scholarly journals Let’s Be Reasonable: The Consumer Expectations Test is Simply Not Viable to Determine Design Defect for Complex Autonomous Vehicle Technology

2019 ◽  
Vol 2019 ◽  
pp. 52-72
Author(s):  
Emily Frascaroli ◽  
John Isaac Southerland ◽  
Elizabeth Davis ◽  
Woods Parker
Keyword(s):  
Autonomous Vehicle ◽  
Product Liability ◽  
Traffic Crashes ◽  
Consumer Expectations ◽  
Design Defect ◽  
Future Viability ◽  
Vehicle Technology ◽  
Design Defects ◽  
Technical Products ◽  
Autonomous Technology

Although highly automated vehicles (“HAVs”) have potential to reduce deaths and injuries from traffic crashes, product liability litigation for design defects in vehicles incorporating autonomous technology is inevitable. During the early stages of implementation, courts and juries will be forced to grapple with the application of traditional product liability principles to a never before experienced category of highly technical products. Recent decisions limiting the use of the consumer expectations test in cases involving complex products prompted the authors to examine more closely the history behind and the future viability of the consumer expectations test in HAV litigation.

Autonomous Transport: Transforming Logistics through Driverless Intelligent Transportation

2018 ◽  
Vol 2672 (7) ◽  
pp. 24-33
Author(s):  
Anders Hjalmarsson-Jordanius ◽  
Mikael Edvardsson ◽  
Martin Romell ◽  
Johan Isacson ◽  
Carl-Johan Aldén ◽  
...  
Keyword(s):  
Traffic Control ◽  
Autonomous Vehicle ◽  
Autonomous Driving ◽  
Lessons Learned ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Traffic Control System ◽  
Vehicle Technology ◽  
Being Moved ◽  
Autonomous Technology

How can autonomous technology be used beyond end-customer autonomous driving features? This position paper addresses this problem by exploring a novel autonomous transport solution applied in the automotive logistics domain. We propose that factory-complete cars can be transformed to become their own autonomous guided vehicles and thus transport themselves when being moved from the factory for shipment. Cars equipped with such a system are driverless and use an onboard autonomous transport solution combined with the advanced driver assistance systems pre-installed in the car for end-customer use. The solution uses factory-equipped sensors as well as the connectivity infrastructure installed in the car. This means that the solution does not require any extra components to enable the car to transport itself autonomously to complete a transport mission in the logistics chain. The solution also includes an intelligent off-board traffic control system that defines the transport mission and manages the interaction between vehicles during systems operation. A prototype of the system has been developed which was tested successfully in live trials at the Volvo Car Group plant in Gothenburg Sweden in 2017. In the paper, autonomous transport is positioned in between autonomous guided vehicles and autonomous driving technology. A review of the literature on autonomous vehicle technology offers contextual background to this positioning. The paper also presents the solution and displays lessons learned from the live trials. Finally, other use areas are introduced for driverless autonomous transport beyond the automotive logistics domain that is the focus of this paper.

scholarly journals Introduction of Human Assistance in Self-Driving Car

2021 ◽  
Vol 23 (08) ◽  
pp. 635-645
Author(s):  
Vidya Khanna ◽  
◽  
Rahul Kakkar ◽  
Sahil Ahlawat ◽  
◽  
...  
Keyword(s):  
Automobile Industry ◽  
Human Life ◽  
Autonomous Vehicle ◽  
Learning Technology ◽  
The Past ◽  
Artificial Intelligence Technology ◽  
Vehicle Technology ◽  
Automation Technology ◽  
Autonomous Technology ◽  
Day By Day

An Autonomous car is also called as self-drive car or driverless car or robotic car whatever the name but the aim of the technology is same. From the past few years, updating automation technology day by day and using all aspects in regular human life. The present scenery of human being is addicted to automation and machine learning technology like medical, transportation and in IT sector. For the last 10 years the Automobile industry came forward to researching autonomous vehicle technology (Tesla, Uber, Google, Volvo, Audi and Renault). Everyday autonomous technology researches are solving challenges. In the future without human help there will be a human assistance using artificial intelligence technology based on requirement and prefer this vehicle are very safe and comfortable in emergency.

FPGA Based Vehicle to Vehicle Communication in Spartan 3E

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.

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

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.

Predictively Coordinated Vehicle Acceleration and Lane Selection Using Mixed Integer Programming

2018 ◽  
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.

On Behavioural Asymmetry in Product Liability Law

2021 ◽  
Vol 12 (1) ◽  
pp. 40-64
Author(s):  
Thomas Verheyen
Keyword(s):  
Cognitive Biases ◽  
Product Liability ◽  
Point Of View ◽  
Evidence Based ◽  
European Law ◽  
Consumer Expectations ◽  
Liability Law ◽  
The Asymmetry ◽  
New Criterion

Abstract This theoretical article identifies the asymmetry between the producer and the consumer as the key to understanding product liability law. In an attempt to resolve the endless scholarly and jurisprudential debates on the proper criterion for defectiveness in European law, it first tracks the ways in which the commonly opposed consumer expectations and risk-utility test each fail to address the typical asymmetries between producers and consumers in a satisfying manner. Building upon the concept of ‘behavioural asymmetry’, it then develops a new criterion for defectiveness under European law: the behavioural risk-utility test. Under a behavioural risk-utility test, the producer is liable if the product is not reasonably safe for average users suffering from cognitive biases and other behavioural shortcomings. This test aptly combines the systemic point of view of risk-utility balancing with an evidence-based conception of asymmetry, and therefore provides a meaningful criterion for adjudicating product liability disputes.

scholarly journals The Impact of Social Influence, Technophobia, and Perceived Safety on Autonomous Vehicle Technology Adoption

2019 ◽  
Vol 48 (2) ◽  
pp. 133-142
Author(s):  
Sahil Koul ◽  
Ali Eydgahi
Keyword(s):  
Technology Adoption ◽  
Social Influence ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Negative Relationship ◽  
Future Research ◽  
Intention To Use ◽  
Perceived Safety ◽  
Vehicle Technology ◽  
The Impact

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.

Performance analysis and design trade-offs in warehouses with autonomous vehicle technology

2012 ◽  
Vol 44 (12) ◽  
pp. 1045-1060 ◽  
Author(s):  
Debjit Roy ◽  
Ananth Krishnamurthy ◽  
Sunderesh S. Heragu ◽  
Charles J. Malmborg
Keyword(s):  
Performance Analysis ◽  
Autonomous Vehicle ◽  
Analysis And Design ◽  
Trade Offs ◽  
Vehicle Technology ◽  
Performance Analysis And Design
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