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    Location-Based System to Improve Pedestrian Safety in a Connected Vehicle Technology Environment

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    Author
    Khosravi, Sara
    Issue Date
    2017
    Keywords
    Connected Vehicle
    Location-Based System
    Pedestrian Safety
    Visually Impaired Pedestrian
    Advisor
    Head, K. Larry
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    People with vision impairment have various challenges in wayfinding, navigation, and crossing signalized intersections. They often face physical and information barriers that impede their mobility and undermine their safety along a trip. Visually impaired people usually use a white cane as their primary aid when crossing urban traffic intersections. In order to improve their mobility, safety and accessibility, it is important to provide an assistive system to help them in intersection navigation and to provide information regarding the surrounding environment. While assistive systems have been developed to help visually impaired pedestrians to navigate and find their way, using these systems may be inconvenient. Furthermore, none of the currently available systems provide communication between the users and traffic signal controller that can help them request pedestrian crossing signal timing. Emerging connected vehicle technologies can provide a solution to assist visually impaired people and address their challenges. Conflicts between vehicles and vulnerable road users (VRUs) often result in injuries and fatalities. A situational awareness system could be based on wireless communications between vehicles and VRUs for the exchange of situational awareness information. Compared to the radar-based and vision-based systems, the wireless-based system. can improve VRUs’ safety, especially in non-line-of-sight (NLOS) situations. In particular, it can be very helpful when drivers are making a right or left turn where there is a pedestrian in a crosswalk and visibility conditions are poor. The Smart Walk Assistant (SWA) system was designed, developed, and tested during the research of this dissertation. It includes two wireless communication pathways; pedestrian-to-infrastructure (P2I) and pedestrian-to-vehicle (P2V). The first communication pathway enables users to send a pedestrian signal request to the traffic signal controller and receive traffic signal status. The second communication pathway enables pedestrians and vehicles to exchange information, including location, speed, and heading, that can be used to detect possible conflict between pedestrian and vehicles and provide conflict alerts. The SWA system may be especially beneficial to pedestrians with disability (e.g., blind or visually impaired pedestrians) who would benefit from active support to safely cross streets at signalized intersections. Developing a reliable situational awareness system for pedestrians is much more challenging than for vehicles because a vehicle’s movement is more predictable and usually remains in the lane in the road. In order to provide better location-based services for pedestrians, a position accuracy is needed of, at most, the width of a crosswalk or sidewalk. The SWA system includes a method to estimate a pedestrian’s position. The algorithm is based on integrating Map-Matching and an Extended Kalman Filter (EKF) in a connected vehicle environment to provide precise location information. The system architecture for the SWA application was developed to be applicable for both a simulation environment and a real world traffic system. Hardware-in-the-loop (HIL) simulation environment is developed and calibrated to mimic the real world. Comprehensive testing and assessment of the system and algorithms are conducted in simulation as well as field test networks.
    Type
    text
    Electronic Dissertation
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Systems & Industrial Engineering
    Degree Grantor
    University of Arizona
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