Semi-autonomous Cars Research Articles

The Utilitarian Virtual Self - Using Embodied Personalized Avatars to Investigate Moral Decision-Making in Semi-Autonomous Vehicle Dilemmas.

Embodied personalized avatars are a promising new tool to investigate moral decision-making by transposing the user into the "middle of the action" in moral dilemmas. Here, we tested whether avatar personalization and motor control could impact moral decision-making, physiological reactions and reaction times, as well as embodiment, presence and avatar perception. Seventeen participants, who had their personalized avatars created in a previous study, took part in a range of incongruent (i.e., harmful action led to better overall outcomes) and congruent (i.e., harmful action led to trivial outcomes) moral dilemmas as the drivers of a semi-autonomous car. They embodied four different avatars (counterbalanced - personalized motor control, personalized no motor control, generic motor control, generic no motor control). Overall, participants took a utilitarian approach by performing harmful actions only to maximize outcomes. We found increased physiological arousal (SCRs and heart rate) for personalized avatars compared to generic avatars, and increased SCRs in motor control conditions compared to no motor control. Participants had slower reaction times when they had motor control over their avatars, possibly hinting at more elaborate decision-making processes. Presence was also higher in motor control compared to no motor control conditions. Embodiment ratings were higher for personalized avatars, and generally, personalization and motor control were perceptually positive features. These findings highlight the utility of personalized avatars and open up a range of future research possibilities that could benefit from the affordances of this technology and simulate, more closely than ever, real-life action.

Developing a Regulatory Framework for Autonomous Vehicles: A Proximal Analysis of European Approach and Its Application to ASEAN Countries

Abstract Autonomous vehicles (AV), a new innovative product of the automobile industry designed on the basis of artificial intelligence (AI) technology, thereby capable of operating without direct human control, are believed to be the future of transportation. Hence, as with most great technology, the development of AVs would eventually be limited if regulatory changes are not implemented on time. ASEAN, one of the world’s leading emerging automobile markets, has accepted the arrival of AVs and allowed the automobile producers to introduce autonomous and semi-autonomous cars for the customers. However, most ASEAN countries, with the exception of Singapore, have yet to enact regulations governing AVs. They are facing a number of challenges in determining the legal status of AVs, thereby creating certain restrictions for establishing the platform for production, sales and uses of this AI-driven product. This article will analyse the legal framework on AVs of four ASEAN countries—Indonesia, Singapore, Thailand, and Vietnam. It then attempts to assess the regulatory approaches toward the development of a legal framework for AVs in Germany, France, and the Netherlands, to suggest some effective solutions for ASEAN.

Entangled Intelligent Driving: Relations with Automated Cars

ABSTRACT As machines become increasingly intelligent, the HCI community is presented with new challenges regarding methods to capture and understand user experience (UX). In the case of autonomous driving (AD), this involves new scenarios where humans and intelligent vehicles need to act together in real-life traffic situations with other road users. This article responds to this context by 1) outlining a longitudinal design ethnography method whereby participants drove semiautonomous cars in their everyday environments to capture such human-machine relations in real-life settings, 2) demonstrating the complexities of the relations between humans and AD vehicles, 3) engaging theories of socio-materiality and entanglement to understand the human-machine relations of AD cars, and 4) identifying anticipatory experiences that emerge from these relations and their implications for informing UX design.

Development of the Car Seat through a Wider Range of Active Elements Implementation

Car seats represent a constructive - functional system including a variety of elements, assembled on a specific frame, among those the main components are the seat pan, the seat backrest, and the seat headrest. In order to improve the comfort of the driver and passengers, as well vehicle general safety, the car seats are under of intensive research and implementation of advanced developments.Thus, through of variety of sensors integrated into the seat, some important parameters are analysed for keeping the drivers alert and comfortable while driving semi-autonomous or autonomous cars. For adjustment of the seat linear and angular positions, a special system has been implemented, comprising electric, electronic, and pneumatic elements. Also, seat micro-adjustments are possible through the action of specific actuators. The car seat design and manufacture take into consideration a diverse array of data, based on a large range of parameters to face the diversity of drivers requirements. The present paper is advancing a conceptual development of car complex seat, integrating a number of active elements, with multiple possible adjustments. The new seat model is designed to satisfy a larger diversity of people both in terms of comfort and safety.

Breaking the cycle of frustration: Applying Neisser's Perceptual Cycle Model to drivers of semi-autonomous vehicles

Semi-autonomous cars are already on the road and highly autonomous cars will soon be with us. Little is understood about how drivers will adapt to the changing relationship with their vehicle, but to ensure safety and consumer acceptance, this insight is vital. To this end, an on-road study in a semi-autonomous vehicle was undertaken with six UK drivers. The ‘think aloud’ technique was employed and video and audio footage of their interaction with the vehicle was captured. Neisser's (1976) Perceptual Cycle Model (PCM) was used to analyse the data and three case studies are presented to highlight how poor synergy between driver and semi-autonomous vehicles can occur from the lens of Schema, Action or World information. Seven key design considerations are proposed to ensure a more positive and safer interaction between driver and autonomous vehicle to guide focus by manufacturers. Further evidence for the existence of a ‘counter cycle’ (Plant and Stanton, 2015) within the PCM is found and how this relates to the challenges of using verbal protocals expressed during a fast moving dynamic task is discussed.

Psychophysiological aspects of maintaining drivers’ optimal attention level while driving semi-autonomous cars

Psychophysiological aspects of maintaining drivers’ optimal attention level while driving semi-autonomous cars

An Innovative Autonomous and Semiautonomous Cars Communication Framework: An Environment Perception Perspective

Autonomous vehicles are equipped with multiple sensors that allow perception of the road environment. However, there are always challenges in terms of measurement accuracy, dynamics of the road driving conditions, and extended perception availability. Vehicular communication technologies have already been extensively researched, and the IEEE 802.11p standard has been approved. Therefore, communications could help in extending the perception of the autonomous vehicles if proper information transmission mechanisms are utilized. In fact, this paper proposes a novel and innovative design that will allow vehicles to extend their perception by exchanging a smaller number of packets than needed and estimate the actual perception of the environment. First, we propose a novel MAC layer that is compatible with the IEEE 802.11p standard that allows vehicles to recover extra perceptional areas of the environment as they receive new packets. Second, we demonstrate that this approach will result in a better utilization of the communication channel and acceptable perception accuracy of the environment, compared to transmitting the complete information.

Technological Solutions to Human Error and How They Can Kill You: Understanding the Boeing 737-Max Products Liability Litigation

Technology often promises increased safety in the form of reduction of human errors. However, there is a dynamic relationship between technological solutions to risks and human behavior. The attempt to design out a persistent pattern of accidents caused by human error can lead to a new, perhaps unanticipated, and possibly even more dangerous pattern of accidents caused or exacerbated by the technology. For this reason it is essential that products liability law proceed from a systems approach, not considering product design and user error in isolation. This article argues that a systems approach to accidents involving technologically advanced products, taking into account the relationship between product design and foreseeable carelessness by users, is essential to ensuring that the law of products liability does not have a negative impact on the underlying goals of this area of law, including the promotion of increased user safety, innovation in product design, and the affordability of useful products. The article uses, as a case study, two accidents involving the Boeing 737-Max jetliner. The Max design incorporated a design feature intended to prevent accidents caused by a pernicious observed pattern of human error. When it failed to function as intended, the result was disaster. Should the blame for these accidents be placed on the manufacturer, for flaws in the design of what was intended as a safety feature? Or should the flight crews be blamed for failing to handle a foreseeable glitch that they were trained to deal with? Complex systems involving interactions between machines and human operators pose a challenge to the usual approach of torts and products liability law of focusing on ex ante incentive creation because of the dynamic relationship between, on the one hand, features of the product’s design and information provided by the manufacturer that are sensitive to patterns of foreseeable user error, and, on the other hand, user behavior that is shaped by the product’s design and the information provided by the manufacturer. The doctrinal and theoretical analysis developed in the context of the 737-Max accidents will be important in other emerging technology contexts, such as the liability exposure of manufacturers and drivers of semi-autonomous cars.

Height-Finding for Automotive THz Radars

This paper explores radar methods to measure the coordinates (distance and height) of objects on or beside a road. Knowledge of these parameters is essential in the development of autonomous or semi-autonomous cars, as well as to improve driving safety. It is shown that the height is best found by trilateration from sensors at multiple locations on a vehicle. The novelty of the work consists in the formulation of the problem and in its solution using a low-THz radar trilateration approach. The expressions obtained allow calculating the coordinates of targets using a number of different methods of radar trilateration. The influence of the system parameters on the accuracy of measurement using different methods of trilateration has been analyzed. The assumptions made were verified by the experimental system based on a 300-GHz ultra-wideband radar. Experimental results are in good agreement with theoretical calculations; they confirmed the practicality of obtaining high-accuracy height measurements on distributed targets such as pedestrians. The physical basis of the techniques developed would also allow the plan position of a target to be found using the same approach.

Intelligent intrusion detection in external communication systems for autonomous vehicles

ABSTRACTSelf-driving vehicles are known to be vulnerable to different types of attacks due to the type of communication systems which are utilized in these vehicles. These vehicles are becoming more reliant on external communication through vehicular ad hoc networks. However, these networks contribute new threats to self-driving vehicles which lead to potentially significant problems in autonomous systems. These communication systems potentially open self-driving vehicles to malicious attacks like the common Sybil attacks, black hole, Denial of Service, wormhole attacks and grey hole attacks. In this paper, an intelligent protection mechanism is proposed, which was created to secure external communications for self-driving and semi-autonomous cars. The protection mechanism is based on the Proportional Overlapping Scores method, which allows to decrease the number of features found in the Kyoto benchmark dataset. This hybrid detection system uses Back Propagation neural networks to detect Denial of Service (DoS), a common type of attack in vehicular ad hoc networks. The results from our experiment revealed that the proposed intrusion detection has the ability to identify malicious vehicles in self-driving and even in semi-autonomous vehicles.

Automation and human relations with the private vehicle: from automobiles to autonomous cars

This article theorises interactions between drivers, cars and their surroundings. It uses Don Ihde’s four human–technology relations – embodiment, hermeneutic, alterity and background – to analyse the ways in which human–car relationships develop through the process of driving. When driving non-autonomous cars, humans are engaged with cars in driver–car assemblages, within which they are aware of not only the car and how they control its movement but also the road and environmental conditions conveyed through the car. In autonomous and semi-autonomous cars, the connection between driver and car, process of driving and surrounding environment is disrupted. This may be regarded as a positive change, freeing drivers from the work of driving to enjoy rest and entertainment as they become passengers; however, as the car moves into a background relation with people inside the vehicle, it can become difficult for a human to take back control of the driving process with little warning.

Hands on the Wheel: A Call for Greater Regulation of Semi-Autonomous Cars

The United States is in the midst of a driverless car revolution. Semi-autonomous cars — those that can steer, accelerate, and brake on their own under certain circumstances — are already available to consumers. Fully autonomous cars will be available within the decade. The federal government and states throughout the nation have responded to these developments by rushing to pass laws designed to regulate the fully autonomous cars that are coming while largely ignoring the semi-autonomous cars that are already on U.S. roads. This is an extremely troubling oversight. New studies suggest that semi-autonomous vehicles are likely far more dangerous than the fully autonomous vehicles being developed. Indeed, despite the fact that semi-autonomous vehicles rely on continuous human supervision to operate safely, a growing body of research demonstrates that drivers of semi-autonomous vehicles are highly prone to distraction and may have significant misunderstandings of the capabilities and limitations of these vehicles. Both the federal government and states should pass laws and regulations designed to address these safety issues. Namely, the federal government should: (1) grant the National Highway Transportation Safety Administration the ability to create and administer a pre-market approval system for autonomous vehicles, (2) require car manufacturers to install attention warning systems on semi-autonomous cars in order to minimize the risk of driver distraction, and (3) place restrictions on the ability of manufacturers to give the semi-autonomous features on their cars names like “Autopilot” that might mislead consumers as to their capabilities. States, in turn, should (1) forbid drivers from tampering with or disabling driver monitoring systems, (2) require owners of semi-autonomous cars to install routine over-the-air software updates that make these vehicles safer, and (3) mandate that drivers of these vehicles complete proper driver training.

Pied Piper and Autonomous Vehicles

Pied Piper's first driverless car had been in an accident and had killed a 26-year-old jogger. Pied Piper felt a deep sadness for the victim's family, and was disappointed and alarmed because the company had optimistically thought driverless cars would eventually lead to total elimination of driving fatalities. The company needed to decide if the car's algorithm was responsible for this death and, if so, what the plan of action should be. Excerpt UVA-E-0413 Rev. Sept. 26, 2018 Pied Piper and Autonomous Vehicles Clara Sloan was in her new semiautonomous car as it drove down California Route 101 when she hit typical morning traffic. The car changed the arrival time to 10 minutes later than she had planned. She hoped to make it to her office in Mountain View, California, by 11:00 a.m. for a meeting with her team. Sloan worked at Pied Piper, a growing tech firm that had earned its stripes in Silicon Valley after creating an impressively fast compression algorithm for eventual use in a wide array of applications, including the most anticipated products of artificial intelligence, drone racing, and autonomous vehicles (AVs). Promoted to senior product manager of Pied Piper's AV division a year ago, Sloan and her team had chalked up some wins, most notably by accomplishing more than 70,000 miles of AV test drives with no accidents. On two occasions, the Pied Piper car had collided with a utility pole and a fire hydrant, but no humans or other cars were involved. Despite its success, Sloan knew that her team faced fierce competition from Ford, Lexus, and even Tesla (she had bought her Model Z before she joined the group) in bringing AVs to market. A rumor had swept through Silicon Valley that Ford was a year away from launching the next Fusion equipped with an autonomous feature. The race to launch the first mass-market AV program was on, and Sloan's development team was not about to lose that honor to what it called “a pack of programmers” from Detroit, Michigan. The stakes regarding this morning's meeting could not have been higher. Sloan and her team had just learned the night before that Pied Piper's first driverless car had been in an accident that had killed a 26-year-old jogger. News of the accident and outrage over the death of a well-loved community member were appearing on social media sites. Sloan felt a deep sadness for the victim's family, and was disappointed and alarmed because like so many others she had optimistically thought driverless cars would eventually lead to total elimination of driving fatalities. But the technology and its various complexities were still in a nascent stage; just yesterday, Sloan had read in a Business Insider article that in 2016 AVs were still “sort of in the Wild West of self-driving cars' ethics.” Nonetheless, Sloan and her team needed to decide if their car's algorithm was responsible for this death and, if so, what the plan of action should be. . . .

Multi-Objective MDPs with Conditional Lexicographic Reward Preferences

Sequential decision problems that involve multiple objectives are prevalent. Consider for example a driver of a semi-autonomous car who may want to optimize competing objectives such as travel time and the effort associated with manual driving. We introduce a rich model called Lexicographic MDP (LMDP) and a corresponding planning algorithm called LVI that generalize previous work by allowing for conditional lexicographic preferences with slack. We analyze the convergence characteristics of LVI and establish its game theoretic properties. The performance of LVI in practice is tested within a realistic benchmark problem in the domain of semi-autonomous driving. Finally, we demonstrate how GPU-based optimization can improve the scalability of LVI and other value iteration algorithms for MDPs.