Understanding Risks and Opportunities of Autonomous Vehicle Technology Adoption Through Systems Dynamic Scenario Modeling—The American Insurance Industry

The objective of this study was to determine whether there was a relationship between social influence, technophobia, perceived safety of autonomous vehicle technology, number of automobile-related accidents and the intention to use autonomous vehicles. The methodology was a descriptive, cross-sectional, correlational study. Theory of Planned Behavior provided the underlying theoretical framework. An online survey was the primary method of data collection. Pearson’s correlation and multiple linear regression were used for data analysis. This study found that both social influence and perceived safety of autonomous vehicle technology had significant, positive relationships with the intention to use autonomous vehicles. Additionally, a significant negative relationship was found among technophobia and intention to use autonomous vehicles. However, no relationship was found between the number of automobile-related accidents and intention to use autonomous vehicles. This study presents several original and significant findings as a contribution to the literature on autonomous vehicle technology adoption and proposes new dimensions of future research within this emerging field.

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FPGA Based Vehicle to Vehicle Communication in Spartan 3E

Journal of Science and Engineering ◽

10.3126/jsce.v8i0.32858 ◽

2020 ◽

Vol 8 ◽

pp. 14-21

Author(s):

Surya Man Koju ◽

Nikil Thapa

Keyword(s):

Signal Processing ◽

Autonomous Vehicle ◽

Processing Unit ◽

Warning Signals ◽

Vehicle Communication ◽

Digital Vlsi ◽

Vehicle To Vehicle ◽

Vehicle Operation ◽

Vehicle Technology ◽

The Voice

This paper presents economic and reconfigurable RF based wireless communication at 2.4 GHz between two vehicles. It implements digital VLSI using two Spartan 3E FPGAs, where one vehicle receives the information of another vehicle and shares its own information to another vehicle. The information includes vehicle’s speed, location, heading and its operation, such as braking status and turning status. It implements autonomous vehicle technology. In this work, FPGA is used as central signal processing unit which is interfaced with two microcontrollers (ATmega328P). Microcontroller-1 is interfaced with compass module, GPS module, DF Player mini and nRF24L01 module. This microcontroller determines the relative position and the relative heading as seen from one vehicle to another. Microcontroller-2 is used to measure the speed of vehicle digitally. The resulting data from these microcontrollers are transmitted separately and serially through UART interface to FPGA. At FPGA, different signal processing such as speed comparison, turn comparison, distance range measurement and vehicle operation processing, are carried out to generate the voice announcement command, warning signals, event signals, and such outputs are utilized to warn drivers about potential accidents and prevent crashes before event happens.

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Auction-Based Consensus of Autonomous Vehicles for Multi-Target Dynamic Task Allocation and Path Planning in an Unknown Obstacle Environment

Applied Sciences ◽

10.3390/app11115057 ◽

2021 ◽

Vol 11 (11) ◽

pp. 5057

Author(s):

Wan-Yu Yu ◽

Xiao-Qiang Huang ◽

Hung-Yi Luo ◽

Von-Wun Soo ◽

Yung-Lung Lee

Keyword(s):

Path Planning ◽

Task Allocation ◽

Autonomous Vehicles ◽

Autonomous Vehicle ◽

Dynamic Task ◽

The Core ◽

Dynamic Task Allocation ◽

Vehicle Technology ◽

Future Work ◽

Complicated Task

The autonomous vehicle technology has recently been developed rapidly in a wide variety of applications. However, coordinating a team of autonomous vehicles to complete missions in an unknown and changing environment has been a challenging and complicated task. We modify the consensus-based auction algorithm (CBAA) so that it can dynamically reallocate tasks among autonomous vehicles that can flexibly find a path to reach multiple dynamic targets while avoiding unexpected obstacles and staying close as a group as possible simultaneously. We propose the core algorithms and simulate with many scenarios empirically to illustrate how the proposed framework works. Specifically, we show that how autonomous vehicles could reallocate the tasks among each other in finding dynamically changing paths while certain targets may appear and disappear during the movement mission. We also discuss some challenging problems as a future work.

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Brief Study and Review on the Next Revolutionary Autonomous Vehicle Technology

2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) ◽

10.1109/icacite51222.2021.9404763 ◽

2021 ◽

Author(s):

Tulasi Krishna Gannavaram V ◽

Rahul Bejgam

Keyword(s):

Autonomous Vehicle ◽

Vehicle Technology

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Autonomous Vehicle Technology: A Guide for Policymakers

10.7249/rr443 ◽

2014 ◽

Keyword(s):

Autonomous Vehicle ◽

Vehicle Technology

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Predictively Coordinated Vehicle Acceleration and Lane Selection Using Mixed Integer Programming

Volume 1: Advances in Control Design Methods; Advances in Nonlinear Control; Advances in Robotics; Assistive and Rehabilitation Robotics; Automotive Dynamics and Emerging Powertrain Technologies; Automotive Systems; Bio Engineering Applications; Bio-Mechatronics and Physical Human Robot Interaction; Biomedical and Neural Systems; Biomedical and Neural Systems Modeling, Diagnostics, and Healthcare ◽

10.1115/dscc2018-9177 ◽

2018 ◽

Cited By ~ 5

Author(s):

R. Austin Dollar ◽

Ardalan Vahidi

Keyword(s):

Autonomous Vehicle ◽

Mixed Integer ◽

Quadratic Program ◽

Vehicle To Vehicle ◽

Trip Time ◽

Induced Travel ◽

Vehicle Acceleration ◽

Vehicle Technology ◽

Rule Based Approach ◽

Integer Quadratic Program

Autonomous vehicle technology provides the means to optimize motion planning beyond human capacity. In particular, the problem of navigating multi-lane traffic optimally for trip time, energy efficiency, and collision avoidance presents challenges beyond those of single-lane roadways. For example, the host vehicle must simultaneously track multiple obstacles, the drivable region is non-convex, and automated vehicles must obey social expectations. Furthermore, reactive decision-making may result in becoming stuck in an undesirable traffic position. This paper presents a fundamental approach to these problems using model predictive control with a mixed integer quadratic program at its core. Lateral and longitudinal movements are coordinated to avoid collisions, track a velocity and lane, and minimize acceleration. Vehicle-to-vehicle connectivity provides a preview of surrounding vehicles’ motion. Simulation results show a 79% reduction in congestion-induced travel time and an 80% decrease in congestion-induced fuel consumption compared to a rule-based approach.

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Managers’ perception of mobile technology adoption in the Life Insurance industry

Information Technology and People ◽

10.1108/itp-09-2016-0212 ◽

2018 ◽

Vol 31 (2) ◽

pp. 507-526 ◽

Cited By ~ 4

Author(s):

Visvanathan Naicker ◽

Derrick Barry Van Der Merwe

Keyword(s):

Technology Adoption ◽

Mobile Technology ◽

Life Insurance ◽

Perceived Risk ◽

Insurance Industry ◽

Demographic Variables ◽

Perceived Usefulness ◽

Content Type ◽

Level Of Education ◽

Life Insurance Industry

Purpose The purpose of this paper is to examine the factors that influence the adoption of mobile technology by considering the information technology (IT) managers’ perception. The research identified the key challenges managers faced and whether management would adopt mobile technology or not. Design/methodology/approach A quantitative approach was used for this research, whereby an explanatory research was utilised. Questionnaires were developed and distributed to respondents who were in management and leadership positions and who were responsible for IT within their organisations. Demographic variables of age, gender differences, level of education, level of experience and culture were tested for association to the perceived factors and adoption. A χ2 of association was used to test the association between demographic variables and mobile technology adoption. Findings The results found that perceived ease of use, perceived usefulness, perceived complexity and perceived cost are important factors for adoption. However, perceived risk was a key factor in the adoption of mobile technology. Mobile strategy adoption must consider perceived risk factors central to the adoption. The younger generation (20 to 40) years found it easier to adopt technology than the older generation of 41 years and older. Individuals with a post matriculation level of education understood the importance of risk and cost required for adoption. Research limitations/implications Purposive sampling from a single industry (Life Insurance) was used. Limited literature was available regarding managers perception of mobile technology adoption in the Life Insurance industry. Practical implications The research offers managers insight into the important factors that need to be considered in adopting mobile technology. Originality/value With mobile technology being pervasive, the research seeks to provide managers with the insight in managing the adoption of the technology.

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