Journal articles on the topic 'Autonomous Vehicles (AVs)'
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Rojas-Rueda, David, Mark J. Nieuwenhuijsen, Haneen Khreis, and Howard Frumkin. "Autonomous Vehicles and Public Health." Annual Review of Public Health 41, no. 1 (April 2, 2020): 329–45. http://dx.doi.org/10.1146/annurev-publhealth-040119-094035.
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Autonomous vehicles (AVs) have the potential to shape urban life and significantly modify travel behaviors. “Autonomous technology” means technology that can drive a vehicle without active physical control or monitoring by a human operator. The first AV fleets are already in service in US cities. AVs offer a variety of automation, vehicle ownership, and vehicle use options. AVs could increase some health risks (such as air pollution, noise, and sedentarism); however, if proper regulated, AVs will likely reduce morbidity and mortality from motor vehicle crashes and may help reshape cities to promote healthy urban environments. Healthy models of AV use include fully electric vehicles in a system of ridesharing and ridesplitting. Public health will benefit if proper policies and regulatory frameworks are implemented before the complete introduction of AVs into the market.
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Wang, Jun, Li Zhang, Yanjun Huang, Jian Zhao, and Francesco Bella. "Safety of Autonomous Vehicles." Journal of Advanced Transportation 2020 (September 15, 2020): 1–13. http://dx.doi.org/10.1155/2020/8867757.
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Autonomous vehicle (AV) is regarded as the ultimate solution to future automotive engineering; however, safety still remains the key challenge for the development and commercialization of the AVs. Therefore, a comprehensive understanding of the development status of AVs and reported accidents is becoming urgent. In this article, the levels of automation are reviewed according to the role of the automated system in the autonomous driving process, which will affect the frequency of the disengagements and accidents when driving in autonomous modes. Additionally, the public on-road AV accident reports are statistically analyzed. The results show that over 3.7 million miles have been tested for AVs by various manufacturers from 2014 to 2018. The AVs are frequently taken over by drivers if they deem necessary, and the disengagement frequency varies significantly from 2 × 10−4 to 3 disengagements per mile for different manufacturers. In addition, 128 accidents in 2014–2018 are studied, and about 63% of the total accidents are caused in autonomous mode. A small fraction of the total accidents (∼6%) is directly related to the AVs, while 94% of the accidents are passively initiated by the other parties, including pedestrians, cyclists, motorcycles, and conventional vehicles. These safety risks identified during on-road testing, represented by disengagements and actual accidents, indicate that the passive accidents which are caused by other road users are the majority. The capability of AVs to alert and avoid safety risks caused by the other parties and to make safe decisions to prevent possible fatal accidents would significantly improve the safety of AVs. Practical applications. This literature review summarizes the safety-related issues for AVs by theoretical analysis of the AV systems and statistical investigation of the disengagement and accident reports for on-road testing, and the findings will help inform future research efforts for AV developments.
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Shatanawi, Mohamad, and Ferenc Mészáros. "Implications of the Emergence of Autonomous Vehicles and Shared Autonomous Vehicles: A Budapest Perspective." Sustainability 14, no. 17 (September 2, 2022): 10952. http://dx.doi.org/10.3390/su141710952.
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The introduction of autonomous vehicles (AVs) and shared autonomous vehicles (SAVs) is projected to enhance network performance and accessibility. The future share distribution of AV and SAV is not yet apparent, nor is which of these two future transport modes will become dominant. Therefore, this research deploys a simulation-based dynamic traffic assignment using Visum software to investigate the impact of varying the share distribution of AVs and SAVs on Budapest’s network performance and consumer surplus in three projected future traffic scenarios for the years 2030 and 2050 compared to the Base scenario for 2020. The three future scenarios are presented and characterized by different penetration rates of AVs and SAVs to reflect the uncertainty in the market share of these future cars as follows: Mix-Traffic scenario for 2030, and AV-Focused and SAV-Focused scenarios for 2050. The results revealed that the emergence of AVs and SAVs would improve the overall network performance, and better performance was observed with increasing the share distribution of SAVs. Similarly, the consumer surplus increased in all future scenarios, especially with increasing the share distribution of AVs. Consequently, the advent of AVs and SAVs will improve traffic performance and increase consumer surplus, benefiting road users and authorities.
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SIQUEIRA SILVA, Dahlen, Csaba CSISZÁR, and Dávid FÖLDES. "Autonomous vehicles and urban space management." Scientific Journal of Silesian University of Technology. Series Transport 110 (March 1, 2021): 169–81. http://dx.doi.org/10.20858/sjsutst.2021.110.14.
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Discussions on how urban space would be transformed by the use of autonomous vehicles (AVs) are scarce. This study identifies the impacts caused by the shared use of AVs on urban parking and urban space management. An estimation method was formulated considering the reduction in parking demand, the possible alteration in vehicle ownership, and the reallocation of urban space. A case study was performed in a 673,220 m2 area through scenarios created by using real data of parking spaces and the results of previous studies. Results showed that parking spaces can be saved with the use of shared AVs, which would allow the reallocation of urban space to new uses (for example, implementation of around 12,000 bike-sharing docking spots, 10 km bike lanes, 7 km additional traffic lane or 140 ‘parklets’). The results contribute to revealing the positive impacts of AVs.
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Abdeen, Mohammad A. R., Ansar Yasar, Mohamed Benaida, Tarek Sheltami, Dimitrios Zavantis, and Youssef El-Hansali. "Evaluating the Impacts of Autonomous Vehicles’ Market Penetration on a Complex Urban Freeway during Autonomous Vehicles’ Transition Period." Sustainability 14, no. 16 (August 15, 2022): 10094. http://dx.doi.org/10.3390/su141610094.
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Autonomous vehicles (AVs) have been a rapidly emerging phenomenon in recent years, with some automated features already available in vehicles. AVs are expected to potentially revolutionize the existing inefficient state of urban transportation and be a step closer to environmental sustainability. This study focuses on simulation modeling in assessing the potential effects of autonomous vehicles (AVs) and on mobility and safety by developing a framework model based on traffic microsimulation for a real network located in Al-Madinah, Saudi Arabia. The market penetration rates (MPRs) will not reach 100% in the near future; instead, penetration will progressively increase. As a result, in our study, we investigated the potential effect of AV technology in five different AV market penetration rates: 0% (baseline), 25%, 50%, 75%, and 100%. The results suggest that Avs significantly improve the network’s safety and operational performance at high penetration rates. Specifically, estimated vehicle delays decreased by 26%, 34.4%, 63.7%, and 74.2% for 25%, 50%, 75%, and 100% AV penetration rates, respectively. Finally, we think this study will help decisionmakers over in the long-term in their attempts to achieve sustainable development through the optimal integration of innovative and novel technologies.
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Nourinejad, Mehdi, and Matthew J. Roorda. "Cruising for Parking with Autonomous and Conventional Vehicles." Journal of Advanced Transportation 2021 (November 1, 2021): 1–16. http://dx.doi.org/10.1155/2021/6269995.
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Parking is a cumbersome part of auto travel because travelers have to search for a spot and walk from that spot to their final destination. This conventional method of parking will change with the arrival of autonomous vehicles (AV). In the near future, users of AVs get dropped off at their final destination and the occupant-free AVs search for the nearest and most convenient parking spot. Hence, individuals no longer bear the discomfort of cruising for parking while sitting in their vehicle. This paper quantifies the impact of AVs on parking occupancy and traffic flow on a corridor that connects a home zone to a downtown zone. The model considers a heterogeneous group of AVs and conventional vehicles (CV) and captures their parking behavior as they try to minimize their generalized travel costs. Insights are obtained from applying the model to two case studies with uniform and linear parking supply along the corridor. We show that (i) CVs park closer to the downtown zone in order to minimize their walking distance, whereas AVs park farther away from the downtown zone to minimize their parking search time, (ii) AVs experience a lower search time than CVs, and (iii) higher AV penetration rates reduce travel costs for both AVs and CVs.
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Ji, Yangbeibei, Mingwei Xu, Hua Wang, and Chaowu Tan. "Commute Equilibrium for Mixed Networks with Autonomous Vehicles and Traditional Vehicles." Journal of Advanced Transportation 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/6218363.
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Recent development of autonomous vehicle (AV) provides new travel opportunities for citizens, and traditional vehicles (TVs) will still be used for a long time. Therefore, it is highly possible that both AVs and TVs will be used as travel modes in a city. In a transportation system with both AVs and TVs, the traffic pattern is worthy of studying. This paper investigates user equilibrium traffic pattern based on the traditional bottleneck model considering AVs and TVs. For both TVs and AVs, travel costs include queuing delay and schedule delay. However, they also have different components of travel costs; more specifically, for AVs, passengers have to pay a riding fare, and, for TVs, travelers encounter a walking time cost after parking their cars. For different combinations of travel demands and riding fare of AVs, analytical solutions of three different user equilibrium traffic patterns are obtained. Finally, numerical examples are provided to demonstrate the usefulness of the analytical models. Sensitivity analyses are examined to show the impacts of AV’s time-dependent fee and trip-based fixed fee on the traffic pattern and travel costs.
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Andersen, Hans, Xiaotong Shen, You Hong Eng, Daniela Rus, and Marcelo H. Ang. "Connected Cooperative Control of Autonomous Vehicles During Unexpected Road Situations." Mechanical Engineering 139, no. 12 (December 1, 2017): S3—S7. http://dx.doi.org/10.1115/1.2017-dec-7.
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This article discusses how connected cooperative control of autonomous vehicles (AVs) can help in providing safe and comfortable mobility during unexpected road situations. Driving AVs in urban areas poses a big challenge due to the complexity of the traffic rules as well as unexpected scenarios involved. In these situations, an inter-vehicle communication system can be of great help. Cooperation between multiple AVs is possible with the development of vehicular communication. In particular, state estimation can be improved with multiple sources of information gathered from different vehicles. Cooperative state estimation can also improve robustness against communication failure. With future trajectories shared among nearby vehicles, the motion can be coordinated to make navigation safer and smoother for AVs. For vehicular communication, the IEEE 802.11p standard has been designed to allow information exchange between high-speed cars, and between vehicles and roadside infrastructure. Other wireless communication technologies, such as 3G, 4G, and WiFi, are also suggested.
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López-Lambas, M. Eugenia, and Andrea Alonso. "The Driverless Bus: An Analysis of Public Perceptions and Acceptability." Sustainability 11, no. 18 (September 12, 2019): 4986. http://dx.doi.org/10.3390/su11184986.
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The development of autonomous vehicles (AVs) holds a high potential for improving security, reducing congestion, increasing fuel efficiency, and saving time. Various studies conducted on the implementation of AVs predict that fully autonomous vehicles will be available for the public in the 2020s. However, it will take another three decades, at least, for these vehicles and technologies to be accepted among the general masses and become reliable and affordable for use. Nonetheless, while a great deal has been stated regarding autonomous cars, little attention has been paid to autonomous public transport, more specifically, autonomous buses (ABs). The present report analyzed the psychological barriers preventing the complete implementation of ABs through data collected from focus group (FG) discussions. The main objective of the FGs was to determine the factors influencing perceptions regarding ABs and their acceptability. The most important factors from the positive side were the reduction of personnel costs, the potential to decrease congestion, waiting time at intersections, and reduced emissions. On the other hand, the most important negative factors were an increase in vehicle and infrastructure costs, safety risks under certain conditions (e.g., system failures, terrorist attacks, etc.), and the possible reduction of employment opportunities.
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Yang, Diange, Xinyu Jiao, Kun Jiang, and Zhong Cao. "Driving Space for Autonomous Vehicles." Automotive Innovation 2, no. 4 (December 2019): 241–53. http://dx.doi.org/10.1007/s42154-019-00081-1.
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AbstractDriving space for autonomous vehicles (AVs) is a simplified representation of real driving environments that helps facilitate driving decision processes. Existing literatures present numerous methods for constructing driving spaces, which is a fundamental step in AV development. This study reviews the existing researches to gain a more systematic understanding of driving space and focuses on two questions: how to reconstruct the driving environment, and how to make driving decisions within the constructed driving space. Furthermore, the advantages and disadvantages of different types of driving space are analyzed. The study provides further understanding of the relationship between perception and decision-making and gives insight into direction of future research on driving space of AVs.
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VONDRÁČKOVÁ, Lucie, Martina TREPÁČOVÁ, and Petr ZÁMEČNÍK. "INTERACTIONS BETWEEN AUTONOMOUS VEHICLES, CYCLISTS, AND PEDESTRIANS FROM THE PERSPECTIVE OF POTENTIAL USERS AND NON-USERS OF AUTONOMOUS VEHICLES." Transport Problems 17, no. 1 (March 1, 2022): 115–26. http://dx.doi.org/10.20858/tp.2022.17.1.10.
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In a few years, autonomous vehicles will slowly become part of traffic flow. This paper evaluated the level of perceived fear of interactions of autonomous vehicles (AVs) with other (vulnerable) road users of different actors in the Czech Republic. Data from the first exploratory project from 2017/2018 are used for the evaluation. A logistic regression model is utilised to evaluate the predictors that influence the fear resulting from interactions of AVs and cyclists or pedestrians. Kilometres driven last year was positively associated with fear of interactions with pedestrians or cyclists (OR = 1,251, p = 0.032). The level of concerns about the risk of AVs is also positively associated with fear of interactions (OR = 1.087, p = 0.000). Out of all socio-demographics and socio-economics, only gender was distinguished regarding the level of fear, with women having a higher chance than men of being fearful (OR = 1.871, p = 0.005). Then, the same model is utilised to evaluate the variables that influence the fear of interactions of Avs and other non-Avs. Only the general level of concerns about the risk of AVs is associated with the level of fear of interactions of AVs and non-AVs (OR = 1.149, p = 0.000). Since these results are only partly in accordance with those obtained in Western countries, our paper concludes that for central European countries, more research is needed to understand the local context and implications of autonomous mobility.
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Pauwels, Alex, Nadia Pourmohammad-Zia, and Frederik Schulte. "Safety and Sustainable Development of Automated Driving in Mixed-Traffic Urban Areas—Considering Vulnerable Road Users and Network Efficiency." Sustainability 14, no. 20 (October 19, 2022): 13486. http://dx.doi.org/10.3390/su142013486.
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Next to environmental aspects, establishing areas for safe and economically viable automated driving in mixed-traffic settings is one major challenge for sustainable development of Autonomous Vehicles (AVs). This work investigates safety in the interactions between AVs, human-driven vehicles, and vulnerable road users, including cyclists and pedestrians, within a simulated urban environment in the Dutch city of Rotterdam. New junction and pedestrian models are introduced, and virtual AVs with an occlusion-aware driving system are deployed to deliver cargo autonomously. The safety of applying this autonomous cargo delivery service is assessed using a large set of Surrogate Safety Indicators (SSIs). Furthermore, Macroscopic Fundamental Diagrams (MFDs) and travel time loss are incorporated to evaluate the network efficiency. By assessing the impact of various measures involving Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Vehicle-to-Everything (V2X) communications, infrastructure modifications, and driving behavior, we show that traffic safety and network efficiency can be achieved in a living lab setting for the considered case. Our findings further suggest that V2X gets implemented, new buildings are not placed close to intersections, and the speed limit of non-arterial roads is lowered.
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Tremoulet, Patrice D., Thomas Seacrist, Chelsea Ward McIntosh, Helen Loeb, Anna DiPietro, and Sophia Tushak. "Transporting Children in Autonomous Vehicles: An Exploratory Study." Human Factors: The Journal of the Human Factors and Ergonomics Society 62, no. 2 (July 3, 2019): 278–87. http://dx.doi.org/10.1177/0018720819853993.
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Objective Identify factors that impact parents’ decisions about allowing an unaccompanied child to ride in an autonomous vehicle (AV). Background AVs are being tested in several U.S. cities and on highways in multiple states. Meanwhile, suburban parents are using ridesharing services to shuttle children from school to extracurricular activities. Parents may soon be able to hire AVs to transport children. Method Nineteen parents of 8- to 16-year-old children, and some of their children, rode in a driving simulator in autonomous mode, then were interviewed. Parents also participated in focus groups. Topics included minimum age for solo child passengers, types of trips unaccompanied children might take, and vehicle features needed to support child passengers. Results Parents would require two-way audio communication and prefer video feeds of vehicle interiors, seatbelt checks, automatic locking, secure passenger identification, and remote access to vehicle information. Parents cited convenience as the greatest benefit and fear that AVs could not protect passengers during unplanned trip interruptions as their greatest concern. Conclusion Manufacturers have an opportunity to design family-friendly AVs from the outset, rather than retrofit them to be safe for child passengers. More research, especially usability studies where families interact with technology prototypes, is needed to understand how AV design impacts child passengers. Application Potential applications of this research include not only designing vehicles that can be used to safely transport children, seniors who no longer drive, and individuals with disabilities but also developing regulations, policies, and societal infrastructure to support safe child transport via AVs.
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Guo, Runhua, Siquan Liu, Yulin He, and Li Xu. "Study on Vehicle–Road Interaction for Autonomous Driving." Sustainability 14, no. 18 (September 17, 2022): 11693. http://dx.doi.org/10.3390/su141811693.
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Autonomous vehicles (AVs) are becoming increasingly popular, and this can potentially affect road performance. Road performance also influences driving comfort and safety for AVs. In this study, the influence of changes in traffic volume and wheel track distribution caused by AVs on the rutting distress of asphalt pavement was investigated through finite element simulations. A vehicle-mounted three-dimensional laser profiler was used to obtain pavement roughness and texture information. The vehicle vibration acceleration was obtained through vehicle dynamics simulations, and the skid resistance indexes of 20 rutting specimens were collected. The results showed that an increase in traffic volume caused by the increasing AV traffic accelerated the occurrence of rutting distress; however, the uniform distribution of vehicles at both ends of the transverse direction could prolong the maintenance life of flexible and semi-rigid pavements by 0.041 and 0.530 years, respectively. According to Carsim and Trucksim vehicle simulations and multiple linear regression fitting, the relationship models of three factors, namely speed, road roughness, and comfort, showed high fitting accuracies; however, there were some differences among the models. Among the texture indexes, the arithmetic mean’s height (Ra) had the greatest influence on the tire–road friction coefficient; Ra greatly influenced the safe driving of AVs. The findings of this study were used to present a speed control strategy for AVs based on the roughness and texture index for ensuring comfort and safety during automatic driving.
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Boualam, Othmane, Attila Borsos, Csaba Koren, and Viktor Nagy. "Impact of Autonomous Vehicles on Roundabout Capacity." Sustainability 14, no. 4 (February 15, 2022): 2203. http://dx.doi.org/10.3390/su14042203.
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Studying the impact of AVs on our road infrastructure offers a lot of potential in the transportation domain; one of these issues is how capacity will be affected. This paper presents a contribution to this research area by investigating the impact of AVs on the capacity of single-lane roundabouts using a microsimulation model. For the development of the model, a roundabout situated in Győr (Hungary) was selected and field data on the roundabout geometric characteristics as well as traffic volumes were used. Simulations using Vissim were run for various scenarios based on varying input traffic volumes and market penetration rates of AVs to assess queue lengths. The highway capacity manual (HCM) roundabout model was used to estimate the capacity of the existing roundabout. Values of follow-up times and critical gaps were set to decreasing as the penetration rate of AVs increases. The results demonstrated that 20% and 40% AVs in the flow would increase leg capacities by about 10% and 20%, respectively. Furthermore, a reduction in excessive queue lengths was estimated and capacities and queue lengths were calculated by legs. It was found that these are highly influenced by the distribution of flows among legs, and the share of flows in various directions.
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Othman, Kareem. "Multidimension Analysis of Autonomous Vehicles: The Future of Mobility." Civil Engineering Journal 7 (March 12, 2022): 71–93. http://dx.doi.org/10.28991/cej-sp2021-07-06.
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The level of investment in AVs technology has been increasing over the years as both researchers and developers are cooperating with the objective of developing AVs and understanding their behaviors and implications. Despite the enthusiastic speculation about AVs, little is known about the implications of AVs on our lives and the intertwined relationships between the implications. Thus, the main objective of this paper is to reveal the benefits and risks of AVs and sketch out the main trends in this area in order to provide some directions and recommendations for the future. This study focuses on analyzing the impact of AVs on the required fleet size, vehicle utilization, cost of mobility, public transit service, public behavior, transportation network, land use, economy, environment, society, and public health. Furthermore, the paper analyzes the intertwined relationship between the implications of AVs. Additionally, the paper sheds light on the potential benefits and challenges of the deployment of AVs in developing countries. The analysis shows that while AVs offer multiple benefits, they also pose new risks. The degree to which AVs can affect our plant mainly depends on regulatory actions, as the broader implications of AVs are mainly dependent on how the technology will be adopted, which can be controlled by regulatory actions. Doi: 10.28991/CEJ-SP2021-07-06 Full Text: PDF
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Norton, Thomas A., Melissa Ruhl, Tim Armitage, Brian Matthews, and John Miles. "Cross-National Focus Group Response to Autonomous Vehicles." Transportation Research Record: Journal of the Transportation Research Board 2675, no. 6 (March 3, 2021): 339–51. http://dx.doi.org/10.1177/0361198121992363.
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The development of autonomous vehicles (AVs) is advancing quickly in some enclaves around the world. Consequently, AVs exist in the public consciousness, featuring regularly in mainstream media. As the form and function of AVs emerge, the attitudes of potential users become more important. The extent to which the public trusts AV technology and anticipates benefits, will drive consumer willingness to use AVs. Broadly, public attitudes will determine whether AVs can attract public investment in infrastructure and become a feature of the future transport mix or fail to realize the potential their developers assert. As part of UK Autodrive, a program trialing the introduction of AVs in the United Kingdom, researchers conducted focus groups in five UK cities, and a comparison focus group in San Francisco (December 2017 to September 2018) using representative samples (total n = 137). Focus group facilitators guided discussions in three areas considered central to usage decisions: trust in the technology, ownership models, and community benefit. This paper describes findings from a quasi-quantitative study supported with qualitative insights. This research provides three key takeaways centering on trust in the technology and in delivering benefit. First, some participants gain trust through experience and others through evidence. Second, participants had difficulty discriminating between AV developers, indicating a need for industry cooperation. Third, partnerships were found to demonstrate trust, highlighting the need for more and deeper partnerships moving forward. Generally, participants had positive attitudes toward AVs and expect AVs to provide benefits. However, these attitudes and expectations could change as AV development progresses.
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Ahangar, M. Nadeem, Qasim Z. Ahmed, Fahd A. Khan, and Maryam Hafeez. "A Survey of Autonomous Vehicles: Enabling Communication Technologies and Challenges." Sensors 21, no. 3 (January 21, 2021): 706. http://dx.doi.org/10.3390/s21030706.
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The Department of Transport in the United Kingdom recorded 25,080 motor vehicle fatalities in 2019. This situation stresses the need for an intelligent transport system (ITS) that improves road safety and security by avoiding human errors with the use of autonomous vehicles (AVs). Therefore, this survey discusses the current development of two main components of an ITS: (1) gathering of AVs surrounding data using sensors; and (2) enabling vehicular communication technologies. First, the paper discusses various sensors and their role in AVs. Then, various communication technologies for AVs to facilitate vehicle to everything (V2X) communication are discussed. Based on the transmission range, these technologies are grouped into three main categories: long-range, medium-range and short-range. The short-range group presents the development of Bluetooth, ZigBee and ultra-wide band communication for AVs. The medium-range examines the properties of dedicated short-range communications (DSRC). Finally, the long-range group presents the cellular-vehicle to everything (C-V2X) and 5G-new radio (5G-NR). An important characteristic which differentiates each category and its suitable application is latency. This research presents a comprehensive study of AV technologies and identifies the main advantages, disadvantages, and challenges.
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Dias, Felipe F., Gopindra S. Nair, Natalia Ruíz-Juri, Chandra R. Bhat, and Arash Mirzaei. "Incorporating Autonomous Vehicles in the Traditional Four-Step Model." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 7 (June 13, 2020): 348–60. http://dx.doi.org/10.1177/0361198120922544.
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Automated vehicles (AVs) are a concrete possibility in the near future. As AVs may shift transportation paradigms, transportation agencies are eager to update their models to consider them in planning. In this context, the use of advanced models may be challenging, given the uncertainty in the use and deployment of AVs. In this paper, we present a general framework to extend the four-step model to include AVs, and test our extension on North Central Texas Council of Governments’ model. Our approach introduces a module for AV ownership and exogenous parameters into an existing four-step model to account for changes in travel decisions for AV owners, and for the impacts of AVs on network performance. The latter is modeled using the concept of passenger-car-equivalent to avoid imposing network-wide assumptions on AVs’ capacity consumption. We analyze five scenarios, representing different assumptions on the impacts of AVs, and include references to inform the selection of modeling parameters. We compute aggregate metrics that suggest that the model is sensitive to the proposed parameters, with the passenger-car-equivalent assumptions having the largest impact on model outcomes. Results suggest that, even when we assume that AVs can better use network capacity and that trip-making rates do not drastically increase, AVs may lead to an increase of about 2.8% in vehicle-hours traveled while also improving speeds by about 1.8%. If AVs introduce additional friction on traffic, the system performance may deteriorate. The analyses presented here suggest that existing modeling tools may be adjusted to support analyses of a future with AVs.
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Ahmed, Hafiz Usman, Ying Huang, Pan Lu, and Raj Bridgelall. "Technology Developments and Impacts of Connected and Autonomous Vehicles: An Overview." Smart Cities 5, no. 1 (March 17, 2022): 382–404. http://dx.doi.org/10.3390/smartcities5010022.
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The scientific advancements in the vehicle and infrastructure automation industry are progressively improving nowadays to provide benefits for the end-users in terms of traffic congestion reduction, safety enhancements, stress-free travels, fuel cost savings, and smart parking, etc. The advances in connected, autonomous, and connected autonomous vehicles (CV, AV, and CAV) depend on the continuous technology developments in the advanced driving assistance systems (ADAS). A clear view of the technology developments related to the AVs will give the users insights on the evolution of the technology and predict future research needs. In this paper, firstly, a review is performed on the available ADAS technologies, their functions, and the expected benefits in the context of CVs, AVs, and CAVs such as the sensors deployed on the partial or fully automated vehicles (Radar, LiDAR, etc.), the communication systems for vehicle-to-vehicle and vehicle-to-infrastructure networking, and the adaptive and cooperative adaptive cruise control technology (ACC/CACC). Secondly, for any technologies to be applied in practical AVs related applications, this study also includes a detailed review in the state/federal guidance, legislation, and regulations toward AVs related applications. Last but not least, the impacts of CVs, AVs, and CAVs on traffic are also reviewed to evaluate the potential benefits as the AV related technologies penetrating in the market. Based on the extensive reviews in this paper, the future related research gaps in technology development and impact analysis are also discussed.
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Jerman, Boris, Banu Yetkin Ekren, Melis Küçükyaşar, and Tone Lerher. "Simulation-Based Performance Analysis for a Novel AVS/RS Technology with Movable Lifts." Applied Sciences 11, no. 5 (March 4, 2021): 2283. http://dx.doi.org/10.3390/app11052283.
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This paper studies a novel autonomous vehicle-based storage and retrieval system (AVS/RS) design with movable lifts (AVS/RS/ML). In the proposed system, there are aisle-captive lifts that are able to travel along the warehouse aisle to position themselves at the target column location. Those lifts can lift up/down the autonomous vehicles to/from the target storage compartment when they are in standstill. This novel design is proposed as an alternative to existing AVS/RSs to balance the resource utilizations as well as to provide an inexpensive solution with highly utilized autonomous vehicles (i.e., AGVs). As an initial work, for this novel system, two alternative operating designs under different racking configurations are experimented. We compare those two designs by their throughput rate performance metrics under the arrival rate scenarios with highly utilized AGVs (i.e., 95%). Besides, we experiment with two warehouse capacity scenarios: 900 and 1800 storage compartments. The results show that designs with two separate I/O point locations provide a better throughput rate than designs with single I/O point location. Besides, a decreased number of columns in the system improves the system’s performance.
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McManus, Ryan M., and Abraham M. Rutchick. "Autonomous Vehicles and the Attribution of Moral Responsibility." Social Psychological and Personality Science 10, no. 3 (February 16, 2018): 345–52. http://dx.doi.org/10.1177/1948550618755875.
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With the imminent advent of autonomous vehicles (AVs) comes a moral dilemma: How do people assign responsibility in the event of a fatal accident? AVs necessarily create conditions in which “drivers” yield agency to a machine. The current study examines how people make attributions of blame and praise in this context. Varying the features of AV technology affected how responsible a “driver” (who purchased the vehicle) is perceived to be following a deadly crash. The findings provide support for agency and commission as crucial bases of moral judgment. They also raise questions about how morally contradictory actions are perceived and underscore the need for research examining how moral responsibility is distributed among multiple potentially culpable agents. Pragmatically, these findings suggest that regulating (or declining to regulate) how AVs are programmed may strongly influence perceptions of moral and legal culpability.
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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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M. Azam, S.A. Hassan, O.C. Puan, S.F. Azhari, and R.U. Faiz. "Performance of Autonomous Vehicles in Mixed Traffic under different Demand Conditions." International Journal of Automotive and Mechanical Engineering 19, no. 4 (December 28, 2022): 10050–62. http://dx.doi.org/10.15282/ijame.19.4.2022.02.0776.
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Autonomous Vehicles (AVs) are considered one of the potential solutions to future urban mobility with several promised benefits regarding safety and traffic operation. Despite of expected benefits, these vehicles will take decades to have full market penetration and before that, AVs will co-exist with Conventional Vehicles (CVs), which may affect the performance of AVs owing to different driving logic than CVs. The aim of this study is to quantify the impacts of varying penetrations of AVs when introduced in mixed traffic conditions. The study employed simulation environment VISSIM to study the different scenarios based on the percentage of AVs in mixed traffic, category of AVs and varying demand levels. The findings show that at lower demand levels (1000 veh/hr and 2000 veh/hr), CVs and three categories of AVs produced similar results. However, cautious and normal AVs negatively affect traffic operations when the demand level is increased. At demand-3 (3000 veh/hr), the penetration rates of cautious AVs greater than 50% shows negative impact on performance. At demand-4 (4000 veh/hr), even a small proportion (25%) of cautious AVs can negatively affect performance, and a similar effect is observed for normal AVs with a penetration rate greater than 75%. For speed, the minimum reduction with the increase in demand is observed for aggressive AVs, followed by conventional vehicles, normal AVs and cautious AVs. It can be concluded that the aggressive AVs produced better delays, queue length, speed and conflicts than CVs, cautious AVs and normal AVs at the highest demand levels.
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Meidute-Kavaliauskiene, Ieva, Bülent Yıldız, Şemsettin Çiğdem, and Renata Činčikaitė. "Do People Prefer Cars That People Don’t Drive? A Survey Study on Autonomous Vehicles." Energies 14, no. 16 (August 6, 2021): 4795. http://dx.doi.org/10.3390/en14164795.
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Only recently, smart cities are taking shape, thanks to the rapid development of Internet of Things (IoT), cloud computing, and other similar technologies. Given the high demands placed on advanced technologies such as autonomous driving, cloud data services, and high-precision sensors, smart cities are creating an intelligent transportation environment conducive to the introduction of autonomous vehicles (AVs). In this context, the use of AVs in transportation is also considered a form of transportation innovation. As a result, AVs are considered more favorable to people interested in new technologies because they appear to be technologically superior. Their association with the most up-to-date technology can serve as a symbol for those who wish to demonstrate their interest in new technologies through their appearance. The positive image of technological innovation projected by AVs may influence their acceptance among technology enthusiasts to a significant degree. In this context, this study investigates the effects of perceived advantage, perceived risk, and perceived safety on the intention to use autonomous vehicles. For this purpose, data were collected from vehicle users living in Turkey by survey method. Secondly, factor analyses and regression analyses were performed with the data set obtained from 611 participants. As a result of the analyses, it has been determined that the perceived advantage and perceived security increase the intention to use autonomous vehicles. In contrast, the perceived risk reduces this intention to use. According to these results, recommendations were made to the companies about the level of acceptance of this technology by the users to assess their investments in autonomous vehicles better.
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Souza, Luisa Muglia, and José Alberto Barroso Castañon. "Public perception of autonomous vehicles: a brief review." Research, Society and Development 10, no. 16 (December 18, 2021): e571101624236. http://dx.doi.org/10.33448/rsd-v10i16.24236.
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There is huge speculation that autonomous vehicles (AVs) will improve urban traffic conditions by enhancing mobility, reducing emissions, and bringing safety. However, AV public acceptance represents a key factor to this technology's success. This paper aims to present a brief review of public perceptions of AVs and focuses on how factors such as demographics, safety, ethics, liability, and COVID-19 pandemic can impact this mobility device’s acceptance. Overall, it was found that young and more educated males are more likely to adopt AVs, whereas concerns about safety, ethics, and liability can impact negatively on people’s perception of them.
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Yu, Hwapyeong, Sehyun Tak, Minju Park, and Hwasoo Yeo. "Impact of Autonomous-Vehicle-Only Lanes in Mixed Traffic Conditions." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 9 (May 8, 2019): 430–39. http://dx.doi.org/10.1177/0361198119847475.
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The introduction of autonomous vehicles (AVs) in the near future will have a significant impact on road traffic. AVs may have advantages in efficiency and convenience, but safety can be compromised in mixed operations of manual vehicles and AVs. To deal with the issues associated with mixed traffic and to avoid its negative effects, a special purpose lane reserved for AVs can be proposed to segregate AVs from manual vehicles. In this research, we analyze the effect on efficiency and safety of AVs in mixed traffic and in a situation where an AV-only lane is deployed. In the analysis, we investigate the average speed, the throughput, and the inverse time-to-collision (ITTC). We differentiate the behaviors of manual vehicles and AVs through the reaction time, desired speed, and car-following models. As a result, we observe that the efficiency is improved when the market penetration rate of AVs increases, especially when the highway throughput increases by up to 84% in the case of mixed traffic. However, safety worsens when the market penetration of AVs is under 40%. In this case, the average speed can be improved and the frequency of dangerous situations (ITTC > 0.49) can be reduced drastically in the merging section by making the innermost lane AV-only. Accordingly, we conclude that AV-only lanes can have a significant positive impact on efficiency and safety when the market penetration rate of AVs is low.
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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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Rahimi, Alireza, Ghazaleh Azimi, and Xia Jin. "What Drives Commuters to Pay for Autonomous Vehicles?" Transportation Research Record: Journal of the Transportation Research Board 2676, no. 4 (December 4, 2021): 267–80. http://dx.doi.org/10.1177/03611981211058095.
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Although commuters have been identified as potential early adopters of autonomous vehicles (AVs) that can boost the adoption rate of this technology, there is a lack of knowledge on their willingness to pay (WTP) for this technology and the attitude that influences this decision. Using data from a consumer survey conducted in the United States, this study presents a comprehensive analysis of the decision to pay for AVs among commuters. An integrated choice and latent variable (ICLV) model was applied in this study, considering its robust performance in modeling choice behavior for integrating users’ attitudes. The results showed that commuters with a favorable view toward multitasking tended to put a higher value on driverless cars. On the other hand, although a favorable view toward technology motivated commuters to pay more for AVs, data privacy and trust issues with the technology could outweigh this factor and discourage commuters from adopting and paying for AVs. This study also provides in-depth insights and comprehensive views on the impacts of commuters’ socioeconomic and demographic attributes on the decision to pay for AVs. Notably, although age and educational attainment did not directly affect WTP behavior, they played important roles in this decision, with significant effects mediated through latent attitudes. These in-depth analyses provide useful insights that can help develop customized marketing strategies for different market segments according to their specific and unique preferences and concerns.
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Mushtaq, Anum, Irfan ul Haq, Wajih un Nabi, Asifullah Khan, and Omair Shafiq. "Traffic Flow Management of Autonomous Vehicles Using Platooning and Collision Avoidance Strategies." Electronics 10, no. 10 (May 20, 2021): 1221. http://dx.doi.org/10.3390/electronics10101221.
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Connected Autonomous Vehicles (AVs) promise innovative solutions for traffic flow management, especially for congestion mitigation. Vehicle-to-Vehicle (V2V) communication depends on wireless technology where vehicles can communicate with each other about obstacles and make cooperative strategies to avoid these obstacles. Vehicle-to-Infrastructure (V2I) also helps vehicles to make use of infrastructural components to navigate through different paths. This paper proposes an approach based on swarm intelligence for the formation and evolution of platoons to maintain traffic flow during congestion and collision avoidance practices using V2V and V2I communications. In this paper, we present a two level approach to improve traffic flow of AVs. At the first level, we reduce the congestion by forming platoons and study how platooning helps vehicles deal with congestion or obstacles in uncertain situations. We performed experiments based on different challenging scenarios during the platoon’s formation and evolution. At the second level, we incorporate a collision avoidance mechanism using V2V and V2I infrastructures. We used SUMO, Omnet++ with veins for simulations. The results show significant improvement in performance in maintaining traffic flow.
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Al-Turki, Mohammed, Nedal T. Ratrout, Syed Masiur Rahman, and Imran Reza. "Impacts of Autonomous Vehicles on Traffic Flow Characteristics under Mixed Traffic Environment: Future Perspectives." Sustainability 13, no. 19 (October 6, 2021): 11052. http://dx.doi.org/10.3390/su131911052.
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Vehicle automation and communication technologies are considered promising approaches to improve operational driving behavior. The expected gradual implementation of autonomous vehicles (AVs) shortly will cause unique impacts on the traffic flow characteristics. This paper focuses on reviewing the expected impacts under a mixed traffic environment of AVs and regular vehicles (RVs) considering different AV characteristics. The paper includes a policy implication discussion for possible actual future practice and research interests. The AV implementation has positive impacts on the traffic flow, such as improved traffic capacity and stability. However, the impact depends on the factors including penetration rate of the AVs, characteristics, and operational settings of the AVs, traffic volume level, and human driving behavior. The critical penetration rate, which has a high potential to improve traffic characteristics, was higher than 40%. AV’s intelligent control of operational driving is a function of its operational settings, mainly car-following modeling. Different adjustments of these settings may improve some traffic flow parameters and may deteriorate others. The position and distribution of AVs and the type of their leading or following vehicles may play a role in maximizing their impacts.
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Otayek, Elie, Rania Wehbe, and Zaher Massaad. "Autonomous vehicles implementation in Lebanon: Opportunities, challenges, and ethical decisions." MATEC Web of Conferences 281 (2019): 01009. http://dx.doi.org/10.1051/matecconf/201928101009.
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The Autonomous Vehicle (AV) technology allows people to travel without intervening. The quick progress in this technology and the efforts of manufacturers companies to reach fully Autonomous Vehicles (AVs) using artificial intelligent, forecast a bright future. Researches have estimated that on average, one passenger in a vehicle traveling one kilometer in Lebanon costs about $ 48, including externality components of crashes, travel time, congestion and pollution. Thus, the main purpose of this research is to highlight the opportunities of implementing AVs in Lebanon, such as reduction in traffic accidents and congestion, improvement of accessibility, human health, economic and social life. Moreover, this paper highlight the barriers standing in front of implementing this technology, like the missing of Intelligent Transportation System (ITS) and the funds needed for its execution, and gives some policy recommendations. Finally, the authors present their statistics conducted in Lebanon about ethical decisions that AVs should take particularly in case of a crash in different scenarios through the participants’ responses.
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Patella, S. M., F. Aletta, and L. Mannini. "Assessing the impact of Autonomous Vehicles on urban noise pollution." Noise Mapping 6, no. 1 (January 1, 2019): 72–82. http://dx.doi.org/10.1515/noise-2019-0006.
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Abstract This paper presents the results of a noise emission study of Autonomous Vehicles (AVs) and their impact on the road network. By comparing the current situation with a future hypothetical scenario (100% AVs penetration), this study highlights the positive effect, in terms of noise pollution, of the adoption of AVs on a real road network (city of Rome). For this scope, a traffic simulation-based approach was used to investigate the effects of AVs on the network congestion. Results show that the full AVs penetration scenario leads to an improvement in the network performances in terms of travel time and average network speed. Moreover, the amount of Vehicle Kilometre Travelled (VKT) shows an 8% increase on longer extra-urban routes, due to the higher capacity impact of AVs on highways, with a consequent load reduction for intra-urban shortcutting routes. These results are also reflected in terms of noise emission. In fact, the central area would benefit from lower noise emission, whereas an increase in traffic volume and speed lead to worsened conditions for some specific highway links of the network. Overall, it was shown that a 100% AVs fleet would have a beneficial effect for the noise pollution, leading to a general reduction of noise emissions, which is more pronounced for intra-urban roads.
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Carvalho, Stephen, Suyash Ahire, Earl W. Huff, and Julian Brinkley. "UTT: A Conceptual Model to Guide the Universal Design of Autonomous Vehicles." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, no. 1 (December 2020): 87–91. http://dx.doi.org/10.1177/1071181320641024.
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Autonomous vehicles (AVs) are closer to becoming a reality in changing the landscape of commercial and personal transportation. The launch of these vehicles come with the promise of improved road safety, reduced traffic fatalities, and enhanced mobility. However, there are questions as to whether the design of AVs will meet the needs of everyone, including people with disabilities and older adults. We argue that there exists no conceptual model that guide sthe inclusive design of autonomous vehicles to benefit all intended users. This paper proposes such a model, called the User Transportation-Activity Technology (UTT) model, which supports the inclusive design of AVs. We present a review of current models of assistive technology design and their drawbacks followed by an introduction of the UTT model and its application in AV design. This paper may benefit researchers, designers, and developers of autonomous vehicles interested in addressing accessible design issues in such vehicles.
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Hafeez, Farrukh, Usman Ullah Sheikh, Abdullahi Abubakar Mas’ud, Saud Al-Shammari, Muhammad Hamid, and Ameer Azhar. "Application of the Theory of Planned Behavior in Autonomous Vehicle-Pedestrian Interaction." Applied Sciences 12, no. 5 (March 1, 2022): 2574. http://dx.doi.org/10.3390/app12052574.
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Automobile manufacturers, alongside technology providers, researchers, and public agencies, are conducting extensive testing to design autonomous vehicles (AVs) algorithms that will provide a complete understanding of road users, specifically pedestrians. Pedestrian behavior and actions determination are highly unpredictable depending on behavioral beliefs, context, and socio-demographic variables. Context includes everything that potentially affects one’s behavior; in AVs–pedestrian interaction, context may consist of weather conditions, road structure, social factors norms, and traffic volume. These influencing elements, therefore, need to be focused on during the development of pedestrian interaction algorithms. For this purpose, the pedestrian behavior questionnaire for FAVs (PBQF) is designed based on the theory of planned behavior (TPB). A total of almost 1000 voluntary participants completed this multilingual survey. As socio-demographic values and physiological perception varies with local norms, regions, and ethnicity, participants from 27 countries were therefore chosen to account for this variation. One of the key findings of this study is the influence of pedestrian attributes and the context on pedestrian behavior. Pedestrian action cannot be understood without visual observation of the pedestrian themselves and their context. The findings showed that pedestrians build communication with vehicles based on their driving styles. The vehicle’s driving style leads pedestrians to think that the vehicle is human-driven or autonomous. The results also revealed that pedestrians use several cues to show their intention. The general perception of AVs was also analyzed, and the communication between AVs and pedestrians with different displaying options was investigated.
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Ren, Weixi, Bo Yu, Yuren Chen, and Kun Gao. "Divergent Effects of Factors on Crash Severity under Autonomous and Conventional Driving Modes Using a Hierarchical Bayesian Approach." International Journal of Environmental Research and Public Health 19, no. 18 (September 9, 2022): 11358. http://dx.doi.org/10.3390/ijerph191811358.
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Influencing factors on crash severity involved with autonomous vehicles (AVs) have been paid increasing attention. However, there is a lack of comparative analyses of those factors between AVs and human-driven vehicles. To fill this research gap, the study aims to explore the divergent effects of factors on crash severity under autonomous and conventional (i.e., human-driven) driving modes. This study obtained 180 publicly available autonomous vehicle crash data, and 39 explanatory variables were extracted from three categories, including environment, roads, and vehicles. Then, a hierarchical Bayesian approach was applied to analyze the impacting factors on crash severity (i.e., injury or no injury) under both driving modes with considering unobserved heterogeneities. The results showed that some influencing factors affected both driving modes, but their degrees were different. For example, daily visitors’ flowrate had a greater impact on the crash severity under the conventional driving mode. More influencing factors only had significant impacts on one of the driving modes. For example, in the autonomous driving mode, mixed land use increased the severity of crashes, while daytime had the opposite effects. This study could contribute to specifying more appropriate policies to reduce the crash severity of both autonomous and human-driven vehicles especially in mixed traffic conditions.
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Jiang, Nan. "Optimal Signal Design for Mixed Equilibrium Networks with Autonomous and Regular Vehicles." Journal of Advanced Transportation 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/5649823.
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A signal design problem is studied for efficiently managing autonomous vehicles (AVs) and regular vehicles (RVs) simultaneously in transportation networks. AVs and RVs move on separate lanes and two types of vehicles share the green times at the same intersections. The signal design problem is formulated as a bilevel program. The lower-level model describes a mixed equilibrium where autonomous vehicles follow the Cournot-Nash (CN) principle and RVs follow the user equilibrium (UE) principle. In the upper-level model, signal timings are optimized at signalized intersections to allocate appropriate green times to both autonomous and RVs to minimize system travel cost. The sensitivity analysis based method is used to solve the bilevel optimization model. Various signal control strategies are evaluated through numerical examples and some insightful findings are obtained. It was found that the number of phases at intersections should be reduced for the optimal control of the AVs and RVs in the mixed networks. More importantly, incorporating AVs into the transportation network would improve the system performance due to the value of AV technologies in reducing random delays at intersections. Meanwhile, travelers prefer to choose AVs when the networks turn to be congested.
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Wang, Tianlu, and Xiaoxiao Hu. "The Impact of Autonomous Vehicles on People's Use of Vehicles and the Possible Environmental Pollution." Highlights in Science, Engineering and Technology 25 (December 13, 2022): 368–73. http://dx.doi.org/10.54097/hset.v25i.3543.
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This paper gives the introduction and impact analysis of autonomous vehicles (AVs). The intention of inventing AVs is to facilitate people's life and to reduce the waste of recourses. It brings several impacts to public society from environmental and other perspectives. Research finds that as the application of AVs is boosting, the vehicle miles traveled (VMTs) of self-driving cars keep increasing. This phenomenon was affected by a few reasons: expanded user groups, increased public transportation, and some personal factors. Furthermore, considering the environmental impacts such as the relationship between energy consumption, life span, and frequency of use. By discovering the negative impact of AVs on humans and the whole society, some of these impacts are listed, like it reduces the labor force and causes radiation to the human body. It is undoubtful that AVs have brought many improvements to human life, it contains drawbacks due to the immature technology and short development period, but protocols and technology advancements will help to minimize these drawbacks as this technology is getting more mature.
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Othman, Kareem. "Impact of Autonomous Vehicles on the Physical Infrastructure: Changes and Challenges." Designs 5, no. 3 (July 8, 2021): 40. http://dx.doi.org/10.3390/designs5030040.
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Over the last few years, autonomous vehicles (AVs) have witnessed tremendous worldwide interest. Although AVs have been extensively studied in the literature regarding their benefits, implications, and public acceptance, research on the physical infrastructure requirements for autonomous vehicles is still in the infancy stage. For the road infrastructure, AVs can be very promising; however, AVs might introduce new risks and challenges. This paper investigates the impact of AVs on the physical infrastructure with the objective of revealing the infrastructure changes and challenges in the era of AVs. In AVs, the human factor, which is the major factor that influences the geometric design, will not be a concern anymore so the geometric design requirements can be relaxed. On the other hand, the decrease in the wheel wander, because of the lane-keeping system, and the increase in the lane capacity, because of the elimination of the human factor, will bring an accelerated rutting potential and will quickly deteriorate the pavement condition. Additionally, the existing structural design methods for bridges are not safe to support autonomous truck platoons. For parking lots, AVs have the potential to significantly increase the capacity of parking lots using the blocking strategy. However, the implementation of this parking strategy faces multiple issues such as the inconsistent marking system. Finally, AVs will need new infrastructure facilities such as safe harbor areas.
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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.
Full textAbstract:
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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Azam, Muhammad, Sitti Asmah Hassan, and Othman Che Puan. "Autonomous Vehicles in Mixed Traffic Conditions—A Bibliometric Analysis." Sustainability 14, no. 17 (August 29, 2022): 10743. http://dx.doi.org/10.3390/su141710743.
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Autonomous Vehicles (AVs) with their immaculate sensing and navigating capabilities are expected to revolutionize urban mobility. Despite the expected benefits, this emerging technology has certain implications pertaining to their deployment in mixed traffic streams, owing to different driving logics than Human-driven Vehicles (HVs). Many researchers have been working to devise a sustainable urban transport system by considering the operational and safety aspects of mixed traffic during the transition phase. However, limited scholarly attention has been devoted to mapping an overview of this research area. This paper attempts to map the state of the art of scientific production about autonomous vehicles in mixed traffic conditions, using a bibliometric analysis of 374 documents extracted from the Scopus database from 1999 to 2021. The VOSviewer 1.1.18 and Biblioshiny 3.1 software were used to demonstrate the progress status of the publications concerned. The analysis revealed that the number of publications has continuously increased during the last five years. The text analysis showed that the author keywords “autonomous vehicles” and “mixed traffic” dominated the other author keywords because of their frequent occurrence. From thematic analysis, three research stages associated with AVs were identified; pre-development (1999–2017), development (2017–2020) and deployment (2021). The study highlighted the potential research areas, such as involvement of autonomous vehicles in transportation planning, interaction between autonomous vehicles and human driven vehicles, traffic and energy efficiencies associated with automated driving, penetration rates for autonomous vehicles in mixed traffic scenarios, and safe and efficient operation of autonomous vehicles in mixed traffic environment. Additionally, discussion on the three key aspects was conducted, including the impacts of AVs, their driving characteristics and strategies for their successful deployment in context of mixed traffic. This paper provides ample future directions to the people willing to work in this area of autonomous vehicles in mixed traffic conditions. The study also revealed current trends as well as potential future hotspots in the area of autonomous vehicles in mixed traffic.
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Ahmed, Hafiz Usman, Ying Huang, and Pan Lu. "A Review of Car-Following Models and Modeling Tools for Human and Autonomous-Ready Driving Behaviors in Micro-Simulation." Smart Cities 4, no. 1 (March 3, 2021): 314–35. http://dx.doi.org/10.3390/smartcities4010019.
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The platform of a microscopic traffic simulation provides an opportunity to study the driving behavior of vehicles on a roadway system. Compared to traditional conventional cars with human drivers, the car-following behaviors of autonomous vehicles (AVs) and connected autonomous vehicles (CAVs) would be quite different and hence require additional modeling efforts. This paper presents a thorough review of the literature on the car-following models used in prevalent micro-simulation tools for vehicles with both human and robot drivers. Specifically, the car-following logics such as the Wiedemann model and adaptive cruise control technology were reviewed based on the vehicle’s dynamic behavior and driving environments. In addition, some of the more recent “AV-ready (autonomous vehicles ready) tools” in micro-simulation platforms are also discussed in this paper.
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Morando, Mark Mario, Qingyun Tian, Long T. Truong, and Hai L. Vu. "Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures." Journal of Advanced Transportation 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/6135183.
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Autonomous vehicle (AV) technology has advanced rapidly in recent years with some automated features already available in vehicles on the market. AVs are expected to reduce traffic crashes as the majority of crashes are related to driver errors, fatigue, alcohol, or drugs. However, very little research has been conducted to estimate the safety impact of AVs. This paper aims to investigate the safety impacts of AVs using a simulation-based surrogate safety measure approach. To this end, safety impacts are explored through the number of conflicts extracted from the VISSIM traffic microsimulator using the Surrogate Safety Assessment Model (SSAM). Behaviours of human-driven vehicles (HVs) and AVs (level 4 automation) are modelled within the VISSIM’s car-following model. The safety investigation is conducted for two case studies, that is, a signalised intersection and a roundabout, under various AV penetration rates. Results suggest that AVs improve safety significantly with high penetration rates, even when they travel with shorter headways to improve road capacity and reduce delay. For the signalised intersection, AVs reduce the number of conflicts by 20% to 65% with the AV penetration rates of between 50% and 100% (statistically significant at p<0.05). For the roundabout, the number of conflicts is reduced by 29% to 64% with the 100% AV penetration rate (statistically significant at p<0.05).
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Bradley, Christopher, and Victoria Preston. "A self driving license: Ensuring autonomous vehicles deliver on the promise of safer roads." MIT Science Policy Review 1 (August 20, 2020): 76–86. http://dx.doi.org/10.38105/spr.k3ju2v9okk.
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Upon maturation, autonomous vehicles (AVs) have the potential to provide significant benefit to society. A breadth of partially autonomous systems are already commercially available, and vehicles with advanced capabilities are tested and deployed on public roads. Although the advancement of AV technology is highly anticipated, the future of the industry currently rests on uncertain ground with respect to regulatory oversight. The current industry standards and legal regulations which apply to AVs are only equipped to fully ensure that simple autonomous capabilities are safe. As vehicles become more autonomous, and as driving decisions are shifted from human to computer, a regulatory paradigm shift will be necessary. This article reviews the present state of AV safety standards and regulations, and discusses the potential for regulatory evolution.
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Liu, Cong-Jian, Fang-Kai Wang, Zhuang-Zhuang Wang, Tao Wang, and Ze-Hao Jiang. "Autonomous Vehicles for Enhancing Expressway Capacity: A Dynamic Perspective." Sustainability 14, no. 9 (April 25, 2022): 5193. http://dx.doi.org/10.3390/su14095193.
Full textAbstract:
With rapidly developing communication and autonomous-driving technology, traffic flow on road networks will change from homogeneous human-driven vehicle (HDV) traffic flow to heterogeneous mixed traffic flow (MTF) comprising HDVs, autonomous vehicles (AVs), and connective-and-autonomous vehicles (CAVs). To understand the changes in the MTF of transportation engineering, we investigated the reserved capacity (RC) and right-of-way (ROW) reallocation policy that should be utilized under MTF scenarios. We established an MTF-based theoretical model to calculate the expressway segment capacity, theoretically analyzed the influence of the market penetration rate (MPR) on capacity and validated the model through numerical analysis. The results showed that the MPR of AVs and CAVs can enhance the MTF RC that is within 0–200% and that the platooning rate of CAVs positively influences the MTF RC. CAV popularization does not necessarily lead to a rapid increase in the transportation system efficiency when the MPR is <40% but significantly improves the efficiency of existing urban transportation facilities. When the MPR is >40%, the greatest enhancement is 4800 pcu/h/lane in terms of RC. A ROW reallocation policy that equips CAV-dedicated lanes according to the MPR of AVs and CAVs can enhance the capacity of expressway systems by 500 pcu/h/lane in terms of RC.
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Liu, Cong-Jian, Fang-Kai Wang, Zhuang-Zhuang Wang, Tao Wang, and Ze-Hao Jiang. "Autonomous Vehicles for Enhancing Expressway Capacity: A Dynamic Perspective." Sustainability 14, no. 9 (April 25, 2022): 5193. http://dx.doi.org/10.3390/su14095193.
Full textAbstract:
With rapidly developing communication and autonomous-driving technology, traffic flow on road networks will change from homogeneous human-driven vehicle (HDV) traffic flow to heterogeneous mixed traffic flow (MTF) comprising HDVs, autonomous vehicles (AVs), and connective-and-autonomous vehicles (CAVs). To understand the changes in the MTF of transportation engineering, we investigated the reserved capacity (RC) and right-of-way (ROW) reallocation policy that should be utilized under MTF scenarios. We established an MTF-based theoretical model to calculate the expressway segment capacity, theoretically analyzed the influence of the market penetration rate (MPR) on capacity and validated the model through numerical analysis. The results showed that the MPR of AVs and CAVs can enhance the MTF RC that is within 0–200% and that the platooning rate of CAVs positively influences the MTF RC. CAV popularization does not necessarily lead to a rapid increase in the transportation system efficiency when the MPR is <40% but significantly improves the efficiency of existing urban transportation facilities. When the MPR is >40%, the greatest enhancement is 4800 pcu/h/lane in terms of RC. A ROW reallocation policy that equips CAV-dedicated lanes according to the MPR of AVs and CAVs can enhance the capacity of expressway systems by 500 pcu/h/lane in terms of RC.
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Huang, Chunxi, Xiao Wen, Dengbo He, and Sisi Jian. "Sharing the Road: How Human Drivers Interact with Autonomous Vehicles on Highways." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 66, no. 1 (September 2022): 1437–41. http://dx.doi.org/10.1177/1071181322661165.
Full textAbstract:
With more autonomous vehicles (AVs) being tested or deployed on public roads, human-driven vehicles (HVs) have to share the road with AVs. However, human drivers may not interact AVs the same way as they interact with HVs. Very few studies have investigated drivers’ behaviors when sharing the road with AVs. Based on a real-world dataset, our study explored drivers’ interactions with AVs in two types of events on highway, i.e., car-following event and car-passing event. The results show that, compared to interacting with HVs, drivers tended to keep a larger safety margin (i.e., larger gap distance and time gap) at high speed in both types of events when interacting with AVs. At the same time, drivers seemed to have difficulty anticipating AVs’ speed changes at high speed, as indicated by a larger standard deviation of the HVs’ speed and a smaller time to collision when following AVs versus following HVs.
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Jing, Peng, Gang Xu, Yuexia Chen, Yuji Shi, and Fengping Zhan. "The Determinants behind the Acceptance of Autonomous Vehicles: A Systematic Review." Sustainability 12, no. 5 (February 25, 2020): 1719. http://dx.doi.org/10.3390/su12051719.
Full textAbstract:
Excessive dependence on autonomous vehicles (AVs) may exacerbate traffic congestion and increase exhaust emissions in the future. The diffusion of AVs may be significantly affected by the public’s acceptance. A few factors that may affect people’s acceptance of AVs have been researched in the existing studies, one-third of which cited behavioral theories, while the rest did not. A total of seven factors with behavior theories are screened out that significantly affect the acceptance intention, including perceived ease of use, attitude, social norm, trust, perceived usefulness, perceived risk, and compatibility. Six factors without behavior theories are summed up that affect AV acceptance, namely safety, performance-to-price value, mobility, value of travel time, symbolic value, and environmentally friendly. We found that people in Europe and Asia have substantial differences in attitudes toward AVs and that safety is one of the most concerned factors of AVs by scholars and respondents. Public acceptance of the different types of AVs and consumers’ dynamic preferences for AVs are highlighted in the review too. The quality of literature is systematically assessed based on previously established instruments and tailored for the current review. The results of the assessment show potential opportunities for future research, such as the citation of behavior theories and access to longitudinal data. Additionally, the experimental methods and the utilization of mathematical and theoretical methods could be optimized.
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Hunter, Jacob G., Matthew Konishi, Neera Jain, Kumar Akash, Xingwei Wu, Teruhisa Misu, and Tahira Reid. "The Interaction Gap: A Step Toward Understanding Trust in Autonomous Vehicles Between Encounters." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 66, no. 1 (September 2022): 147–51. http://dx.doi.org/10.1177/1071181322661311.
Full textAbstract:
Shared autonomous vehicles (SAVs) will be introduced in greater numbers over the coming decade. Due to rapid advances in shared mobility and the slower development of fully autonomous vehicles (AVs), SAVs will likely be deployed before privately-owned AVs. Moreover, existing shared mobility services are transitioning their vehicle fleets toward those with increasingly higher levels of driving automation. Consequently, people who use shared vehicles on an “as needed” basis will have infrequent interactions with automated driving, thereby experiencing interaction gaps. Using human trust data of 25 participants, we show that interaction gaps can affect human trust in automated driving. Participants engaged in a simulator study consisting of two interactions separated by a one-week interaction gap. A moderate, inverse correlation was found between the change in trust during the initial interaction and the interaction gap, suggesting people “forget” some of their gained trust or distrust in automation during an interaction gap.