VOLUME 13(1) • 2021
Autonomous Vehicle Decision-Making Algorithms and Data-driven Mobilities in Networked Transport Systems
ABSTRACT. This article presents an empirical study carried out to evaluate and analyze autonomous vehicle decision-making algorithms and data-driven mobilities in networked transport systems. Building my argument by drawing on data collected from AAA, Accenture, ANSYS, APA, Atomik Research, AUVSI, B..
Autonomous Vehicle Driving Algorithms and Smart Mobility Technologies in Big Data-driven Transportation Planning and Engineering
ABSTRACT. The aim of this paper is to synthesize and analyze existing evidence on autonomous vehicle driving algorithms and smart mobility technologies in big data-driven transportation planning and engineering. Using and replicating data from ANSYS, Atomik Research, AUDI AG, Brookings, Capgemini, D..
Sensing and Computing Technologies, Intelligent Vehicular Networks, and Big Data-driven Algorithmic Decision-Making in Smart Sustainable Urbanism
ABSTRACT. We draw on a substantial body of theoretical and empirical research on sensing and computing technologies, intelligent vehicular networks, and big data-driven algorithmic decision-making in smart sustainable urbanism, and to explore this, we inspected, used, and replicated survey data from..
Autonomous Vehicle Interaction Control Software and Smart Sustainable Urban Mobility Behaviors in Network Connectivity Systems
ABSTRACT. Based on an in-depth survey of the literature, the purpose of the paper is to explore autonomous vehicle interaction control software and smart sustainable urban mobility behaviors in network connectivity systems. Using and replicating data from ANSYS, Atomik Research, AUVSI, Capgemini, CB..
Autonomous Vehicle Algorithms, Big Geospatial Data Analytics, and Interconnected Sensor Networks in Urban Transportation Systems
ABSTRACT. Employing recent research results covering autonomous vehicle algorithms, big geospatial data analytics, and interconnected sensor networks in urban transportation systems, and building my argument by drawing on data collected from AAA, BCG, Brookings, Capgemini, CivicScience, eMarketer, G..
Networked Driverless Technologies, Autonomous Vehicle Algorithms, and Transportation Analytics in Smart Urban Mobility Systems
ABSTRACT. This paper analyzes the outcomes of an exploratory review of the current research on networked driverless technologies, autonomous vehicle algorithms, and transportation analytics in smart urban mobility systems. Using and replicating data from AAA, Abraham et al. (2017), AUDI AG, AUVSI, A..
Autonomous Driving Perception Algorithms and Urban Mobility Technologies in Smart Transportation Systems
ABSTRACT. Empirical evidence on autonomous driving perception algorithms and urban mobility technologies in smart transportation systems has been scarcely documented in the literature. The data used for this study was obtained and replicated from previous research conducted by Adobe Analytics, ANSYS..
Real-World Connected Vehicle Data, Deep Learning-based Sensing Technologies, and Decision-Making Self-Driving Car Control Algorithms in Autonomous Mobility Systems
ABSTRACT. The purpose of this study was to empirically examine real-world connected vehicle data, deep learning-based sensing technologies, and decision-making self-driving car control algorithms in autonomous mobility systems. Building my argument by drawing on data collected from AAA, Abraham et a..
Algorithm-driven Sensing Devices and Connected Vehicle Data in Smart Transportation Networks
ABSTRACT. Despite the relevance of algorithm-driven sensing devices and connected vehicle data in smart transportation networks, only limited research has been conducted on this topic. Using and replicating data from APA, INRIX, Ipsos, Jones Day, Management Events, Nvidia, and Reuters, we performed ..
Autonomous Vehicle Perception Sensor Data in Sustainable and Smart Urban Transport Systems
ABSTRACT. We develop a conceptual framework based on a systematic and comprehensive literature review on autonomous vehicle perception sensor data in sustainable and smart urban transport systems. Building our argument by drawing on data collected from AHAS, CarGurus, Catapult, Dentons, Future Agend..