Autonomous Driving Algorithms and Behaviors, Sensing and Computing Technologies, and Connected Vehicle Data in Smart Transportation Networks
Autonomous Driving Algorithms and Behaviors, Sensing and Computing Technologies, and Connected Vehicle Data in Smart Transportation Networks

Summary/Abstract: This article presents an empirical study carried out to evaluate and analyze autonomous driving algorithms and behaviors, sensing and computing technologies, and connected vehicle data in smart transportation networks. Building our argument by drawing on data collected from AAA, AUVSI, CARiD, Deloitte, McKinsey, Perkins Coie, Schoettle & Sivak (2014), Statista, Thomas et al. (2015), and YouGov, we performed analyses and made estimates regarding how autonomous vehicle planning and driving algorithms can optimize road safety, being instrumental in sensor and data processing methods by cutting down crashes and casualties through a massive volume of information that can be shared between self-driving cars and roadside infrastructure. Data collected from 5,900 respondents are tested against the research model. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.

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