Journal articles on the topic 'Private autonomous vehicles'
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Feys, Manon, Evy Rombaut, and Lieselot Vanhaverbeke. "Does a Test Ride Influence Attitude towards Autonomous Vehicles? A Field Experiment with Pretest and Posttest Measurement." Sustainability 13, no. 10 (May 12, 2021): 5387. http://dx.doi.org/10.3390/su13105387.
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Autonomous vehicles have the potential to disrupt the mobility system. Therefore, it is important to understand attitude formation towards autonomous vehicles. The focus of this study is on the private user’s technology acceptance of an autonomous vehicle. The study applies the determinants of technology acceptance to capture users’ attitude towards and intention to adopt autonomous vehicles. A field experiment with 27 participants was conducted to assess changes in determinants before and after a test ride with a level 2 automated vehicle. The automated vehicle was equipped with technology that allowed a hands-off, feet-off experience on a public road in real traffic. The results show that a ride has a positive and significant effect on attitudes towards autonomous vehicles. Additionally, participants with higher ratings of technology anxiety show a remarkable increase in attitude towards autonomous vehicles after the ride compared to participants with lower levels of technology anxiety. These findings indicate that experience with a partially automated vehicle has a potentially positive effect on the acceptance of autonomous vehicles. As such, our study illustrates the importance of continuous pilot testing with private automated vehicles to increase future user acceptance of autonomous vehicles.
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Schlenther, Tilmann, Kai Martins-Turner, Joschka Felix Bischoff, and Kai Nagel. "Potential of Private Autonomous Vehicles for Parcel Delivery." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 11 (September 10, 2020): 520–31. http://dx.doi.org/10.1177/0361198120949878.
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Using the same vehicles for both passenger and freight transport, to increase vehicle occupancy and decrease their number, is an idea that drives transport planners and is also being addressed by manufacturers. This paper proposes a methodology to simulate the behavior of such vehicles within an urban traffic system and evaluate their performance. The aim is to investigate the impacts of resignation from fleet ownership by a transport service company (TSC) operating on a city-wide scale. In the simulation, the service provider hires private autonomous cars for tour performance. Based on assumptions concerning the operation of such vehicles and TSCs, the software Multi-Agent Transport Simulation (MATSim) is extended to model vehicle and operator behavior. The proposed framework is applied to a case study of a parcel delivery service in Berlin serving a synthetic parcel demand. Results suggest that the vehicle miles traveled for freight purposes increase because of additional access and egress trips. Moreover, the number of vehicles en route is higher throughout the day. The lowering of driver costs can reduce the costs of the operator by approximately 74.5%. If the service provider additionally considers the resignation from fleet ownership, it might lower the operation cost by another 10%, not taking into account the costs of system transfer or risks like vehicle non-availability. From an economic perspective, the reduction of the overall number of vehicles in the system seems to be beneficial.
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Moreno, Ana T., Andrzej Michalski, Carlos Llorca, and Rolf Moeckel. "Shared Autonomous Vehicles Effect on Vehicle-Km Traveled and Average Trip Duration." Journal of Advanced Transportation 2018 (2018): 1–10. http://dx.doi.org/10.1155/2018/8969353.
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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.
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Obaid, Mohammed, Arpad Torok, and Jairo Ortega. "A Comprehensive Emissions Model Combining Autonomous Vehicles with Park and Ride and Electric Vehicle Transportation Policies." Sustainability 13, no. 9 (April 22, 2021): 4653. http://dx.doi.org/10.3390/su13094653.
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Several transport policies reduce pollution levels caused by private vehicles by introducing autonomous or electric vehicles and encouraging mode shift from private to public transport through park and ride (P&R) facilities. However, combining the policies of introducing autonomous vehicles with the implementation of electric vehicles and using the P&R system could amplify the decrease of transport sector emissions. The COPERT software has been used to calculate the emissions. This article aims to study these policies and determine which combinations can better reduce pollution. The result shows that each combination of autonomous vehicles reduces pollution to different degrees. In conclusion, the shift to more sustainable transport modes through autonomous electric vehicles and P&R systems reduces pollution in the urban environment to a higher percentage. In contrast, the combination of autonomous vehicles has lower emission reduction but is easier to implement with the currently available infrastructure.
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Obaid, Mohammed, and Arpad Torok. "Macroscopic Traffic Simulation of Autonomous Vehicle Effects." Vehicles 3, no. 2 (April 29, 2021): 187–96. http://dx.doi.org/10.3390/vehicles3020012.
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The increasing worldwide demand on urban road transportation systems requires more restrictive measures and policies to reduce congestion, time delay and pollution. Autonomous vehicle mobility services, both shared and private, are possibly a good step towards a better road transportation future. This article aims to study the expected impact of private autonomous vehicles on road traffic parameters from a macroscopic level. The proposed methodology focuses on finding the different effects of different combinations of autonomous vehicle penetration and Passenger Car Units (PCU) on the chosen road traffic model. Four parameters are studied: traveled daily kilometers, daily hours, total daily delay and average network speed. The analysis improves the four parameters differently by implementing autonomous vehicles. The parameter total delay has the most significant reduction. Finally, several mathematical models are developed for the percentage of improvement for each chosen parameter.
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Guo, Hao, Yao Chen, and Yang Liu. "Shared autonomous vehicle management considering competition with human-driven private vehicles." Transportation Research Part C: Emerging Technologies 136 (March 2022): 103547. http://dx.doi.org/10.1016/j.trc.2021.103547.
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Tan, Limin, Changxi Ma, Xuecai Xu, and Jin Xu. "Choice Behavior of Autonomous Vehicles Based on Logistic Models." Sustainability 12, no. 1 (December 19, 2019): 54. http://dx.doi.org/10.3390/su12010054.
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To understand the public’s acceptance of autonomous vehicles, studies were conducted from the perspectives of personal attributes, travel demand and cognitions of autonomous vehicles based on 403 valid questionnaires. Influencing factors of whether travelers are purchasing autonomous vehicles, whether travelers without a driver’s license intend to take a driver’s license in the future and whether travelers are choosing an autonomous private car if travelers can only take a taxi or drive a private car are analyzed by building Logistic regression models. The results show that personal monthly income, driver’s license, driving confidence, preference for autonomous vehicles and convenience of arriving at public transport stations will affect the purchase decision of autonomous vehicles; teenagers, long-distance travelers, students and employees of enterprises and institutions, those who believe that traditional taxis/taxi-hailing are unsafe, and those who lack confidence in driving have a higher probability of choosing autonomous vehicles. This research can be used to predict the probability of future purchase and use decisions for autonomous vehicles based on data from other populations.
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Polydoropoulou, Amalia, Ioannis Tsouros, Nikolas Thomopoulos, Cristina Pronello, Arnór Elvarsson, Haraldur Sigþórsson, Nima Dadashzadeh, et al. "Who Is Willing to Share Their AV? Insights about Gender Differences among Seven Countries." Sustainability 13, no. 9 (April 23, 2021): 4769. http://dx.doi.org/10.3390/su13094769.
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The introduction of shared autonomous vehicles into the transport system is suggested to bring significant impacts on traffic conditions, road safety and emissions, as well as overall reshaping travel behaviour. Compared with a private autonomous vehicle, a shared automated vehicle (SAV) is associated with different willingness-to-adopt and willingness-to-pay characteristics. An important aspect of future SAV adoption is the presence of other passengers in the SAV—often people unknown to the cotravellers. This study presents a cross-country exploration of user preferences and WTP calculations regarding mode choice between a private non-autonomous vehicle, and private and shared autonomous vehicles. To explore user preferences, the study launched a survey in seven European countries, including a stated-preference experiment of user choices. To model and quantify the effect of travel mode attributes and socio-demographic characteristics, the study employs a mixed logit model. The model results were the basis for calculating willingness-to-pay values for all countries and travel modes, and provide insight into the significant heterogeneous, gender-wise effect of cotravellers in the choice to use an SAV. The study results highlight the importance of analysis of the effect of SAV attributes and shared-ride conditions on the future acceptance and adoption rates of such services.
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Metz, David. "Developing Policy for Urban Autonomous Vehicles: Impact on Congestion." Urban Science 2, no. 2 (April 13, 2018): 33. http://dx.doi.org/10.3390/urbansci2020033.
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An important problem for surface transport is road traffic congestion, which is ubiquitous and difficult to mitigate. Accordingly, a question for policymakers is the possible impact on congestion of autonomous vehicles. It seems likely that the main impact of vehicle automation will not be seen until driverless vehicles are sufficiently safe for use amid general traffic on urban streets. Shared use driverless vehicles could reduce the cost of taxis and a wider range of public transport vehicles could be economic. Individually owned autonomous vehicles would have the ability to travel unoccupied and may need to be regulated where this might add to congestion. It is possible that autonomous vehicles could provide mobility services at lower cost and wider scope, such that private car use in urban areas could decline and congestion reduce. City authorities should be alert to these possibilities in developing transport policy.
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Zhang, Wenwen, Subhrajit Guhathakurta, and Elias B. Khalil. "The impact of private autonomous vehicles on vehicle ownership and unoccupied VMT generation." Transportation Research Part C: Emerging Technologies 90 (May 2018): 156–65. http://dx.doi.org/10.1016/j.trc.2018.03.005.
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Martin, George. "A Sustainability Interrogation of the Autonomous Vehicle at Its Society-Technology Interface." Bulletin of Science, Technology & Society 39, no. 3-4 (October 2019): 23–32. http://dx.doi.org/10.1177/0270467620965466.
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This analysis of the emergent automated vehicle technology focuses on the friction at its interface with society, clouding its future. The sequential focus of development → deployment is reconfigured as reciprocal: society ↔ technology. A best path forward is presented that incorporates environmental and social sustainability factors as they relate to climate change and public health. The path’s signpost is automated electric vehicles deployed in public and private fleets. This course has promise to recover automobility from the damaging, unsustainable legacy of personal internal combustion vehicles—highlighted by their toxic and carbon emissions, and road casualties.
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Das, Subasish, Anandi Dutta, Tomas Lindheimer, Mohammad Jalayer, and Zachary Elgart. "YouTube as a Source of Information in Understanding Autonomous Vehicle Consumers: Natural Language Processing Study." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 8 (April 17, 2019): 242–53. http://dx.doi.org/10.1177/0361198119842110.
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The automotive industry is currently experiencing a revolution with the advent and deployment of autonomous vehicles. Several countries are conducting large-scale testing of autonomous vehicles on private and even public roads. It is important to examine the attitudes and potential concerns of end users towards autonomous cars before mass deployment. To facilitate the transition to autonomous vehicles, the automotive industry produces many videos on its products and technologies. The largest video sharing website, YouTube.com, hosts many videos on autonomous vehicle technology. Content analysis and text mining of the comments related to the videos with large numbers of views can provide insight about potential end-user feedback. This study examines two questions: first, how do people view autonomous vehicles? Second, what polarities exist regarding (a) content and (b) automation level? The researchers found 107 videos on YouTube using a related keyword search and examined comments on the 15 most-viewed videos, which had a total of 60.9 million views and around 25,000 comments. The videos were manually clustered based on their content and automation level. This study used two natural language processing (NLP) tools to perform knowledge discovery from a bag of approximately seven million words. The key issues in the comment threads were mostly associated with efficiency, performance, trust, comfort, and safety. The perception of safety and risk increased in the textual contents when videos presented full automation level. Sentiment analysis shows mixed sentiments towards autonomous vehicle technologies, however, the positive sentiments were higher than the negative.
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Hasan, Umair, Andrew Whyte, and Hamad Al Jassmi. "A Review of the Transformation of Road Transport Systems: Are We Ready for the Next Step in Artificially Intelligent Sustainable Transport?" Applied System Innovation 3, no. 1 (December 19, 2019): 1. http://dx.doi.org/10.3390/asi3010001.
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Mobility is experiencing a revolution, as advanced communications, computers with big data capacities, efficient networks of sensors, and signals, are developing value-added applications such as intelligent spaces and autonomous vehicles. Another new technology that is both promising and might even be pervasive for faster, safer and more environmentally-friendly public transport (PT) is the development of autonomous vehicles (AVs). This study aims to understand the state of the current research on the artificially intelligent transportation system (ITS) and AVs through a critical evaluation of peer-reviewed literature. This study’s findings revealed that the majority of existing research (around 82% of studies) focused on AVs. Results show that AVs can potentially reduce more than 80% of pollutant emissions per mile if powered by alternate energy resources (e.g., natural gas, biofuel, electricity, hydrogen cells, etc.). Not only can private vehicle ownership be cut down by bringing in ridesharing but the average vehicle miles travelled (VMT) should also be reduced through improved PT. The main benefits of AV adoption were reported in the literature to be travel time, traffic congestion, cost and environmental factors. Findings revealed barriers such as technological uncertainties, lack of regulation, unawareness among stakeholders and privacy and security concerns, along with the fact that lack of simulation and empirical modelling data from pilot studies limit the application. AV–PT was also found to be the most sustainable strategy in dense urban areas to shift the heavy trip load from private vehicles.
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Maciejewski, Michal, and Joschka Bischoff. "CONGESTION EFFECTS OF AUTONOMOUS TAXI FLEETS." Transport 33, no. 4 (December 5, 2018): 971–80. http://dx.doi.org/10.3846/16484142.2017.1347827.
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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.
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Tak, Sehyun, Soomin Woo, Sungjin Park, and Sunghoon Kim. "The City-Wide Impacts of the Interactions between Shared Autonomous Vehicle-Based Mobility Services and the Public Transportation System." Sustainability 13, no. 12 (June 14, 2021): 6725. http://dx.doi.org/10.3390/su13126725.
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When attempts are made to incorporate shared autonomous vehicles (SAVs) into urban mobility services, public transportation (PT) systems are affected by the changes in mode share. In light of that, a simulation-based method is presented herein for analyzing the manner in which mode choices of local travelers change between PT and SAVs. The data used in this study were the modal split ratios measured based on trip generation in the major cities of South Korea. Subsequently, using the simulated results, a city-wide impact analysis method is proposed that can reflect the differences between the two mode types with different travel behaviors. As the supply–demand ratio of SAVs increased in type 1 cities, which rely heavily on PT, use of SAVs gradually increased, whereas use of PT and private vehicles decreased. Private vehicle numbers significantly reduced only when SAVs and PT systems were complementary. In type 2 cities, which rely relatively less on PT, use of SAVs gradually increased, and use of private vehicles decreased; however, no significant impact on PT was observed. Private vehicle numbers were observed to reduce when SAVs were operated, and the reduction was a minimum of thrice that in type 1 cities when SAVs and PT systems interacted. Our results can therefore aid in the development of strategies for future SAV–PT operations.
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Tomic-Petrovic, Natasa. "Self-driving cars and liability in traffic - reality or fiction?" Zbornik Matice srpske za drustvene nauke, no. 168 (2018): 769–76. http://dx.doi.org/10.2298/zmsdn1868769t.
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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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Epstein, Richard A. "Liability rules for autonomous vehicles." Journal of Entrepreneurship and Public Policy 10, no. 2 (March 4, 2021): 218–34. http://dx.doi.org/10.1108/jepp-03-2019-0008.
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PurposeThe coming use of autonomous vehicles has kindled an extensive debate over the choice of a desirable liability regime. This article contributes to that debate by explaining how rules for liability and damages ought to be constructed to deal first with stranger (including highway) cases and then with consensual cases (like medical malpractice). It concludes that an output regime based on events as they unfold is applicable in the former but not in the latter. It then argues that this legal regime carries over without a hitch to autonomous vehicles. It then further notes that in private disputes there are no fixed rules for deciding how to mix rules for injunctions and liabilities for threatened harms, and further notes that the regulatory regime for IoT will face those same difficulties, which are best solved by trying to minimize the sum of Type I and Type II errors, as in other cases.Design/methodology/approachLegal reasoning/analysis.FindingsOne salient point is that the rules of the road should change in response to technical innovation, but liability rules should not. The sound approach for dealing with damages for past incidents ought to be constructed to deal first with stranger (including highway) cases in which there is a dichotomous decision on compliance or not. That regime is based on events as they unfold, and carries over without a hitch to autonomous vehicles. For dealing with the prevention of future harms from violation of these rules, by contrast, there are no fixed rules for deciding how to mix damages with injunction, and the substitution of a system of direct state enforcement faces the same difficulties of implementation. In both settings, the rules of the road should be held constant, after which the ideal remedial mix follows the traditional approach of trying to minimize the sum of Type I and Type II errors, relating to over and underenforcement. The basic rules of tort liability stand in contrast to the different standards of liability that arise in consensual situations, and in all cases, they must necessarily be supplemented by rules of vicarious and product liability. Overall, the bottom line is this: autonomous vehicle innovations are relevant to designing regulations for future and uncertain harms, but irrelevant to liability for past harms.Originality/valueThis is an original legal analysis on the topic of Autonomous Vehicles.
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Burri, Thomas, and Isabelle Wildhaber. "Introduction to the Special Issue on the Man and the Machine." European Journal of Risk Regulation 7, no. 2 (June 2016): 295–96. http://dx.doi.org/10.1017/s1867299x00005717.
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This special issue assembles five articles ensuing from a conference on “The Man and the Machine: When Systems Take Decisions Autonomously”, which took place on June 26 and 27, 2015, at the University of St. Gallen in Switzerland.The aim of the conference was to explore the broader implications of artificial intelligence, machine learning and autonomous robots and vehicles. Alphabet's Deep Mind is just one example about Whom we know, at least a little, and who, we are told, will be good. Autonomous vehicles are also about to enter the market and our phones have begun to verbalize at us. Private drones are being regulated by the US Federal Aviation Administration. The five papers in this special issue address some of the legal issues the broader development raises.The first article is on “The Implications of Modern Business-Entity Law for the Regulation of Autonomous Systems” and is written by Shawn Bayern.
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Olakanmi, Oladayo, and Sekoni Oluwaseun. "A Trust Based Secure and Privacy Aware Framework for Efficient Taxi and Car Sharing System." International Journal of Vehicular Telematics and Infotainment Systems 2, no. 1 (January 2018): 34–47. http://dx.doi.org/10.4018/ijvtis.2018010103.
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This article describes how taxi service is an essential means of mobility in many cities. Recent findings show that average automobile owners utilize their vehicles for only 5% of its time in a day. Therefore, the advent of autonomous vehicles and car sharing will make it possible for owners to engage their vehicles as taxis when not in use by utilizing its 95% free time for income generation. Sensitive private information is required to be released during a taxi service delivery, which may bring certain security and privacy issues and challenges. This may hinder the prospect of using autonomous vehicles as a form of taxi. As a result of these, the authors propose a secure and privacy-preserving taxi service framework for car sharing, which ensures protection of car owner and passengers personal details, e.g. identity, location, destination, etc. The authors developed a decay-based trust model for a framework in order to monitor and improve the quality of service rendered to passengers by vehicles. The decay-based trust model was simulated on the framework. The simulation of the decay-based trust model shows that it is a perfect model for rewarding vehicles which render good quality of service and blacklisting vehicles with frequent poor service delivery.
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Pettigrew, Simone, Leon Booth, Victoria Farrar, Branislava Godic, Julie Brown, Charles Karl, and Jason Thompson. "Walking in the Era of Autonomous Vehicles." Sustainability 14, no. 17 (August 23, 2022): 10509. http://dx.doi.org/10.3390/su141710509.
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(1) Background: The emergence of autonomous vehicles (AVs) is likely to have substantial implications for walking behaviours due to the availability of new transport options and altered physical environments within cities. The aim of this exploratory study was to identify AV-related factors that could affect walking at the population level and strategies to ameliorate any negative effects. (2) Methods: A total of 46 Australian expert stakeholders were interviewed about their perceptions of the potential impacts of AVs on walking behaviours. The interviewees represented government departments (state and federal), non-government organisations (NGOs), private sector companies, peak bodies, and academia. (3) Results: Interviewees expected AVs to have different effects on individuals’ ability and motivation to engage in planned versus incidental walking. While those with innate motivation to walk as a form of exercise or leisure may experience enhanced participation opportunities, it appears that incidental walking could be adversely impacted through the availability of convenient AV door-to-door transport options and automated home delivery services that reduce walking related to commuting and shopping. (4) Conclusions: Proactive policy actions are needed to optimize the potential positive impacts of AVs on walking and circumvent the potential negative impacts on valuable incidental walking that constitutes a key component of many people’s total physical activity.
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Mocanu, Tudor. "What Types of Cars Will We Be Driving? Methods of Forecasting Car Travel Demand by Vehicle Type." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 49 (November 29, 2018): 125–34. http://dx.doi.org/10.1177/0361198118797457.
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New technologies are emerging in the private vehicle market. Conventional propulsion systems are set to be replaced by alternative, more environment-friendly ones (e.g., electric vehicles), and certain new features, like autonomous driving, will possibly change the way private cars are employed. To assess the impact of such technologies, one must estimate how often and for which trips these vehicle types will be used. Another issue is the exact localization of certain vehicle types on the network, to assess environmental effects and identify where specific roadside infrastructure (e.g., charging stations) will be required. This paper presents four approaches to forecasting car usage by vehicle type using a macroscopic travel demand model in combination with a vehicle fleet or technology diffusion model. Integrating the two types of models requires tools ranging from assumptions and extrapolation of empirical data to synthetic or incremental discrete choice models. The approaches are employed in a case study forecasting travel demand using privately owned autonomous vehicles (AVs) in Germany in 2030. Despite identical input data, the estimated proportion of vehicle miles traveled (VMT) using AVs varies between 11% and 23% of overall car VMT, depending on the approach chosen. The reasons for this variation in results are investigated and some recommendations are given. To avoid the difficulties of fitting a synthetic model to observed data and to increase the accuracy of the results, the recommendation is to formulate the vehicle type choice as an incremental model added to the travel demand model.
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Singh, Harprinderjot, Mohammadreza Kavianipour, Mehrnaz Ghamami, and Ali Zockaie. "Adoption of autonomous and electric vehicles in private and shared mobility systems." Transportation Research Part D: Transport and Environment 115 (February 2023): 103561. http://dx.doi.org/10.1016/j.trd.2022.103561.
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Hardinghaus, Seidel, and Anderson. "Estimating Public Charging Demand of Electric Vehicles." Sustainability 11, no. 21 (October 24, 2019): 5925. http://dx.doi.org/10.3390/su11215925.
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Electric vehicles require sufficient public charging infrastructure. This in turn necessitates detailed information on charging demand. In this paper we present a four-step approach to estimating public charging demand of electric vehicles. Previous methods are limited in their ability to provide differentiated results and adapt to future developments. Therefore, we account for user groups (private, carsharing, commercial), technical developments (vehicles, infrastructure), infrastructure availability, and carsharing development (operational area, business models, autonomous vehicles). Our approach also considers the interactions between these factors and allows for scenario analysis yielding the quantity and spatial distribution of public charging demand. We demonstrate our approach for Berlin, Germany. We find that the majority of public charging demand results from carsharing. This demand is concentrated in the city center, even when carsharing is available citywide. Public charging demand for commercial users is relatively low and located outside the city center. For private users, public charging demand shifts to the city center with an increasing market penetration of electric vehicles and technological advancements (increased range, charging speed). Public demand from private users increases dramatically when private infrastructure is absent. Finally, public charging demand shifts to the city center when private users do not have private infrastructure.
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Andrei, Liliana, Oana Luca, and Florian Gaman. "Insights from User Preferences on Automated Vehicles: Influence of Socio-Demographic Factors on Value of Time in Romania Case." Sustainability 14, no. 17 (August 30, 2022): 10828. http://dx.doi.org/10.3390/su141710828.
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New transport technologies, such as autonomous vehicles, are increasingly discussed in the debate on the transition to a sustainable urban future. Automated vehicles (AVs) are expected to reduce the value of travel time (VoT), allowing the use of time for other types of activities during travel, including working, reading, sleeping, entertainment, etc. Our study aims to provide empirical insights on future modal choice preferences for regular trips for Romanian citizens, using a sample of 309 respondents to a web survey on issues related to automated vehicles. Using multinomial logistic models (MNL), we analysed the relationship between three mode choices: regular car, private automated vehicle, and shared automated vehicle, along with the individual and household characteristics. In addition, we calculated the VoT for each mode choice based on the results of MNL analysis. Results showed that VoT is strongly influenced by travel cost and travel time, by socio-economic characteristics such as age, gender, and education, and has the lowest value for the shared AV compared with a regular car or a private AV. Future research may conduct comparable studies in European countries but also explore the opinions and perceptions of vulnerable road users on AVs and VoT.
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Lavieri, Patrícia S., Venu M. Garikapati, Chandra R. Bhat, Ram M. Pendyala, Sebastian Astroza, and Felipe F. Dias. "Modeling Individual Preferences for Ownership and Sharing of Autonomous Vehicle Technologies." Transportation Research Record: Journal of the Transportation Research Board 2665, no. 1 (January 2017): 1–10. http://dx.doi.org/10.3141/2665-01.
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Considerable interest exists in modeling and forecasting the effects of autonomous vehicles on travel behavior and transportation network performance. In an autonomous vehicle (AV) future, individuals may privately own such vehicles, use mobility-on-demand services provided by transportation network companies that operate shared AV fleets, or adopt a combination of those two options. This paper presents a comprehensive model system of AV adoption and use. A generalized, heterogeneous data model system was estimated with data collected as part of the Puget Sound, Washington, Regional Travel Study. The results showed that lifestyle factors play an important role in shaping AV usage. Younger, urban residents who are more educated and technologically savvy are more likely to be early adopters of AV technologies than are older, suburban and rural individuals, a fact that favors a sharing-based service model over private ownership. Models such as the one presented in this paper can be used to predict the adoption of AV technologies, and such predictions will, in turn, help forecast the effects of AVs under alternative future scenarios.
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Asgari, Hamidreza, and Xia Jin. "Incorporating Attitudinal Factors to Examine Adoption of and Willingness to Pay for Autonomous Vehicles." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 8 (April 25, 2019): 418–29. http://dx.doi.org/10.1177/0361198119839987.
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Results from a recent consumer survey were thoroughly analyzed in relation to willingness to adopt and willingness to pay (WTP) for different autonomous vehicle (AV) features. Four different levels of automation were considered including basic vehicles, adding advanced features, partial automation, and full automation. A structural equations model with latent variables was employed, which simultaneously regressed adoption and WTP levels against a variety of available variables including socioeconomic and demographic attributes, private car usage habits, and attitudinal preferences/personal opinions. To address the endogeneity in personal attitudes, these variables were added to the model as latent factors. Accordingly, the analysis revealed four major latent attitudinal factors, respectively labeled as “joy of driving,”“mode choice reasoning,”“trust,” and “technology savviness.” Model results indicated that those who enjoy driving were the hardest to persuade towards AV adoption or to pay for automated features. On the other hand, technology savvy people showed higher tendency towards AV adoption. When it comes to factors affecting mode choice including travel time, travel cost, and functionality, people are willing to pay more for automated features when they believe that these features and services will provide them better utility, in relation to time and cost savings, convenience, stress reduction, and quality of life, and so forth. Interestingly, individuals with trust concerns showed higher WTP values, which may indicate that the market believes autonomous vehicles will bring more privacy and protection, at least compared with existing shared mobility or public transit options.
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Williams, Eric, Vivekananda Das, and Andrew Fisher. "Assessing the Sustainability Implications of Autonomous Vehicles: Recommendations for Research Community Practice." Sustainability 12, no. 5 (March 3, 2020): 1902. http://dx.doi.org/10.3390/su12051902.
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Autonomous vehicles (AV) are poised to induce disruptive changes, with significant implications for the economy, the environment, and society. This article reviews prior research on AVs and society, and articulates future needs. Research to assess future societal change induced by AVs has grown dramatically in recent years. The critical challenge in assessing the societal implications of AVs is forecasting how consumers and businesses will use them. Researchers are predicting the future use of AVs by consumers through stated preference surveys, finding analogs in current behaviors, utility optimization models, and/or staging empirical “AV-equivalent” experiments. While progress is being made, it is important to recognize that potential behavioral change induced by AVs is massive in scope and that forecasts are difficult to validate. For example, AVs could result in many consumers abandoning private vehicles for ride-share services, vastly increased travel by minors, the elderly and other groups unable to drive, and/or increased recreation and commute miles driven due to increased utility of in-vehicle time. We argue that significantly increased efforts are needed from the AVs and society research community to ensure 1) the important behavioral changes are analyzed and 2) models are explicitly evaluated to characterize and reduce uncertainty.
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Schweizer, Joerg, Cristian Poliziani, and Federico Rupi. "Simulating platooned connected autonomous vehicle in a large scale urban scenario." SUMO Conference Proceedings 3 (September 29, 2022): 171–79. http://dx.doi.org/10.52825/scp.v3i.175.
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This article is concerned with the performance evaluation of connected, autonomous vehicles (CAVs) in a realistic large-scale microsimulation scenario. In particular the question is: how much could a high diffusion of CAVs possibly change (1)~the average travel speeds (2)~the trip times of all traffic participants, including pedestrians, and (3)~the energy/fuel consumption? For this purpose, admittedly favourable assumptions are made: a 100\% diffusion of platooning-capable CAVs as substitution for private cars as well as a high maximum speed of platooned vehiclesin order to enable platoon formation. The morning rush hour scenario of the metropolitan area of Bologna, Italy has been selected for assessment. This scenario, which has been created and validated in previous works, represents an activity based demand model with travel plans for individual citizens, including all relevant transport modes. The microsimulation is performed by means of the SUMO simulator. The entire demand has been generated with the SUMOPy tool. For the platooning of CAVs, SUMO's SIMPLA module has been used, which controlls the vehicles via the interactive TRACI API. Results show an increased speed and reduced travel time for CAV vehicles, with respect to human driven cars, in particular in the periphery and less in the center with a dense road network. However, the reason for improved speeds and travel times is predominantly the higher maximum speed allowed for vehicles trying to catch up and join a platoon. Furthermore these higher speed would also be resposible for an increase in fuel consumption of approximately 5\%. In conclusion, CAVs alone are unlikely to reduce congestion in an urban area. To make the platooning concept work, additional technology and infrastructure is required in order to merge platoons effectively at freeways and at traffic lights. The latter could be simulated with GLOSA.
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Zou, Xin, David B. Logan, and Hai L. Vu. "Modeling public acceptance of private autonomous vehicles: Value of time and motion sickness viewpoints." Transportation Research Part C: Emerging Technologies 137 (April 2022): 103548. http://dx.doi.org/10.1016/j.trc.2021.103548.
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Nazari, Fatemeh, Mohamadhossein Noruzoliaee, and Abolfazl (Kouros) Mohammadian. "Shared versus private mobility: Modeling public interest in autonomous vehicles accounting for latent attitudes." Transportation Research Part C: Emerging Technologies 97 (December 2018): 456–77. http://dx.doi.org/10.1016/j.trc.2018.11.005.
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Ma, Wei, and Sean Qian. "High-Resolution Traffic Sensing with Probe Autonomous Vehicles: A Data-Driven Approach." Sensors 21, no. 2 (January 11, 2021): 464. http://dx.doi.org/10.3390/s21020464.
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Recent decades have witnessed the breakthrough of autonomous vehicles (AVs), and the sensing capabilities of AVs have been dramatically improved. Various sensors installed on AVs will be collecting massive data and perceiving the surrounding traffic continuously. In fact, a fleet of AVs can serve as floating (or probe) sensors, which can be utilized to infer traffic information while cruising around the roadway networks. Unlike conventional traffic sensing methods relying on fixed location sensors or moving sensors that acquire only the information of their carrying vehicle, this paper leverages data from AVs carrying sensors for not only the information of the AVs, but also the characteristics of the surrounding traffic. A high-resolution data-driven traffic sensing framework is proposed, which estimates the fundamental traffic state characteristics, namely, flow, density and speed in high spatio-temporal resolutions and of each lane on a general road, and it is developed under different levels of AV perception capabilities and for any AV market penetration rate. Experimental results show that the proposed method achieves high accuracy even with a low AV market penetration rate. This study would help policymakers and private sectors (e.g., Waymo) to understand the values of massive data collected by AVs in traffic operation and management.
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Ma, Wei, and Sean Qian. "High-Resolution Traffic Sensing with Probe Autonomous Vehicles: A Data-Driven Approach." Sensors 21, no. 2 (January 11, 2021): 464. http://dx.doi.org/10.3390/s21020464.
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Recent decades have witnessed the breakthrough of autonomous vehicles (AVs), and the sensing capabilities of AVs have been dramatically improved. Various sensors installed on AVs will be collecting massive data and perceiving the surrounding traffic continuously. In fact, a fleet of AVs can serve as floating (or probe) sensors, which can be utilized to infer traffic information while cruising around the roadway networks. Unlike conventional traffic sensing methods relying on fixed location sensors or moving sensors that acquire only the information of their carrying vehicle, this paper leverages data from AVs carrying sensors for not only the information of the AVs, but also the characteristics of the surrounding traffic. A high-resolution data-driven traffic sensing framework is proposed, which estimates the fundamental traffic state characteristics, namely, flow, density and speed in high spatio-temporal resolutions and of each lane on a general road, and it is developed under different levels of AV perception capabilities and for any AV market penetration rate. Experimental results show that the proposed method achieves high accuracy even with a low AV market penetration rate. This study would help policymakers and private sectors (e.g., Waymo) to understand the values of massive data collected by AVs in traffic operation and management.
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Park, Se-Min. "A Study of Interpretation of Private liability for Accidents led by Level 3 Autonomous Vehicles." BUSINESS LAW REVIEW 33, no. 1 (March 31, 2019): 179–207. http://dx.doi.org/10.24886/blr.2019.3.33.1.179.
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Saleh, Sherine Nagy, and Cherine Fathy. "A Novel Deep-Learning Model for Remote Driver Monitoring in SDN-Based Internet of Autonomous Vehicles Using 5G Technologies." Applied Sciences 13, no. 2 (January 8, 2023): 875. http://dx.doi.org/10.3390/app13020875.
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The rapid advancement in the Internet of Things (IoT) and its integration with Artificial Intelligence (AI) techniques are expected to play a crucial role in future Intelligent Transportation Systems (ITS). Additionally, the continuous progress in the industry of autonomous vehicles will accelerate and increase their short adoption in smart cities to allow safe, sustainable and accessible trips for passengers in different public and private means of transportation. In this article, we investigate the adoption of 5G different technologies, mainly, the Software-Defined Networks (SDN) to support the communication requirements of delegation of control of level-2 autonomous vehicles to the Remote-Control Center (RCC) in terms of ultra-low delay and reliability. This delegation occurs upon the detection of a drowsy driver using our proposed deep-learning-based technique deployed at the edge to reduce the level of accidents and road congestion. The deep learning-based model was evaluated and produced higher accuracy, precision and recall when compared to other methods. The role of SDN is to implement network slicing to achieve the Quality of Service (QoS) level required in this emergency case. Decreasing the end-to-end delay required to provide feedback control signals back to the autonomous vehicle is the aim of deploying QoS support available in an SDN-based network. Feedback control signals are sent to remotely activate the stopping system or to switch the vehicle to direct teleoperation mode. The mininet-WiFi emulator is deployed to evaluate the performance of the proposed adaptive SDN framework, which is tailored to emulate radio access networks. Our simulation experiments conducted on realistic vehicular scenarios revealed significant improvement in terms of throughput and average Round-Trip Time (RTT).
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Moghaddam, Ali Alamdar, Hamid Mirzahossein, and Robert Guzik. "Comparing Inequality in Future Urban Transport Modes by Doughnut Economy Concept." Sustainability 14, no. 21 (November 3, 2022): 14462. http://dx.doi.org/10.3390/su142114462.
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Inequality is a problem facing the world community, especially in developing countries, that affects urban transport and vice versa. Which possible urban transportation mode will cause the least inequality? This is a vital question. The development of Autonomous vehicles (AV) has made Shared Autonomous Vehicles (SAV) one of the future transport modes. Active and public transport are also mentioned as applicable future modes, based on the literature. This paper aims to compare inequality in active transportation, public transport and SAV as the most important alternatives to private cars in the future. In this regard, we use doughnut economic concepts as the framework for our comparison. First, the inequality concept is expanded and then literature demonstrates the future desirability of modes. We show why doughnut economics could be a beneficial alternative for comparing that resulted in the superiority of active and public transport over SAV in terms of future inequality.
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Lee, Dongwoo, John Mulrow, Chana Joanne Haboucha, Sybil Derrible, and Yoram Shiftan. "Attitudes on Autonomous Vehicle Adoption using Interpretable Gradient Boosting Machine." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 11 (June 23, 2019): 865–78. http://dx.doi.org/10.1177/0361198119857953.
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This article applies machine learning (ML) to develop a choice model on three choice alternatives related to autonomous vehicles (AV): regular vehicle (REG), private AV (PAV), and shared AV (SAV). The learned model is used to examine users’ preferences and behaviors on AV uptake by car commuters. Specifically, this study applies gradient boosting machine (GBM) to stated preference (SP) survey data (i.e., panel data). GBM notably possesses more interpretable features than other ML methods as well as high predictive performance for panel data. The prediction performance of GBM is evaluated by conducting a 5-fold cross-validation and shows around 80% accuracy. To interpret users’ behaviors, variable importance (VI) and partial dependence (PD) were measured. The results of VI indicate that trip cost, purchase cost, and subscription cost are the most influential variables in selecting an alternative. Moreover, the attitudinal variables Pro-AV Sentiment and Environmental Concern are also shown to be significant. The article also examines the sensitivity of choice by using the PD of the log-odds on selected important factors. The results inform both the modeling of transportation technology uptake and the configuration and interpretation of GBM that can be applied for policy analysis.
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Swierczynski, Marek, and Łukasz Żarnowiec. "Law Applicable to Liability for Damages due to Traffic Accidents Involving Autonomous Vehicles." Masaryk University Journal of Law and Technology 14, no. 2 (September 23, 2020): 177–200. http://dx.doi.org/10.5817/mujlt2020-2-2.
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The authors examine the problem of the law applicable to liability for damages due to traffic accidents involving autonomous vehicles. Existing conflict-of-laws regulation adopted in the Rome II Regulation and both Hague Conventions of 1971 and 1973 is criticized. Upon examination of these legal instruments, it becomes clear that existing regulation is very complex and complicated. In effect authors recommend revisions to the legal framework. Proposed solutions are balanced and take into consideration both the interests of the injured persons, as well the persons claimed to be liable. New approach allows for more individual consideration of specific cases and direct to better outcome of the disputes. The findings may be useful in handling the cases related to use of algorithms of artificial intelligence in private international law.
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Tian, Jingjing, Hongfei Jia, Guanfeng Wang, Yu Lin, Ruiyi Wu, and Ao Lv. "A Long-Term Shared Autonomous Vehicle System Design Problem considering Relocation and Pricing." Journal of Advanced Transportation 2022 (June 15, 2022): 1–19. http://dx.doi.org/10.1155/2022/1905526.
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Compared to conventional private vehicles (CPVs), shared autonomous vehicles (SAVs) provide users the potential for the reduced value of time (VoT), improved mobility experience, and less traffic congestion. In the presence of the SAV system, numerous studies have mainly concentrated on the strategic planning and operational decision problem separately while ignoring the complicated interaction between them and the distinct features of autonomous vehicles. It is imperative to determine the relocation and pricing strategies at the operational level. In this study, in terms of the pricing strategy, we formalize a logit model to capture the mode choice behavior in a multimodal network, where the reduced VoT is considered simultaneously. A time-space network is employed to capture the daily operation problem based on the elastic demand. The minimum customer service rate is regarded as a constraint to ensure the system’s reliability. Moreover, a mixed-integer nonlinear programming (MINLP) model is formulated to jointly determine the number of stations and parking spaces, fleet size, relocation, and pricing strategies to maximize the total profit. Then, we integrate the Particle Swarm Optimization (PSO) algorithm with the optimization solver Gurobi to address the complex problem. Numerical experiments and comparative analyses are conducted to demonstrate the feasibility and efficiency of the proposed model.
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Da Rocha, Marcelo, and Gilberto Sarfati. "Cenários Prospectivos para a Competitividade do Varejo de Veículos no Brasil em 2040." Future Studies Research Journal: Trends and Strategies 10, no. 2 (May 1, 2018): 238–69. http://dx.doi.org/10.24023/futurejournal/2175-5825/2018.v10i2.375.
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The auto industry seems to face major changes and transformations. The sector has always been characterized by being very dynamic and pioneering in the development of new technologies, be they related to the production system or product. The pillar of this industry was built under the model of private ownership of vehicles. This scenario began to change most notably from the economic crisis of 2008 with the emergence and popularization of asset sharing platforms, which can shift vehicle ownership around the vehicle as a service. This paper focus on the future of the vehicle distribution industry in Brazil. The objective is to explore and analyze possible prospective scenarios for this industry in the country in 2040. Four scenarios were developed around the driving forces technological development and consumer behavior - Democratization of mobility, Consumer turnaround, Nothing new and Where we will stop. The study concludes that there is no doubt that the evolution of the industry is occurring and the disruption coming. While there is no certainty in any future forecast, it is quite clear that today's dealership model - based primarily on selling one vehicle at a time to individuals and then servicing those cars in their workshops - will not leave unscathed in a world of sharing, electrified, connected and autonomous vehicles.
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Choi, Yongsoon, Seryong Baek, Cheonho Kim, Junkyu Yoon, and Seongkwan Mark Lee. "Simulation of AEBS Applicability by Changing Radar Detection Angle." Applied Sciences 11, no. 5 (March 5, 2021): 2305. http://dx.doi.org/10.3390/app11052305.
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As smart cities become a global topic, interest in smart mobility, the core of smart cities, is also growing. The technology that comes closest to general users is “autonomous driving”. In particular, the successful market entry and establishment of some private companies proved that “autonomous driving” is not technology of the future but imminent reality. However, safety in autonomous vehicles that rely on sensors instead of the driver’s five senses has been the focus of attention from the beginning and continues to be so. In this study, we attempted to counter this interest. Based on the actual data of thirty traffic accidents, assuming the AEBS (Autonomous Emergency Braking System) was installed to assist the driver in safe driving, it was reinterpreted through simulation to see what changes occurred in the accident. In the computer program, PC-Crash, the results were first analyzed through simulation using Euro NCAP (New Car Assessment Program)’s AEBS test standards. Subsequently, the other variables in the AEBS were controlled and the accident was reinterpreted by changing only the angle of the radar detection sensor. As a result, it was confirmed that a total of 27 accidents out of thirty accidents could have been prevented with the AEBS. In addition, it proved that the crash avoidance rate of vehicles gradually increased as the radar angle increased.
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Pransky, Joanne. "The Pransky interview: Mel Torrie, Founder, CEO and President of Autonomous Solutions, Inc." Industrial Robot: An International Journal 45, no. 1 (January 15, 2018): 7–10. http://dx.doi.org/10.1108/ir-11-2017-0199.
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Purpose The following paper is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry engineer-turned successful innovator and leader, regarding the challenges of bringing technological discoveries to fruition. This paper aims to discuss these issues. Design/methodology/approach The interviewee is Mel Torrie, CEO and President of Autonomous Solutions, Inc. (ASI). ASI manufactures an OEM/vendor independent software and hardware solution retrofitted to existing equipment to create a wide variety of fully autonomous vehicles spanning agriculture, mining, automotive, industrial cleaning, security and government/military applications. In this interview, Torrie shares how he first got started in the robotics field along with his experiences in running his ground-breaking startup. Findings In 1999, Torrie received a Master’s Degree in Electrical Engineering at Utah State University (USU) where he worked on two National Aeronautics and Space Administration (NASA) space shuttle payloads. After his work at USU, he managed robotics development programs for John Deere, the US Department of Defense and the US Department of Energy. He founded ASI, a spin-off of the Center of Self Organizing and Intelligent Systems (CSOIS) at USU, in 2000. Originality/value Torrie was a pioneer and visionary who bootstrapped ASI from the beginning. Under Torrie’s leadership, ASI raised over $85m in a unique business model where there is no equity but only strategic partners. These foremost companies are given exclusive rights to their vertical market and jointly own their industry’s driverless vehicle’s intellectual property (IP) with ASI. The vehicles are developed and tested at ASI’s 100-acre proving ground facility in Utah. To date, ASI’s more than 100 employees and their business partners have automated 75 different vehicle types and ASI continues to create new markets. Some of ASI’s notable installations include the Bingham Canyon Mine clean-up effort; BatCat, the teleoperated CAT telehandler for the Los Angeles Police Department; and the robotic durability testing program with Ford Motors, Toyota, Fiat Chrysler Automotive, Hyundai, General Motors as well as other private proving grounds.
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Liu, Zhiguang, Tomio Miwa, Weiliang Zeng, Michael G. H. Bell, and Takayuki Morikawa. "Shared Autonomous Taxi System and Utilization of Collected Travel-Time Information." Journal of Advanced Transportation 2018 (August 8, 2018): 1–13. http://dx.doi.org/10.1155/2018/8919721.
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Shared autonomous taxi systems (SATS) are being regarded as a promising means of improving travel flexibility. Each shared autonomous taxi (SAT) requires very precise traffic information to independently and accurately select its route. In this study, taxis were replaced with ride-sharing autonomous vehicles, and the potential benefits of utilizing collected travel-time information for path finding in the new taxi system examined. Specifically, four categories of available SATs for every taxi request were considered: currently empty, expected-empty, currently sharable, and expected-sharable. Two simulation scenarios—one based on historical traffic information and the other based on real-time traffic information—were developed to examine the performance of information use in a SATS. Interestingly, in the historical traffic information-based scenario, the mean travel time for taxi requests and private vehicle users decreased significantly in the first several simulation days and then remained stable as the number of simulation days increased. Conversely, in the real-time information-based scenario, the mean travel time was constant. As the SAT fleet size increased, the total travel time for taxi requests significantly decreased, and convergence occurred earlier in the historical information-based scenario. The results demonstrate that historical traffic information is better than real-time traffic information for path finding in SATS.
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Martí, Pasqual, Jaume Jordán, Fernando De la Prieta, Holger Billhardt, and Vicente Julian. "Demand-Responsive Shared Transportation: A Self-Interested Proposal." Electronics 11, no. 1 (December 27, 2021): 78. http://dx.doi.org/10.3390/electronics11010078.
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With the world population highly increasing, efficient methods of transportation are more necessary than ever. On the other hand, the sharing economy must be explored and applied where possible, aiming to palliate the effects of human development on the environment. In this paper we explore demand-responsive shared transportation as a system with the potential to serve its users’ displacement needs while being less polluting. In contrast with previous works, we focus on a distributed proposal that allows each vehicle to retain its private information. Our work describes a partially dynamic system in which the vehicles are self-interested: they decide which users to serve according to the benefit it reports them. With our modelling, the system can be adapted to mobility platforms of autonomous drivers and even simulate the competition among different companies.
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Kim, Jung Hwan, Alwin Poulose, and Dong Seog Han. "The Extensive Usage of the Facial Image Threshing Machine for Facial Emotion Recognition Performance." Sensors 21, no. 6 (March 12, 2021): 2026. http://dx.doi.org/10.3390/s21062026.
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Facial emotion recognition (FER) systems play a significant role in identifying driver emotions. Accurate facial emotion recognition of drivers in autonomous vehicles reduces road rage. However, training even the advanced FER model without proper datasets causes poor performance in real-time testing. FER system performance is heavily affected by the quality of datasets than the quality of the algorithms. To improve FER system performance for autonomous vehicles, we propose a facial image threshing (FIT) machine that uses advanced features of pre-trained facial recognition and training from the Xception algorithm. The FIT machine involved removing irrelevant facial images, collecting facial images, correcting misplacing face data, and merging original datasets on a massive scale, in addition to the data-augmentation technique. The final FER results of the proposed method improved the validation accuracy by 16.95% over the conventional approach with the FER 2013 dataset. The confusion matrix evaluation based on the unseen private dataset shows a 5% improvement over the original approach with the FER 2013 dataset to confirm the real-time testing.
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Dubljevic, Veljko, George List, Jovan Milojevich, Nirav Ajmeri, William A. Bauer, Munindar P. Singh, Eleni Bardaka, et al. "Toward a rational and ethical sociotechnical system of autonomous vehicles: A novel application of multi-criteria decision analysis." PLOS ONE 16, no. 8 (August 13, 2021): e0256224. http://dx.doi.org/10.1371/journal.pone.0256224.
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The impacts of autonomous vehicles (AV) are widely anticipated to be socially, economically, and ethically significant. A reliable assessment of the harms and benefits of their large-scale deployment requires a multi-disciplinary approach. To that end, we employed Multi-Criteria Decision Analysis to make such an assessment. We obtained opinions from 19 disciplinary experts to assess the significance of 13 potential harms and eight potential benefits that might arise under four deployments schemes. Specifically, we considered: (1) the status quo, i.e., no AVs are deployed; (2) unfettered assimilation, i.e., no regulatory control would be exercised and commercial entities would “push” the development and deployment; (3) regulated introduction, i.e., regulatory control would be applied and either private individuals or commercial fleet operators could own the AVs; and (4) fleets only, i.e., regulatory control would be applied and only commercial fleet operators could own the AVs. Our results suggest that two of these scenarios, (3) and (4), namely regulated privately-owned introduction or fleet ownership or autonomous vehicles would be less likely to cause harm than either the status quo or the unfettered options.
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Bucsky, Péter. "Autonomous vehicles and freight traffic: towards better efficiency of road, rail or urban logistics?" Urban Development Issues 58, no. 1 (July 30, 2018): 41–52. http://dx.doi.org/10.2478/udi-2018-0022.
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Abstract The freight transport sector is a low profit and high competition business and therefore has less ability to invest in research and development in the field of autonomous vehicles (AV) than the private car industry. There are already different levels of automation technologies in the transport industry, but most of these are serving niche demands and answers have yet to be found about whether it would be worthwhile to industrialise these technologies. New innovations from different fields are constantly changing the freight traffic industry but these are less disruptive than on other markets. The aim of this article is to show the current state of development of freight traffic with regards to AVs and analyse which future directions of development might be viable. The level of automation is very different in the case of different transport modes and most probably the technology will favour road transport over other, less environmentally harmful traffic modes.
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Heilig, Michael, Tim Hilgert, Nicolai Mallig, Martin Kagerbauer, and Peter Vortisch. "Potentials of Autonomous Vehicles in a Changing Private Transportation System – a Case Study in the Stuttgart Region." Transportation Research Procedia 26 (2017): 13–21. http://dx.doi.org/10.1016/j.trpro.2017.07.004.
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Hasnat, Md Mehedi, Eleni Bardaka, M. Shoaib Samandar, Nagui Rouphail, George List, and Billy Williams. "Impacts of Private Autonomous and Connected Vehicles on Transportation Network Demand in the Triangle Region, North Carolina." Journal of Urban Planning and Development 147, no. 1 (March 2021): 04020058. http://dx.doi.org/10.1061/(asce)up.1943-5444.0000649.
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Szabolcsi, Róbert. "Pole Placement Technique Applied in Unmanned Aerial Vehicles Automatic Flight Control Systems Design." Land Forces Academy Review 23, no. 1 (March 1, 2018): 88–98. http://dx.doi.org/10.2478/raft-2018-0011.
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Abstract Unmanned aerial vehicles are widely spread and intensively used ones both in governmental and in private applications. The standard arrangements of the commercial-off-the-shelves unmanned aerial vehicles sometimes neglect application of the automatic flight control system onboard. However, there are many initiatives to ensure autonomous flights of the unmanned aerial vehicles via pre-programmed flight paths. Moreover, automatic flight control system can ensure necessary level of the flight safety both in VFR and IFR flights. The aim of this study is to guide UAV users in set up commercial onboard autopilots available on the market. On the contrary, fitness of the autopilot to a given type of the air robot is not guaranteed, and, an extra load on users can appear in controller settings. The proposed pole placement technique is one of the proper methods eliminating difficulties, and, computer aided gain selection using MATLAB will be presented.
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Janasekaran, Shamini, and Eshvinder Singh Mann. "A Case Study: Implementation of Automated Guided Vehicle Replacing Trollies Transportation in Manufacturing Industry to reduce Motion Waste in Lean Manufacturing practicing factory." Journal of Engineering & Technological Advances 5, no. 1 (2020): 1–7. http://dx.doi.org/10.35934/segi.v5i1.1.
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This research introduces and demonstrates the procedures and method used to eliminate waste of motion to achieve lean manufacturing which is the starting for Industrial Revolution 4.0. This was conducted in a private manufacturing factory that assembles printed circuit board (PCB). The research done provides an advantage by developing an efficient and effective way to carry out the transportation of PCB magazine trolley. The data collected and results obtained proved the benefits of the utilization of automated guided vehicle. In contrast, result attained for time reduction of transportation of PCB magazine trollies was in the range of 3.39% to 8.08%. Moreover, autonomous guided vehicles also verified the capability to eliminate the occurrence of human error and non-added value activities. In conclusion, the research carried showed a successful method towards optimization of the production in the selected PCB assembly manufacturing company.