comprise concern. Empirical findings also supported a role for official warnings in raising participant awareness and increasing confidence in general storm expectations and concern, but highlighted people’s reliance on informal sources to inform specific mobility intentions and behaviours as a storm progressed. vi This dissertation is among the first to incorporate and evaluate a general behavioural theory—the Theory of Planned Behaviour (TPB)—to help explain the influence of weather information on trip and activity practices during winter storms. An interpretive analysis raised questions about the effectiveness of guidance offered through TPB, diagnosing a particular inability of the model to accommodate and discretize potential interaction, sequencing, or substitution among certain protective behaviours. Other contributions of the dissertation were methodological. They included development and successful application of new event definition criteria to capture the entire life cycle and evolution of discrete winter storms as might be perceived and experienced by the public; the design of a consistency analysis method to assess and interrogate TPB constructs using small samples; and the combination of pre-season interviews with a novel experience sampling procedure used to examine inter- and intra-storm effects, which shed unique light upon dynamic aspects of factors and TPB constructs thought to affect the influence of winter weather-related risk information on trip and activity behaviour. The multiple dimensions of temporal and within-participant variation in risk outcomes, exposure, beliefs, perceptions, and preferences revealed through this dissertation strongly points to a future of warning services that necessarily must be tailored to individual situations and circumstances at discrete points in time in order to increase efficacy and societal value