Pedestrians, Autonomous Vehicles, and Cities

2016 ◽  
Vol 38 (1) ◽  
pp. 6-12 ◽  
Author(s):  
Adam Millard-Ball
Keyword(s):  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Urban Neighborhoods ◽  
Urban Traffic ◽  
Risk Averse ◽  
Strategic Interactions ◽  
Road Users ◽  
Self Driving Cars ◽  
Time Autonomous

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.

scholarly journals Autonomous Vehicles within the Urban Space and Transport Security Challenges: Legal Aspect

2020 ◽  
Vol 13 (3) ◽  
pp. 133
Author(s):  
Denis V. Iroshnikov ◽  
Lyubov Yu. Larina ◽  
Aleksandr I. Sidorkin
Keyword(s):  
Urban Space ◽  
Autonomous Vehicles ◽  
Criminal Liability ◽  
Autonomous Vehicle ◽  
Legal Aspect ◽  
Urban Traffic ◽  
Autonomous Operation ◽  
Road Users ◽  
Operation Rules ◽  
Vehicle Inspection

Nowadays autonomous vehicles are getting widespread use in different parts of the world. In some countries, they are being tested within the urban traffic whereas other counties have been already operating them. Such vehicles possess a number of obvious advantages. We cannot but agree that these cars are the future. However, before complete implementation and mass use of autonomous transport on public roads, it is necessary to resolve a number of problems concerning their safety towards road-users. Except for ethical, economic, and other aspects, it also embraces the legal aspect. The article analyses legal problems of ensuring transport security when using autonomous vehicles. It also touches upon the issues of obligations and liability. Special attention is paid to the matters of criminal liability for offences involving an autonomous vehicle. The conducted legal research allowed concluding that it is necessary to improve legislation in the sphere of operating such vehicles. It is essential to enshrine in law autonomous vehicles (whether fully-autonomous or partially-autonomous) operation rules, oblige their owners to perform regular diagnostic assessment, and to add demands to periodic vehicle inspection. When regulating criminal liability for harm caused by a self-driving vehicle, one must proceed from the layer of its autonomy which stipulates bringing the general public to responsibility.

scholarly journals A Game Theory-Based Approach for Modeling Autonomous Vehicle Behavior in Congested, Urban Lane-Changing Scenarios

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1523
Author(s):  
Nikita Smirnov ◽  
Yuzhou Liu ◽  
Aso Validi ◽  
Walter Morales-Alvarez ◽  
Cristina Olaverri-Monreal
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Urban Traffic ◽  
Road User ◽  
Lane Change ◽  
Traffic Light ◽  
User Interactions ◽  
Lane Changing

Autonomous vehicles are expected to display human-like behavior, at least to the extent that their decisions can be intuitively understood by other road users. If this is not the case, the coexistence of manual and autonomous vehicles in a mixed environment might affect road user interactions negatively and might jeopardize road safety. To this end, it is highly important to design algorithms that are capable of analyzing human decision-making processes and of reproducing them. In this context, lane-change maneuvers have been studied extensively. However, not all potential scenarios have been considered, since most works have focused on highway rather than urban scenarios. We contribute to the field of research by investigating a particular urban traffic scenario in which an autonomous vehicle needs to determine the level of cooperation of the vehicles in the adjacent lane in order to proceed with a lane change. To this end, we present a game theory-based decision-making model for lane changing in congested urban intersections. The model takes as input driving-related parameters related to vehicles in the intersection before they come to a complete stop. We validated the model by relying on the Co-AutoSim simulator. We compared the prediction model outcomes with actual participant decisions, i.e., whether they allowed the autonomous vehicle to drive in front of them. The results are promising, with the prediction accuracy being 100% in all of the cases in which the participants allowed the lane change and 83.3% in the other cases. The false predictions were due to delays in resuming driving after the traffic light turned green.

scholarly journals Self-Driving Cars and Criminal Liability

2020 ◽  
Vol 17 (3-4) ◽  
Author(s):  
Béla Csitei
Keyword(s):  
Autonomous Vehicles ◽  
Criminal Liability ◽  
Autonomous Vehicle ◽  
Essential Elements ◽  
Criminal Sanction ◽  
Criminal Offence ◽  
The Subject ◽  
Definition Of ◽  
Self Driving Cars

After clarifying the concepts of automated and autonomous vehicles, the purpose of the study is to investigate how reasonable the criminal sanction is arising from accidents caused by autonomous vehicles. The next question to be answered is that the definition of the crime according to the Hungarian law may be applied in case of traffic related criminal offences caused by automated and autonomous vehicles. During my research I paid special attention to two essential elements of criminal offence, namely the human act and guilt. Furthermore, I strived for finding solution for the next problem, as well: if the traffic related criminal offence is committed by driving an autonomous vehicle, how to define the subject of criminal liability.

Future Blockchain Technology for Autonomous Applications/Autonomous Vehicle

2022 ◽  
pp. 1027-1038
Author(s):  
Arnab Kumar Show ◽  
Abhishek Kumar ◽  
Achintya Singhal ◽  
Gayathri N. ◽  
K. Vengatesan
Keyword(s):  
Autonomous Vehicles ◽  
New Technology ◽  
Autonomous Vehicle ◽  
The Self ◽  
Third Party ◽  
Traffic Information ◽  
Online Transactions ◽  
The Third ◽  
Blockchain Technology ◽  
Self Driving Cars

The autonomous industry has rapidly grown for self-driving cars. The main purpose of autonomous industry is trying to give all types of security, privacy, secured traffic information to the self-driving cars. Blockchain is another newly established secured technology. The main aim of this technology is to provide more secured, convenient online transactions. By using this new technology, the autonomous industry can easily provide more suitable, safe, efficient transportation to the passengers and secured traffic information to the vehicles. This information can easily gather by the roadside units or by the passing vehicles. Also, the economical transactions can be possible more efficiently since blockchain technology allows peer-to-peer communications between nodes, and it also eliminates the need of the third party. This chapter proposes a concept of how the autonomous industry can provide more adequate, proper, and safe transportation with the help of blockchain. It also examines for the possibility that autonomous vehicles can become the future of transportation.

Examining the Equity Impacts of Autonomous Vehicles: A Travel Demand Model Approach

2019 ◽  
Vol 2673 (5) ◽  
pp. 23-35 ◽  
Author(s):  
Jesse Cohn ◽  
Richard Ezike ◽  
Jeremy Martin ◽  
Kwasi Donkor ◽  
Matthew Ridgway ◽  
...  
Keyword(s):  
Performance Measures ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Travel Demand ◽  
Autonomous Vehicle ◽  
Demand Model ◽  
The Status ◽  
Mode Share ◽  
Transit Agencies ◽  
Travel Demand Model

As investments in autonomous vehicle (AV) technology continue to grow, agencies are beginning to consider how AVs will affect travel behavior within their jurisdictions and how to respond to this new mobility technology. Different autonomous futures could reduce, perpetuate, or exacerbate existing transportation inequities. This paper presents a regional travel demand model used to quantify how transportation outcomes may differ for disadvantaged populations in the Washington, D.C. area under a variety of future scenarios. Transportation performance measures examined included job accessibility, trip duration, trip distance, mode share, and vehicle miles traveled. The model evaluated changes in these indicators for disadvantaged and non-disadvantaged communities under scenarios when AVs were primarily single-occupancy or high-occupancy, and according to whether transit agencies responded to AVs by maintaining the status quo, removing low-performing routes, or applying AV technology to transit vehicles. Across the performance measures, the high-occupancy AV and enhanced transit scenarios provided an equity benefit, either mitigating an existing gap in outcomes between demographic groups or reducing the extent to which that gap was expanded.

Current Developments in Autonomous Vehicle Policy in the United States: Federalism’s Influence in State and National Regulatory Law and Policy

Global Jurist ◽  
2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Christopher Salatiello ◽  
Troy B. Felver
Keyword(s):  
United States ◽  
Autonomous Vehicles ◽  
New Technologies ◽  
Autonomous Vehicle ◽  
The United States ◽  
Great Promise ◽  
Maximum Benefit ◽  
Regulatory Law ◽  
Regulatory Bodies ◽  
Self Driving Cars

Abstract With the advent of autonomous vehicles, especially self-driving cars, there is great promise for society. However, cars are not islands; they operate in a community of vehicles. Laws and regulations are crafted to allow the maximum benefit for the community while imposing the fewest costs. Unfortunately, a full accounting of these benefits and costs is not entirely clear at promulgation. Because the technologies and how they will be used are so uncertain, regulatory bodies have to try to build on what they have done in the past, sometimes successfully and sometimes unevenly. This paper will examine several regulatory attempts involving these new technologies in the United States, both on the federal and state levels. Also considered will be the interaction of these regulations under a federal system with defined and specific responsibilities for both sovereigns. A view on future developments is provided to gauge the directions additional regulation could take. Finally, generalizable lessons from this approached will be summarized.

scholarly journals TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agents

2019 ◽  
Vol 33 ◽  
pp. 6120-6127 ◽  
Author(s):  
Yuexin Ma ◽  
Xinge Zhu ◽  
Sibo Zhang ◽  
Ruigang Yang ◽  
Wenping Wang ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Short Term Memory ◽  
Autonomous Vehicle ◽  
Large City ◽  
Urban Traffic ◽  
Heterogeneous Traffic ◽  
Prediction Algorithm ◽  
Trajectory Prediction ◽  
Long Short Term Memory ◽  
Traffic Agents

To safely and efficiently navigate in complex urban traffic, autonomous vehicles must make responsible predictions in relation to surrounding traffic-agents (vehicles, bicycles, pedestrians, etc.). A challenging and critical task is to explore the movement patterns of different traffic-agents and predict their future trajectories accurately to help the autonomous vehicle make reasonable navigation decision. To solve this problem, we propose a long short-term memory-based (LSTM-based) realtime traffic prediction algorithm, TrafficPredict. Our approach uses an instance layer to learn instances’ movements and interactions and has a category layer to learn the similarities of instances belonging to the same type to refine the prediction. In order to evaluate its performance, we collected trajectory datasets in a large city consisting of varying conditions and traffic densities. The dataset includes many challenging scenarios where vehicles, bicycles, and pedestrians move among one another. We evaluate the performance of TrafficPredict on our new dataset and highlight its higher accuracy for trajectory prediction by comparing with prior prediction methods.

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
Keyword(s):  
Social Desirability ◽  
Autonomous Vehicles ◽  
Critical Incidents ◽  
Autonomous Vehicle ◽  
Moral Dilemmas ◽  
Road Users ◽  
Course Of Action ◽  
Moral Decisions ◽  
Conflicting Interests ◽  
Accident Scenarios

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.

Witness of Things

2019 ◽  
Vol 7 (2) ◽  
pp. 72-87 ◽  
Author(s):  
Serkan Ayvaz ◽  
Salih Cemil Cetin
Keyword(s):  
Autonomous Vehicles ◽  
Vehicular Networks ◽  
Autonomous Vehicle ◽  
Content Type ◽  
Record Keeping ◽  
Vehicle To Vehicle ◽  
Autonomous Cars ◽  
Vehicle To Infrastructure ◽  
Governmental Institutions ◽  
Self Driving Cars

Purpose The purpose of this paper is to develop a model for autonomous cars to establish trusted parties by combining distributed ledgers and self-driving cars in the traffic to provide single version of the truth and thus build public trust. Design/methodology/approach The model, which the authors call Witness of Things, is based on keeping decision logs of autonomous vehicles in distributed ledgers through the use of vehicular networks and vehicle-to-vehicle/vehicle-to-infrastructure (or vice versa) communications. The model provides a single version of the truth and thus helps enable the autonomous vehicle industry, related organizations and governmental institutions to discover the true causes of road accidents and their consequences in investigations. Findings In this paper, the authors explored one of the potential effects of blockchain protocol on autonomous vehicles. The framework provides a solution for operating autonomous cars in an untrusted environment without needing a central authority. The model can also be generalized and applied to other intelligent unmanned systems. Originality/value This study proposes a blockchain protocol-based record-keeping model for autonomous cars to establish trusted parties in the traffic and protect single version of the truth.

Virtual Simulations Environment Development for Autonomous Vehicles Interaction

2020 ◽  
Author(s):  
Mohsen Malayjerdi ◽  
Vladimir Kuts ◽  
Raivo Sell ◽  
Tauno Otto ◽  
Barış Cem Baykara
Keyword(s):  
Virtual Environment ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Mapping Method ◽  
Human Robot Interaction ◽  
Industrial Robots ◽  
Simulation Environment ◽  
Road Users ◽  
Virtual Simulations ◽  
Road Testing

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.

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