scholarly journals A future without drivers? Comparing users', urban planners' and developers' assumptions, hopes, and concerns about autonomous vehicles

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Helena Strömberg ◽  
Érika Martins Silva Ramos ◽  
MariAnne Karlsson ◽  
Mikael Johansson ◽  
Fredrick Ekman ◽  
...  
Keyword(s):  
Focus Groups ◽  
Transport System ◽  
Thematic Analysis ◽  
Autonomous Vehicles ◽  
Travel Demand ◽  
Autonomous Vehicle ◽  
Negative Consequences ◽  
Stakeholder Groups ◽  
The City ◽  
Detrimental Impact

Abstract Aim This study identifies and compares perceptions of autonomous vehicle (AV) implementation among three Swedish stakeholder groups: Future Users, Urban Planners, and Developers. Method Semi-structured comparative focus groups were conducted separately with each of the three groups of stakeholders and the transcripts were analysed in broad themes using thematic analysis. Results Assumptions, hopes, concerns, and direction of development were the main themes that emerged from the analysis. Assumptions included electrification of vehicles, changes in travel demand, and the need for regulations; Hopes included the idea that AVs will contribute to a more accessible and safer transport system; Concerns included overtrust in AV technology, a possible detrimental impact on the city in the form of congestion and higher demand for investments in infrastructure that could outcompete other modes of transport; and Direction of development and their own role, where the need for collaboration between stakeholders and implementation of AVs in connection with society’s needs were emphasised. Conclusions AVs were seen to lead to both positive and negative consequences depending on implementation and the development of society. The study shows that dialogue between different stakeholders is lacking but it is desired for the inclusive implementation of AVs.

scholarly journals Model Contrast of Autonomous Vehicle Impacts on Traffic

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Derek Hungness ◽  
Raj Bridgelall
Keyword(s):  
Autonomous Vehicles ◽  
Travel Demand ◽  
Autonomous Vehicle ◽  
Sociodemographic Factors ◽  
Vehicle Miles Traveled ◽  
The Road ◽  
Traffic Conditions ◽  
Demand Models ◽  
Wide Range ◽  
Potential Benefits

The adoption of connected and autonomous vehicles (CAVs) is in its infancy. Therefore, very little is known about their potential impacts on traffic. Meanwhile, researchers and market analysts predict a wide range of possibilities about their potential benefits and the timing of their deployments. Planners traditionally use various types of travel demand models to forecast future traffic conditions. However, such models do not yet integrate any expected impacts from CAV deployments. Consequently, many long-range transportation plans do not yet account for their eventual deployment. To address some of these uncertainties, this work modified an existing model for Madison, Wisconsin. To compare outcomes, the authors used identical parameter changes and simulation scenarios for a model of Gainesville, Florida. Both models show that with increasing levels of CAV deployment, both the vehicle miles traveled and the average congestion speed will increase. However, there are some important exceptions due to differences in the road network layout, geospatial features, sociodemographic factors, land-use, and access to transit.

scholarly journals Novel Routing Algorithm for Autonomous Vehicles in Smart Transportation System

2021 ◽  
Vol 3 (3) ◽  
pp. 164-179
Author(s):  
Haoxiang Wang
Keyword(s):  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Intelligent Transportation System ◽  
Autonomous Vehicle ◽  
Routing Algorithm ◽  
Transportation System ◽  
Traffic Condition ◽  
Smart Transportation ◽  
Centralized Management ◽  
The City

In recent times Automation is emerging every day and bloomed in every sector. Intelligent Transportation System (ITS) is one of the important branches of Automation. The major constrain in the transportation system is traffic congestion. This slurps the individual’s time and consequently pollutes the environment. A centralized management is required for optimizing the transportation system. The current traffic condition is predicted by evaluating the historical data and thereby it reduces the traffic congestion. The periodic update of traffic condition in each and every street of the city is obtained and the data is transferred to the autonomous vehicle. These data are obtained from the simulation results of transportation prediction tool SUMO. It is proved that our proposed work reduces the traffic congestion and maintains ease traffic flow and preserves the fleet management.

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.

scholarly journals A Qualitative Exploration of Practitioners’ Understanding of and Response to Child-to-Parent Aggression

2020 ◽  
pp. 088626052096714
Author(s):  
Sarah E. O’Toole ◽  
Stella Tsermentseli ◽  
Athanasia Papastergiou ◽  
Claire P. Monks
Keyword(s):  
Risk Factors ◽  
Focus Groups ◽  
Thematic Analysis ◽  
Youth Justice ◽  
The United Kingdom ◽  
Effective Policy ◽  
Qualitative Exploration ◽  
And Control ◽  
Detrimental Impact ◽  
Research And Policy

There has been limited research and policy directed toward defining and understanding child-to-parent aggression (CPA), resulting in inconsistent definitions, understandings, and responses, which has a detrimental impact on families. In particular, there have been limited qualitative studies of those working on the frontline of CPA, hindering the development of effective policy. The present qualitative study therefore aimed to explore practitioner perspectives of CPA. Twenty-five practitioners from diverse fields (e.g., youth justice, police, charities) participated in four focus groups relating to their experiences of working with CPA in the United Kingdom. Thematic analysis of focus groups revealed three key themes: definitions of CPA, understanding of CPA risk factors, and responding to CPA. Practitioners understood CPA to be a broad use of aggression to intimidate and control parents and highlighted a range of individual (e.g., mental health, substance abuse) and social (e.g., parenting, gangs) risk factors for CPA. Further, practitioners felt that current methods of reporting CPA were ineffective and may have a detrimental impact on families. The findings of this study have implications for CPA policy and support the need for a multiagency and coordinated strategy for responding to CPA.

Economic Effects of Automated Vehicles

2017 ◽  
Vol 2606 (1) ◽  
pp. 106-114 ◽  
Author(s):  
Lewis M. Clements ◽  
Kara M. Kockelman
Keyword(s):  
Automotive Industry ◽  
Autonomous Vehicles ◽  
Travel Demand ◽  
Autonomous Vehicle ◽  
The United States ◽  
Economic Effects ◽  
Legal Services ◽  
Automotive Market ◽  
Reduction Of Pain ◽  
Pain And Suffering

Connected and fully automated or autonomous vehicles (CAVs) may soon dominate the automotive industry. Once CAVs are sufficiently reliable and affordable, they will penetrate markets and thereby generate economic ripple effects throughout industries. This paper synthesizes and expands on existing analyses of the economic effects of CAVs in the United States across 13 industries and the overall economy. CAVs will soon be central to the automotive industry, with software composing a greater share of vehicle value than previously. The number of vehicles purchased each year may fall because of vehicle sharing, but rising travel distances may increase vehicle sales. The opportunity for heavy-truck drivers to do other work or rest during long drives may lower freight costs and increase capacity. Personal transport may shift toward shared autonomous vehicle fleet use, reducing that of taxis, buses, and other forms of group travel. Fewer collisions and more law-abiding vehicles will lower demand for auto repair, traffic police, medical, insurance, and legal services. CAVs will also lead to new methods for managing travel demand and the repurposing of curbside and off-street parking and will generate major savings from productivity gains during hands-free travel and reduction of pain and suffering costs from crashes. If CAVs eventually capture a large share of the automotive market, they are estimated to have economic impacts of $1.2 trillion or $3,800 per American per year. This paper presents important considerations for CAVs’ overall effects and quantifies those impacts.

scholarly journals Vehicle Electrification Impacts on Energy Consumption for Different Connected-Autonomous Vehicle Scenario Runs

2019 ◽  
Vol 11 (1) ◽  
pp. 9
Author(s):  
Ehsan Sabri Islam ◽  
Ayman Moawad ◽  
Namdoo Kim ◽  
Aymeric Rousseau
Keyword(s):  
Energy Consumption ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Transportation System ◽  
Regional Energy ◽  
Energy Impact ◽  
Potential Factors ◽  
The Impact ◽  
The City

Transportation system simulation is a widely accepted approach to evaluate the impact of transport policy deployment. In developing a transportation system deployment model, the energy impact of the model is extremely valuable for sustainability and validation. It is expected that different penetration levels of Connected-Autonomous Vehicles (CAVs) will impact travel behavior due to changes in potential factors such as congestion, miles traveled, etc. Along with such impact analyses, it is also important to further quantify the regional energy impact of CAV deployment under different factors of interest. The objective of this paper is to study the energy consumption of electrified vehicles in the future for different penetration levels of CAVs deployment in the City of Chicago. The paper will further provide a statistical analysis of the results to evaluate the impact of the different penetration levels on the different electrified powertrains used in the study.

scholarly journals Conjoint Vehicle License Plate Identification System

2020 ◽  
Vol 14 (1) ◽  
pp. 164-173
Author(s):  
Yair Wiseman
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Automatic Identification ◽  
Identification System ◽  
License Plate ◽  
Vehicle Identification ◽  
Parking Lot ◽  
High Level ◽  
Identification Techniques ◽  
The City

Background: An autonomous vehicle will go unaccompanied to park itself in a remote parking lot without a driver or a passenger inside. Unlike traditional vehicles, an autonomous vehicle can drop passengers off near any location. Afterward, instead of cruising for a nearby free parking, the vehicle can be automatically parked in a remote parking lot which can be in a rural fringe of the city where inexpensive land is more readily available. Objective: The study aimed at avoidance of mistakes in the identification of the vehicle with the help of the automatic identification device. Methods: It is proposed to back up license plate identification procedure by making use of three distinct identification techniques: RFID, Bluetooth and OCR with the aim of considerably reducing identification mistakes. Results: The RFID is the most reliable identification device but the Bluetooth and the OCR can improve the reliability of RFID. Conclusion: A very high level of reliable vehicle identification device is achievable. Parking lots for autonomous vehicles can be very efficient and low-priced. The critical difficulty is to automatically make sure that the autonomous vehicle is correctly identified at the gate.

Listening-Related Fatigue in Children With Hearing Loss: Perspectives of Children, Parents, and School Professionals

2021 ◽  
pp. 1-12
Author(s):  
Hilary Davis ◽  
David Schlundt ◽  
Kemberlee Bonnet ◽  
Stephen Camarata ◽  
Benjamin Hornsby ◽  
...  
Keyword(s):  
Hearing Loss ◽  
Focus Groups ◽  
Process Analysis ◽  
Pediatric Population ◽  
Theoretical Framework ◽  
Negative Consequences ◽  
Profound Hearing Loss ◽  
School Professionals ◽  
Stakeholder Groups ◽  
Children With Hearing Loss

Purpose Children with hearing loss (CHL) are considered at risk for listening-related fatigue and its negative consequences. We collected data via focus groups and interviews from three stakeholder groups—CHL, their parents, and teachers/school professionals—in order to define the construct of listening-related fatigue from the perspective of CHL and key stakeholders. This is an important first step in our long-term goal to construct and validate a measure (i.e., scale) of listening-related fatigue for the pediatric population, with a focus on CHL. This article provides an overview of the data gathering process, analysis of qualitative reports, and the development of a theoretical framework for understanding the experience of listening-related fatigue in CHL. Method We conducted focus groups and interviews in school-age children exhibiting bilateral, moderate-to-profound hearing loss ( n = 43), their parents ( n = 17), and school professionals who work with CHL ( n = 28). The discussions were audio-recorded, transcribed, and coded using a hierarchical coding system. Qualitative analysis was conducted using an iterative inductive–deductive approach. Results We identified primary themes from the focus group/interview discussions to develop a theoretical framework of listening-related fatigue in CHL. The framework demonstrates the complex interaction among situational determinants that impact fatigue, symptoms or manifestations of fatigue, and the utilization of, and barriers to, coping strategies to reduce listening-related fatigue. Conclusions Participant discussion suggests that listening-related fatigue is a significant problem for many, but not all, CHL. Qualitative data obtained from these stakeholder groups help define the construct and provide a framework for better understanding listening-related fatigue in children.

scholarly journals Shared Autonomous Vehicles Effect on Vehicle-Km Traveled and Average Trip Duration

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Ana T. Moreno ◽  
Andrzej Michalski ◽  
Carlos Llorca ◽  
Rolf Moeckel
Keyword(s):  
Metropolitan Area ◽  
Autonomous Vehicles ◽  
Online Survey ◽  
Travel Demand ◽  
Stated Preference ◽  
Autonomous Vehicle ◽  
Trip Duration ◽  
Conventional Vehicle ◽  
Willingness To Use ◽  
The Impact

Intermediate modes of transport, such as shared vehicles or ride sharing, are starting to increase their market share at the expense of traditional modes of car, public transport, and taxi. In the advent of autonomous vehicles, single occupancy shared vehicles are expected to substitute at least in part private conventional vehicle trips. The objective of this paper is to estimate the impact of shared autonomous vehicles on average trip duration and vehicle-km traveled in a large metropolitan area. A stated preference online survey was designed to gather data on the willingness to use shared autonomous vehicles. Then, commute trips and home-based other trips were generated microscopically for a synthetic population in the greater Munich metropolitan area. Individuals who traveled by auto were selected to switch from a conventional vehicle to a shared autonomous vehicle subject to their willingness to use them. The effect of shared autonomous vehicles on urban mobility was assessed through traffic simulations in MATSim with a varying autonomous taxi fleet size. The results indicated that the total traveled distance increased by up to 8% after autonomous fleets were introduced. Current travel demand can still be satisfied with an acceptable waiting time when 10 conventional vehicles are replaced with 4 shared autonomous vehicles.

scholarly journals Self-driving cars and liability in traffic - reality or fiction?

2018 ◽  
pp. 769-776
Author(s):  
Natasa Tomic-Petrovic
Keyword(s):  
Autonomous Vehicles ◽  
Technological Development ◽  
Autonomous Vehicle ◽  
Legal Framework ◽  
The Self ◽  
Public And Private ◽  
The Public ◽  
Private Transportation ◽  
Self Driving Cars ◽  
The City

Self-driving vehicles are considered to be the technology that will change the city, public and private transportation, as well as the concept of mobility in general. The great obstacle to self-driving vehicles are legal conditions, although the situation in this area is slowly changing. It is indeed true that producers need to gain more experience in testing vehicles without a driver on public roads before this technology is offered to the general public. The expansion of autonomous vehicles will depend on the public belief that the self-driving cars are considerably safer than those manually-controlled. Lawmakers intercede in favor of a balance between security and technological development. There should not be place for unsafe technologies on the roads, but the solution is not to prevent the easier way for vehicles that improve safety to reach consumers. If a man is not driving the vehicle, that appoints responsibility to the manufacturer of the self-driving operating system of the car in the event of a collision. Clarification of the blame for the accident will sometimes entail complex issues of allocating responsibility of man as the driver and those who provide technology of autonomous vehicle. The issue of privacy of the owner is also one of the current ones, because these data could be misused. Protection of privacy of the passenger should be in balance with the gain that the utilization of data brings. Self-driving cars may have to wait if the existing legal framework does not offer sufficient legal certainty.

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