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 An Efficiency Enhancing Methodology for Multiple Autonomous Vehicles in an Urban Network Adopting Deep Reinforcement Learning

2021 ◽  
Vol 11 (4) ◽  
pp. 1514 ◽  
Author(s):  
Quang-Duy Tran ◽  
Sang-Hoon Bae
Keyword(s):  
Reinforcement Learning ◽  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Penetration Rate ◽  
Autonomous Vehicle ◽  
Effective Means ◽  
Urban Network ◽  
Learning Agents ◽  
Policy Optimization ◽  
The Impact

To reduce the impact of congestion, it is necessary to improve our overall understanding of the influence of the autonomous vehicle. Recently, deep reinforcement learning has become an effective means of solving complex control tasks. Accordingly, we show an advanced deep reinforcement learning that investigates how the leading autonomous vehicles affect the urban network under a mixed-traffic environment. We also suggest a set of hyperparameters for achieving better performance. Firstly, we feed a set of hyperparameters into our deep reinforcement learning agents. Secondly, we investigate the leading autonomous vehicle experiment in the urban network with different autonomous vehicle penetration rates. Thirdly, the advantage of leading autonomous vehicles is evaluated using entire manual vehicle and leading manual vehicle experiments. Finally, the proximal policy optimization with a clipped objective is compared to the proximal policy optimization with an adaptive Kullback–Leibler penalty to verify the superiority of the proposed hyperparameter. We demonstrate that full automation traffic increased the average speed 1.27 times greater compared with the entire manual vehicle experiment. Our proposed method becomes significantly more effective at a higher autonomous vehicle penetration rate. Furthermore, the leading autonomous vehicles could help to mitigate traffic congestion.

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 Assessment of Social Acceptance for Autonomous Vehicles in Southeastern Poland

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5778
Author(s):  
Agnieszka Dudziak ◽  
Monika Stoma ◽  
Andrzej Kuranc ◽  
Jacek Caban
Keyword(s):  
Autonomous Vehicles ◽  
Social Acceptance ◽  
New Technologies ◽  
Consumer Preferences ◽  
Autonomous Vehicle ◽  
Developed Countries ◽  
Automotive Market ◽  
Advantages And Disadvantages ◽  
Autonomous Cars ◽  
The Impact

New technologies reaching out for meeting the needs of an aging population in developed countries have given rise to the development and gradual implementation of the concept of an autonomous vehicle (AV) and have even made it a necessity and an important business paradigm. However, in parallel, there is a discussion about consumer preferences and the willingness to pay for new car technologies and intelligent vehicle options. The main aim of the study was to analyze the impact of selected factors on the perception of the future of autonomous cars by respondents from the area of Southeastern Poland in terms of a comparison with traditional cars, with particular emphasis on the advantages and disadvantages of this concept. The research presented in this study was conducted in 2019 among a group of 579 respondents. Data analysis made it possible to identify potential advantages and disadvantages of the concept of introducing autonomous cars. A positive result of the survey is that 68% of respondents stated that AV will be gradually introduced to our market, which confirms the high acceptance of this technology by Poles. The obtained research results may be valuable information for governmental and local authorities, but also for car manufacturers and their future users. It is an important issue in the area of shaping the strategy of actions concerning further directions of development on the automotive market.

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 CONGESTION EFFECTS OF AUTONOMOUS TAXI FLEETS

Transport ◽  
2018 ◽  
Vol 33 (4) ◽  
pp. 971-980 ◽  
Author(s):  
Michal Maciejewski ◽  
Joschka Bischoff
Keyword(s):  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Large Scale ◽  
Traffic Volume ◽  
City Centre ◽  
Conventional Vehicle ◽  
Road Capacity ◽  
Private Car ◽  
The One ◽  
The Impact

Fleets of shared Autonomous Vehicles (AVs) could replace private cars by providing a taxi-like service but at a cost similar to driving a private car. On the one hand, large Autonomous Taxi (AT) fleets may result in increased road capacity and lower demand for parking spaces. On the other hand, an increase in vehicle trips is very likely, as travelling becomes more convenient and affordable, and additionally, ATs need to drive unoccupied between requests. This study evaluates the impact of a city-wide introduction of ATs on traffic congestion. The analysis is based on a multi-agent transport simulation (MATSim) of Berlin (Germany) and the neighbouring Brandenburg area. The central focus is on precise simulation of both real-time AT operation and mixed autonomous/conventional vehicle traffic flow. Different ratios of replacing private car trips with AT trips are used to estimate the possible effects at different stages of introducing such services. The obtained results suggest that large fleets operating in cities may have a positive effect on traffic if road capacity increases according to current predictions. ATs will practically eliminate traffic congestion, even in the city centre, despite the increase in traffic volume. However, given no flow capacity improvement, such services cannot be introduced on a large scale, since the induced additional traffic volume will intensify today’s congestion.

scholarly journals The Impact of Social Influence, Technophobia, and Perceived Safety on Autonomous Vehicle Technology Adoption

2019 ◽  
Vol 48 (2) ◽  
pp. 133-142
Author(s):  
Sahil Koul ◽  
Ali Eydgahi
Keyword(s):  
Technology Adoption ◽  
Social Influence ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Negative Relationship ◽  
Future Research ◽  
Intention To Use ◽  
Perceived Safety ◽  
Vehicle Technology ◽  
The Impact

The objective of this study was to determine whether there was a relationship between social influence, technophobia, perceived safety of autonomous vehicle technology, number of automobile-related accidents and the intention to use autonomous vehicles. The methodology was a descriptive, cross-sectional, correlational study. Theory of Planned Behavior provided the underlying theoretical framework. An online survey was the primary method of data collection. Pearson’s correlation and multiple linear regression were used for data analysis. This study found that both social influence and perceived safety of autonomous vehicle technology had significant, positive relationships with the intention to use autonomous vehicles. Additionally, a significant negative relationship was found among technophobia and intention to use autonomous vehicles. However, no relationship was found between the number of automobile-related accidents and intention to use autonomous vehicles. This study presents several original and significant findings as a contribution to the literature on autonomous vehicle technology adoption and proposes new dimensions of future research within this emerging field.

scholarly journals Public Preferences and Willingness to Pay for Shared Autonomous Vehicles Services in Nagoya, Japan

Smart Cities ◽  
2019 ◽  
Vol 2 (2) ◽  
pp. 230-244 ◽  
Author(s):  
Mingyang Hao ◽  
Yanyan Li ◽  
Toshiyuki Yamamoto
Keyword(s):  
Willingness To Pay ◽  
Autonomous Vehicles ◽  
Stated Preference ◽  
Autonomous Vehicle ◽  
Transportation Mode ◽  
Public Preferences ◽  
Socioeconomic Characteristics ◽  
On Demand ◽  
Vehicle Systems ◽  
The Relationship

Shared autonomous vehicle systems are anticipated to offer cleaner, safer, and cheaper mobility services when autonomous vehicles are finally implemented on the roads. The evaluation of people’s intentions regarding shared autonomous vehicle services appears to be critical prior to the promotion of this emerging mobility on demand approach. Based on a stated preference survey in Nagoya, Japan, the preference for shared autonomous vehicle services as well as willingness to pay for these services were examined among 1036 respondents in order to understand the relationship between people’s socioeconomic characteristics and their preferred shared autonomous vehicle services. For this purpose, k-modes clustering technique was selected and six clusters were obtained. Six groups with respect to different interests on shared autonomous vehicle services were clustered. The result of correlation analysis and discussion of willingness to pay on services provided insightful results for the future shared autonomous vehicle services. This study not only aids in revealing the demands of customer different clusters, but also states the prospective needs of users for stakeholders from research, policymaker and industry field, who are preparing to work on promoting shared autonomous vehicle systems, and subsequently, develops an optimum transportation mode by considering both demand and services as a whole.

Effect of connected and autonomous vehicles on traffic flow at a bidirectional road

2021 ◽  
Author(s):  
H. Echab ◽  
A. Khallouk ◽  
H. Ez-Zahraouy
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Negative Influence ◽  
Conventional Vehicle ◽  
Cooperative Driving ◽  
Moving Vehicles ◽  
Penetration Ratio ◽  
Slow Moving ◽  
The Impact ◽  
Cv Model

The objective of this study was to investigate the impact of connected and autonomous vehicles (CAVs) on traffic flow under various parameters. For this purpose, we propose a mixed CAV and conventional vehicle (CV) model to investigate a bidirectional two-lane traffic flow under the periodic boundary condition. The traffic flux and the phase diagrams of the system in the ([Formula: see text]) area are constructed in both cases: with and without CAVs. The overtaking frequency is also calculated. The simulation findings show that the traffic capacity is greatly enhanced with the increase in the CAV penetration ratio. Owing to the cooperative driving strategy, with the increase in penetration ratio of the CAV, the portion of smooth overtaking is boosted. Furthermore, it is found that the traffic throughput is positively correlated to the speed limit of the fast vehicle where the flux increases as [Formula: see text] increases. Also, even if there is a low rate of slow moving vehicles in the system, it will have an appreciable and a significant negative influence.

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.

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