scholarly journals Modeling the Synchronization of Multimodal Perceptions as a Basis for the Emergence of Deterministic Behaviors

2020 ◽  
Vol 14 ◽  
Author(s):  
Pierre Bonzon
Keyword(s):  
Thought Experiment ◽  
Random Search ◽  
Autonomous Vehicle ◽  
Neural Basis ◽  
Scale Level ◽  
Appropriate Behavior ◽  
Human Driver ◽  
Living Organisms ◽  
Potential Food ◽  
Deterministic Behavior

Living organisms have either innate or acquired mechanisms for reacting to percepts with an appropriate behavior e.g., by escaping from the source of a perception detected as threat, or conversely by approaching a target perceived as potential food. In the case of artifacts, such capabilities must be built in through either wired connections or software. The problem addressed here is to define a neural basis for such behaviors to be possibly learned by bio-inspired artifacts. Toward this end, a thought experiment involving an autonomous vehicle is first simulated as a random search. The stochastic decision tree that drives this behavior is then transformed into a plastic neuronal circuit. This leads the vehicle to adopt a deterministic behavior by learning and applying a causality rule just as a conscious human driver would do. From there, a principle of using synchronized multimodal perceptions in association with the Hebb principle of wiring together neuronal cells is induced. This overall framework is implemented as a virtual machine i.e., a concept widely used in software engineering. It is argued that such an interface situated at a meso-scale level between abstracted micro-circuits representing synaptic plasticity, on one hand, and that of the emergence of behaviors, on the other, allows for a strict delineation of successive levels of complexity. More specifically, isolating levels allows for simulating yet unknown processes of cognition independently of their underlying neurological grounding.

scholarly journals Imitating a Safe Human Driver Behaviour in Roundabouts Through Deep Learning

2020 ◽  
Vol 19 (1) ◽  
pp. 85-88
Author(s):  
A. S. J. Cervera ◽  
F. J. Alonso ◽  
F. S. García ◽  
A. D. Alvarez
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Driver Behaviour ◽  
Safety Issues ◽  
Current State ◽  
Surrounding Environment ◽  
Human Driver ◽  
State Of The Environment

Roundabouts provide safe and fast circulation as well as many environmental advantages, but drivers adopting unsafe behaviours while circulating through them may cause safety issues, provoking accidents. In this paper we propose a way of training an autonomous vehicle in order to behave in a human and safe way when entering a roundabout. By placing a number of cameras in our vehicle and processing their video feeds through a series of algorithms, including Machine Learning, we can build a representation of the state of the surrounding environment. Then, we use another set of Deep Learning algorithms to analyze the data and determine the safest way of circulating through a roundabout given the current state of the environment, including nearby vehicles with their estimated positions, speeds and accelerations. By watching multiple attempts of a human entering a roundabout with both safe and unsafe behaviours, our second set of algorithms can learn to mimic the human’s good attempts and act in the same way as him, which is key to a safe implementation of autonomous vehicles. This work details the series of steps that we took, from building the representation of our environment to acting according to it in order to attain safe entry into single lane roundabouts.

scholarly journals An Initial Investigation of the Effects of a Fully Automated Vehicle Fleet on Geometric Design

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
John Khoury ◽  
Kamar Amine ◽  
Rima Abi Saad
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Real Life ◽  
Geometric Design ◽  
Design Elements ◽  
Sight Distance ◽  
Human Driver ◽  
Projected Change ◽  
Vehicle Fleet ◽  
Stopping Sight Distance

This paper investigates the potential changes in the geometric design elements in response to a fully autonomous vehicle fleet. When autonomous vehicles completely replace conventional vehicles, the human driver will no longer be a concern. Currently, and for safety reasons, the human driver plays an inherent role in designing highway elements, which depend on the driver’s perception-reaction time, driver’s eye height, and other driver related parameters. This study focuses on the geometric design elements that will directly be affected by the replacement of the human driver with fully autonomous vehicles. Stopping sight distance, decision sight distance, and length of sag and crest vertical curves are geometric design elements directly affected by the projected change. Revised values for these design elements are presented and their effects are quantified using a real-life scenario. An existing roadway designed using current AASHTO standards has been redesigned with the revised values. Compared with the existing design, the proposed design shows significant economic and environmental improvements, given the elimination of the human driver.

scholarly journals The Convolution Addressing the Conundrum of Liability and Privacy in the Age of Autonomous Vehicles

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Aarushi Kapoor ◽  
Khushi Sharma
Keyword(s):  
Growth Rate ◽  
Future Development ◽  
Automotive Industry ◽  
Privacy Protection ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Human Driver ◽  
The Future ◽  
New Framework

The Automotive Industry has registered an impeccable growth rate since the adoption of autonomous vehicles by vehicle manufacturers in their high-end models. These fully autonomous vehicles are poised to replace the traditional human driver. Hence, the whole set of laws defining liability in the event of an accident involving a vehicle have to be reformed. An autonomous vehicle being sued in lieu of a human driver, would be impractical. With the accidents involving autonomous vehicles increasing, newly minted laws like that of Michigan Harbor Lacunas are forming to address the question of liability and as a consequence of which the innocent (the manufacturer in so many cases) is held absolutely liable, despite his pleading defense. Such a harsh stance is unhealthy for the development of technology. Apart from the conundrum surrounding liability there are other dimensions which are equally unaddressed when it comes to automation. These autonomous vehicles rely on data, thereby adding to the vulnerability of protection of an individual’s privacy. These brimming chaos are likely to hamper the aggrandizement of technology and subsequent protection of commercial interests.This Article is an attempt to comprehensively analyze the uncertainty surrounding the questions of liability and privacy protection for autonomous vehicles. It takes into account the technology friendly interpretation of law, which will balance the diametrically opposite variables. It draws the laws from the existing set of principles available. Further, it proposes a new framework eliminate obscurity and concludes on a positive note with recommendations which are likely to accentuate the effectiveness of the current laws and lay down a steppingstone for the future development of laws.

scholarly journals Time Minimization of Rescue Action Realized by an Autonomous Vehicle

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2099
Author(s):  
Zdzisław Gosiewski ◽  
Konrad Kwaśniewski
Keyword(s):  
Path Planning ◽  
Random Search ◽  
Autonomous Vehicle ◽  
A Priori ◽  
Optimal Path ◽  
Full Time ◽  
Time Optimization ◽  
Time Minimization ◽  
Two Phases ◽  
Time Of Travel

In rescue operations, the full time of action plays important role. It is the sum of the planning, travel, and manipulation (in the action place) phase times. The time minimization of the first two phases by autonomous vehicle for remote action is considered in the paper. For a known a priori map, the path planning consists of local optimal decisions collected next in the general algorithm of the optimal path. Such an approach significantly reduces time of path planning. The robot features and known sparse obstacles reduce the allowable robot speeds. The time of travel is calculated from an allowable velocity profile. Therefore, it can be used to estimate the travel performance. Genetic algorithm and random search-based methods for path finding with travel time optimization are used and compared in the paper. All the proposed time optimization solutions of rescue operations are checked during computer simulations, and results of the simulations are presented.

Enacting into Reality: Using User Enactment to Explore the Future of Autonomous Vehicle Design

2020 ◽  
Vol 64 (1) ◽  
pp. 1561-1565
Author(s):  
Earl W. Huff ◽  
Mengyuan Zhang ◽  
Julian Brinkley
Keyword(s):  
Older Adults ◽  
Interaction Design ◽  
Autonomous Vehicle ◽  
Driving Safety ◽  
Personal Mobility ◽  
Human Driver ◽  
Methodological Tool ◽  
Additional Support ◽  
The Relationship ◽  
Vehicular Technology

Self-driving vehicles have been heralded as a dramatic new advancement in personal mobility. This emerging technology, beyond potentially improving driving safety, also represents a redefined relationship between the human driver and the vehicle. As this artificial intelligence-based vehicular technology becomes more intelligent, conventional interaction design methodologies may be challenged in their ability to fully encompass this redefined relationship. This problem may be even more pronounced for specific populations like older adults (60+) whose perspectives, we argue, have been underexplored in the self-driving vehicle context. Within this report we describe an emerging methodology, user enactment, and explore its use as a generative design process in two studies focused on older adults. This work adds additional support to the contention that user enactment may be an effective methodological tool for researchers in exploring the relationship between humans and intelligent technologies.

scholarly journals Economic Rationality and Ethical Values in Design-Defect Analysis: The Trolley Problem and Autonomous Vehicles

2018 ◽  
Author(s):  
W. Bradley Wendel
Keyword(s):  
Moral Philosophy ◽  
Autonomous Vehicles ◽  
Ethical Issues ◽  
Thought Experiment ◽  
Autonomous Vehicle ◽  
Strict Liability ◽  
Trolley Problem ◽  
Products Liability ◽  
The Third ◽  
Design Defect

The trolley problem is a well-known thought experiment in moral philosophy, used to explore issues such as rights, deontological reasons, and intention and the doctrine of double effect. Recently it has featured prominently in popular discussions of decision making by autonomous vehicle systems. For example, a Mercedes-Benz executive stated that, if faced with the choice between running over a child that had unexpectedly darted into the road and steering suddenly, causing a rollover accident that would kill the driver, an automated Mercedes would opt to kill the child. This paper considers not the ethical issues raised by such dilemmas, but the liability of vehicle manufacturers for injuries that foreseeably result from the design of autonomous systems. Some of the recent commentary on the liability of autonomous vehicle manufacturers suggests unfamiliarity with modern products liability law, particularly the design-defect standard in the Third Restatement of Torts. A superficial understanding of products liability principles – for example, believing it is a regime of strict liability in any meaningful sense – can lead to serious errors in the application of this area of law to autonomous vehicles. It is also a mistake to believe that the economic approach to negligence liability, as developed by Posner and Calabresi, accurately characterizes modern products liability principles. Under the Third Restatement approach, a court or jury will consider whether a product embodies a reasonable balance of safety and utility, and “reasonable” can be interpreted in accordance with ordinary community ethical standards. Thus, some of the issues that are central to resolving trolley problems in moral philosophy may actually recur in design-defect litigation.

scholarly journals Using Real World Data in Virtual Development and Testing of a Path Tracking Controller for an Autonomous Vehicle

2019 ◽  
Vol 8 (12) ◽  
pp. 720-726
Keyword(s):  
Real World ◽  
Autonomous Vehicle ◽  
Field Testing ◽  
Development Project ◽  
Path Tracking ◽  
Real World Data ◽  
Human Driver ◽  
Automatic Regulator ◽  
Pros And Cons ◽  
Two Stages

The article describes an approach to development and testing of a path tracking function for an autonomous vehicle. The essence of the approach consists in combining experimental data and mathematical modeling in order to simulate operation of a path-tracking regulator in real world maneuvers. The procedure can be divided into two stages. The first one implies field-testing of the vehicle under control of a human driver with logging of the essential dynamic variables including the driving trajectory. Then the obtained data is used to validate the model of vehicle dynamics being a tool for further simulations. At the second stage, a simulation is performed with tracking of the previously logged trajectory by an automatic regulator. The results of these steps allow for comparison between the human and automatic controls with assessment of pros and cons of the latter and the ways of improving its performance. The proposed approach was implemented within a research and development project aimed at building of an experimental autonomous vehicle. The article describes the obtained results as well as the experiments and the mathematical model used for implementation of the said approach.

scholarly journals Patterns of Sequential Off-Road Glances Indicate Levels of Distraction in Automated Driving

2019 ◽  
Vol 63 (1) ◽  
pp. 2056-2060 ◽  
Author(s):  
Shiyan Yang ◽  
Jonny Kuo ◽  
Michael G. Lenné
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Autonomous Vehicle ◽  
Mitigation Strategies ◽  
State Monitoring ◽  
Automated Driving ◽  
Safety Concerns ◽  
Human Driver ◽  
Driver Monitoring ◽  
Different Levels

The safety concerns linked to semi-automated driving – more automation, less driver engagement – could be resolved by real-time driver monitoring with mitigation strategies. To achieve this, this paper analyzed an on-road dataset of sequential off-road glance behaviors under different levels of distraction in an autonomous vehicle trial named CANdrive. Several metrics based on sequential off-road glances were proposed and examined in terms of their capacity of measuring the levels of distraction. These findings are useful for the development of high-resolution driver state monitoring to improve safety in the collaboration between human driver and semi-autonomous vehicle.

scholarly journals Explore User Behaviour in Semi-autonomous Driving

2019 ◽  
Vol 1 (1) ◽  
pp. 3871-3880
Author(s):  
Yuan Shi ◽  
Jeyhoon Maskani ◽  
Giandomenico Caruso ◽  
Monica Bordegoni
Keyword(s):  
Autonomous Vehicle ◽  
Autonomous Driving ◽  
Lateral Position ◽  
Steering Wheel ◽  
Physiological Indicators ◽  
The Road ◽  
Road Map ◽  
Human Driver ◽  
And Performance ◽  
Physiological Sensors

AbstractThe control shifting between a human driver and a semi-autonomous vehicle is one of the most critical scenarios in the road-map of autonomous vehicle development. This paper proposes a methodology to study driver's behaviour in semi-autonomous driving with physiological-sensors-integrated driving simulators. A virtual scenario simulating take-over tasks has been implemented. The behavioural profile of the driver has been defined analysing key metrics collected by the simulator namely lateral position, steering wheel angle, throttle time, brake time, speed, and the take-over time. In addition, heart rate and skin conductance changes have been considered as physiological indicators to assess cognitive workload and reactivity. The methodology has been applied in an experimental study which results are crucial for taking insights on users’ behaviour. Results show that individual different driving styles and performance are able to be distinguished by calculating and elaborating the data collected by the system. This research provides potential directions for establishing a method to characterize a driver's behaviour in a semi-autonomous vehicle.

scholarly journals An end-to-end approach to autonomous vehicle control using deep learning

2021 ◽  
Vol 13 (3) ◽  
pp. 32-41
Author(s):  
Gustavo Antonio Magera Novello ◽  
Henrique Yda Yamamoto ◽  
Eduardo Lobo Lustosa Cabral
Keyword(s):  
Neural Network ◽  
Autonomous Vehicle ◽  
Recurrent Network ◽  
Vehicle Control ◽  
Training Data ◽  
Steering Wheel ◽  
Accelerator Pedal ◽  
Convolutional Network ◽  
Human Driver ◽  
End To End

The objective of this work is to develop an autonomous vehicle controller inside Grand Theft Auto V game, used as a simulation environment. It is used an end-to-end approach, in which the model maps directly the inputs from the image of a car hood camera and a sequence of speed values to three driving commands: steering wheel angle, accelerator pedal pressure and brake pedal pressure. The developed model is composed of a convolutional neural network and a recurring neural network. The convolutional network processes the images and the recurrent network processes the speed data. The model learns from data generated by a human driver´s commands. Two interfaces are developed: one for collecting in-game training data and another to verify the performance of the model for the autonomous vehicle control. The results show that the model after training is capable to drive the vehicle as well as a human driver. This proves that a combination of a convolutional network with a recurrent network, using an end-to-end approach, is capable of obtaining a good driving performance even using only images and speed velocity as sensory data.

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