scholarly journals Self-protective and self-sacrificing preferences of pedestrians and passengers in moral dilemmas involving autonomous vehicles

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261673
Author(s):  
Maike M. Mayer ◽  
Raoul Bell ◽  
Axel Buchner

Upon the introduction of autonomous vehicles into daily traffic, it becomes increasingly likely that autonomous vehicles become involved in accident scenarios in which decisions have to be made about how to distribute harm among involved parties. In four experiments, participants made moral decisions from the perspective of a passenger, a pedestrian, or an observer. The results show that the preferred action of an autonomous vehicle strongly depends on perspective. Participants’ judgments reflect self-protective tendencies even when utilitarian motives clearly favor one of the available options. However, with an increasing number of lives at stake, utilitarian preferences increased. In a fifth experiment, we tested whether these results were tainted by social desirability but this was not the case. Overall, the results confirm that strong differences exist among passengers, pedestrians, and observers about the preferred course of action in critical incidents. It is therefore important that the actions of autonomous vehicles are not only oriented towards the needs of their passengers, but also take the interests of other road users into account. Even though utilitarian motives cannot fully reconcile the conflicting interests of passengers and pedestrians, there seem to be some moral preferences that a majority of the participants agree upon regardless of their perspective, including the utilitarian preference to save several other lives over one’s own.

Author(s):  
Giovanni Iacca ◽  
Francesca Lagioia ◽  
Andrea Loreggia ◽  
Giovanni Sartor

As Autonomous vehicles (AVs) are entering shared roads, the challenge of designing and implementing a completely autonomous vehicle is still open. Aside from technological issues regarding how to manage the complexity of the environment, AVs raise difficult legal issues and ethical dilemmas, especially in unavoidable accident scenarios. In this context, a vast speculation depicting moral dilemmas has developed in recent years. A new perspective was proposed: an “Ethical Knob” (EK), enabling passengers to ethically customise their AVs, namely, to choose between different settings corresponding to different moral approaches or principles. In this contribution we explore how an AV can automatically learn to determine the value of its “Ethical Knob” in order to achieve a trade-off between the ethical preferences of passengers and social values, learning from experienced instances of collision. To this end, we propose a novel approach based on a genetic algorithm to optimize a population of neural networks. We report a detailed description of simulation experiments as well as possible applications.


2016 ◽  
Vol 38 (1) ◽  
pp. 6-12 ◽  
Author(s):  
Adam Millard-Ball

Autonomous vehicles, popularly known as self-driving cars, have the potential to transform travel behavior. However, existing analyses have ignored strategic interactions with other road users. In this article, I use game theory to analyze the interactions between pedestrians and autonomous vehicles, with a focus on yielding at crosswalks. Because autonomous vehicles will be risk-averse, the model suggests that pedestrians will be able to behave with impunity, and autonomous vehicles may facilitate a shift toward pedestrian-oriented urban neighborhoods. At the same time, autonomous vehicle adoption may be hampered by their strategic disadvantage that slows them down in urban traffic.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Darius-Aurel Frank ◽  
Polymeros Chrysochou ◽  
Panagiotis Mitkidis ◽  
Dan Ariely

Abstract The development of artificial intelligence has led researchers to study the ethical principles that should guide machine behavior. The challenge in building machine morality based on people’s moral decisions, however, is accounting for the biases in human moral decision-making. In seven studies, this paper investigates how people’s personal perspectives and decision-making modes affect their decisions in the moral dilemmas faced by autonomous vehicles. Moreover, it determines the variations in people’s moral decisions that can be attributed to the situational factors of the dilemmas. The reported studies demonstrate that people’s moral decisions, regardless of the presented dilemma, are biased by their decision-making mode and personal perspective. Under intuitive moral decisions, participants shift more towards a deontological doctrine by sacrificing the passenger instead of the pedestrian. In addition, once the personal perspective is made salient participants preserve the lives of that perspective, i.e. the passenger shifts towards sacrificing the pedestrian, and vice versa. These biases in people’s moral decisions underline the social challenge in the design of a universal moral code for autonomous vehicles. We discuss the implications of our findings and provide directions for future research.


Author(s):  
Mohsen Malayjerdi ◽  
Vladimir Kuts ◽  
Raivo Sell ◽  
Tauno Otto ◽  
Barış Cem Baykara

Abstract One of the primary verification criteria of the autonomous vehicle is safe interaction with other road users. Based on studies, real-road testing is not practical for safety validation due to its time and cost consuming. Therefore, simulating miles driven is the only feasible way to overcome this limitation. The primary goal of the related research project is to develop advanced techniques in the human-robot interaction (HRI) safety validation area by usage of immersive simulation technologies. Developing methods for the creation of the simulation environment will enable us to do experiments in a digital environment rather than real. The main aim of the paper is to develop an effective method of creating a virtual environment for performing simulations on industrial robots, mobile robots, and autonomous vehicles (AGV-s) from the safety perspective for humans. A mid-size drone was used for aerial imagery as the first step in creating a virtual environment. Then all the photos were processed in several steps to build the final 3D map. Next, this mapping method was used to create a high detail simulation environment for testing an autonomous shuttle. Developing efficient methods for mapping real environments and simulating their variables is crucial for the testing and development of control algorithms of autonomous vehicles.


2018 ◽  
Author(s):  
Igor Radun ◽  
Jenni Radun ◽  
Jyrki Kaistinen ◽  
Jake Olivier ◽  
Göran Kecklund ◽  
...  

Unlike hypothetical trolley problem studies and an ongoing ethical dilemma with autonomous vehicles, road users can face similar ethical dilemmas in real life. Swerving a heavy vehicle towards the road-side in order to avoid a head-on crash with a much lighter passenger car is often the only option available which could save lives. However, running off-road increases the probability of a roll-over and endangers the life of the heavy vehicle driver. We have created an experimental survey study in which heavy vehicle drivers randomly received one of two possible scenarios. We found that responders were more likely to report they would ditch their vehicle in order to save the hypothetical driver who fell asleep than to save the driver who deliberately diverted their car towards the participant’s heavy vehicle. Additionally, the higher the empathy score, the higher the probability of ditching a vehicle. Implications for autonomous vehicle programming are discussed.


Author(s):  
Yiran Zhang ◽  
Peng Hang ◽  
Chao Huang ◽  
Chen Lv

Interacting with surrounding road users is a key feature of vehicles and is critical for intelligence testing of autonomous vehicles. The Existing interaction modalities in autonomous vehicle simulation and testing are not sufficiently smart and can hardly reflect human-like behaviors in real world driving scenarios. To further improve the technology, in this work we present a novel hierarchical game-theoretical framework to represent naturalistic multi-modal interactions among road users in simulation and testing, which is then validated by the Turing test. Given that human drivers have no access to the complete information of the surrounding road users, the Bayesian game theory is utilized to model the decision-making process. Then, a probing behavior is generated by the proposed game theoretic model, and is further applied to control the vehicle via Markov chain. To validate the feasibility and effectiveness, the proposed method is tested through a series of experiments and compared with existing approaches. In addition, Turing tests are conducted to quantify the human-likeness of the proposed algorithm. The experiment results show that the proposed Bayesian game theoretic framework can effectively generate representative scenes of human-like decision-making during autonomous vehicle interactions, demonstrating its feasibility and effectiveness. Corresponding author(s) Email:   [email protected]  


2020 ◽  
Vol 47 (2) ◽  
pp. 292-300
Author(s):  
Thomas P Novak

Abstract By using scenarios based on moral dilemmas, Gill (2020) found that when consumers are riding in an autonomous vehicle (AV), they are more willing to harm a pedestrian than when they, themselves, are driving a regular car. By taking a first-person perspective, in contrast to most prior research that has taken a third-person perspective, the problem is framed in a personal way that allows identification of a mechanism of responsibility attribution. In this commentary, a generalized framework is developed in which we can locate the work of Gill (2020), as well as prior research that uses moral dilemmas, to understand how consumers believe that AVs should respond when faced with competing life-and-death alternatives. The framework shows the distinct positions that research to date has adopted, points out gaps in research, and suggests a family of four research agendas that can be pursued going forward, driven in large part by the perspective taken to the moral dilemma. Research employing these different perspectives, including the unresearched problem of taking the perspective of the object, holds promise for using moral dilemmas for enabling our understanding of consumer experience and consumer–object relationships with AVs.


2019 ◽  
Vol 9 (11) ◽  
pp. 2335 ◽  
Author(s):  
Sarfraz Ahmed ◽  
M. Nazmul Huda ◽  
Sujan Rajbhandari ◽  
Chitta Saha ◽  
Mark Elshaw ◽  
...  

As autonomous vehicles become more common on the roads, their advancement draws on safety concerns for vulnerable road users, such as pedestrians and cyclists. This paper presents a review of recent developments in pedestrian and cyclist detection and intent estimation to increase the safety of autonomous vehicles, for both the driver and other road users. Understanding the intentions of the pedestrian/cyclist enables the self-driving vehicle to take actions to avoid incidents. To make this possible, development of methods/techniques, such as deep learning (DL), for the autonomous vehicle will be explored. For example, the development of pedestrian detection has been significantly advanced using DL approaches, such as; Fast Region-Convolutional Neural Network (R-CNN) , Faster R-CNN and Single Shot Detector (SSD). Although DL has been around for several decades, the hardware to realise the techniques have only recently become viable. Using these DL methods for pedestrian and cyclist detection and applying it for the tracking, motion modelling and pose estimation can allow for a successful and accurate method of intent estimation for the vulnerable road users. Although there has been a growth in research surrounding the study of pedestrian detection using vision-based approaches, further attention should include focus on cyclist detection. To further improve safety for these vulnerable road users (VRUs), approaches such as sensor fusion and intent estimation should be investigated.


Author(s):  
Sergiu C. Stanciu ◽  
David W. Eby ◽  
Lisa J. Molnar ◽  
Renée M. St. Louis ◽  
Nicole Zanier ◽  
...  

Interpersonal roadway communication is a vital component of the transportation system. Road users communicate to coordinate movement and increase roadway safety. Future autonomous vehicle research needs to account for the role of interpersonal roadway communication. This literature review synthesizes research on interpersonal interaction between drivers, bicyclists, and pedestrians while also directing attention to implications for autonomous and connected vehicle research. Articles were collected from TRID, PsycINFO, Google Scholar, and ScienceDirect using search terms relevant to driving, communication, and vulnerable road users. The synthesis documents that interpersonal communication not only takes place but is also an important and understudied aspect of safe roadway travel. The review also found that road users employ a variety of communication methods that include gestures, facial expressions, and built-in vehicular devices. Comprehension of messages is influenced by several factors including culture, context, and experience. These results shed light on potential issues and challenges of interpersonal communication and the introduction of autonomous vehicles to the roadway.


Author(s):  
Karina A. Roundtree ◽  
Steven Hattrup ◽  
Janani Swaminathan ◽  
Nicholas Zerbel ◽  
Jeffrey Klow ◽  
...  

Autonomous vehicles are expected on roads in the near future and need to interact safely with external road users, such as manual motor drivers, cyclists, and pedestrians. The particular needs of the external road users, such as children, adults, older adults, and individuals with visual, auditory, and/or cognitive impairments, will vary greatly and must be considered in order to design effective inclusive interfaces for all users. Current interface designs lack effective communication between an autonomous vehicle and external road users with regard to conveying and understanding the mobility intent of each party. The goal is to provide inclusive design guidance for an external human-vehicle interface that enables effective communication between autonomous vehicles and external road users. Factors related to communicating intent, the external road users, and environmental constraints, were used to inform the design guidance.


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