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Self-Expressive & Self-Healing Closures Hardwares for Autonomous & Shared Mobility
ISSN: 0148-7191, e-ISSN: 2688-3627
Published November 21, 2019 by SAE International in United States
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Event: NuGen Summit
Shared Mobility is changing mobility trends of Automotive Industry and its one of the Disruptions. The current vehicle customer usage and life of components are designed majorly for personal vehicle and with factors that comprehend usage of shared vehicles. The usage pattern for customer differ between personal vehicle, shared vehicle & Taxi. In the era of Autonomous and Shared mobility systems, the customer usage and expectation of vehicle condition on each & every ride of vehicle will be a vehicle in good condition on each ride. The vehicle needs systems that will guide or fix the issues on its own, to improve customer satisfaction. We also need a transformation in customer behavior pattern to use shared mobility vehicle as their personal vehicle to improve the life of vehicle hardwares & reduce warranty cost. We will be focusing on Vehicle Closure hardware & mechanisms as that will be the first and major interaction point for customers in vehicle. This gives us an opportunity to improve product life and customer experience in ride share and shared mobility vehicles. Vehicle closures human interface’s and their components like opening/closing of door, hood, liftgate, Inside / Outside handle, window regulator etc., will be monitored against specific parameters for their performance and usage pattern. The performance parameters will be tracked for every customer and mapped to their profile as customer behavior model. Vehicle closure hardware will express its emotions (Self-Expressive) based on customer interactions to the components. By this system we will control customer abusive behavior, reduce impacts to vehicle and improve life to the component. Vehicle Closures hardware performance parameters will be monitored by IoT sensors and predictive maintenance decisions (Self-Healing) will be taken by component failure theory & warranty history by machine learning algorithms. This system will help to increase life of component & also improve customer satisfaction.
CitationSubramanian, V., Kumar, B., Sivakrishna, M., and Marappan, A., "Self-Expressive & Self-Healing Closures Hardwares for Autonomous & Shared Mobility," SAE Technical Paper 2019-28-2525, 2019.
Data Sets - Support Documents
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