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Relevant bibliographies by topics / Autonomous vehicle testing

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Academic literature on the topic 'Autonomous vehicle testing'

Author: Grafiati

Published: 15 March 2025

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Journal articles on the topic "Autonomous vehicle testing"

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Tulsyan, Ansh, Anshul Bhardwaj, Pranjal Shukla, Piyush Gautam, and Tushar Singh. "Autonomous Vehicle Simulation." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (January 5, 2025): 1–9. https://doi.org/10.55041/ijsrem40459.

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Autonomous vehicles represent a revolutionary advancement in transportation technology, relying heavily on sophisticated simulations for development and testing. This abstract presents an approach to autonomous vehicle simulation utilizing the Udacity Self-Driving Car Nanodegree platform coupled with Convolutional Neural Networks (CNNs) for perception tasks. The simulation environment provided by Udacity offers a realistic representation of urban driving scenarios, allowing developers to test and train autonomous vehicle algorithms in a virtual setting before deploying them on real-world roads. This environment includes various elements such as traffic lights, pedestrians, and other vehicles, providing a comprehensive testbed for algorithmic validation. To enhance the perception capabilities of autonomous vehicles within this simulated environment, Convolutional Neural Networks (CNNs) are employed. CNNs have proven effective in image recognition tasks, making them well-suited for tasks like object detection and classification crucial to autonomous driving. The neural network is trained on a diverse dataset, enabling it to accurately identify and interpret the surrounding environment through sensor data, such as camera images. The integration of CNNs with the Udacity simulation platform enables the autonomous vehicle to make informed decisions based on its perception of the environment. The trained CNN serves as a crucial component in the overall perception pipeline, enhancing the vehicle's ability to recognize and respond to dynamic and complex scenarios. Keywords—Autonomous vehicle simulation, Artificial Intelligence, Object Recognition, Real-Time Processing, convolutional neural networks.

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Dickens, John, Thabisa Maweni, Tiro Setati, and Zubair Suddoo. "Design of HERMES: a mobile autonomous surveillance robot for security patrol." MATEC Web of Conferences 388 (2023): 04005. http://dx.doi.org/10.1051/matecconf/202338804005.

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The HERMES autonomous surveillance robot platform is a low-cost outdoor autonomous surveillance vehicle. It is designed to autonomously patrol outdoor areas performing surveillance and providing automated alerts of detected vehicles and people. The design and testing of this system are covered in this paper. The design philosophy focused on the use of off-the-shelf components wherever possible with the base of the robot being a modified electric quadbike. The testing has verified that the surveillance robot can perform real-time person and vehicle detection, video streaming, manual and autonomous navigation on a low-cost platform. The development of the robot platform is continuing with the current focus being on the improvement of the autonomous navigation, ingress protection (IP) rating and verification of the battery life.

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Abu Bakar, Amirul Ibrahim, Mohd Azman Abas, Mohd Farid Muhamad Said, and Tengku Azrul Tengku Azhar. "Synthesis of Autonomous Vehicle Guideline for Public Road-Testing Sustainability." Sustainability 14, no. 3 (January 27, 2022): 1456. http://dx.doi.org/10.3390/su14031456.

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Autonomous vehicles have the potential to reduce the risk of accidents as they eliminate the element of human error from driving. Lack of attention, poor judgement, or physical limitations may lead to road incidents. Thus, the development and deployment of autonomous vehicles should be a priority. However, before being publicly available, autonomous vehicles must be tested to ensure their viability and safety by conducting public road testing. Autonomous vehicles have been designed and tested since the early 1900s; however, deployment of fully autonomous vehicles on public roads only started in the 2000s. Numerous countries have developed guidelines for public road testing, but those rules are not uniform, and discrepancies occur between nations. Issues such as vehicular safety, registrations, authority, insurance, cybersecurity, and infrastructures weigh differently in each country. Synthesizing these diverse national regulations into global guidelines would promote the safety and sustainability of autonomous vehicle testing and benefit all parties interested in autonomous vehicles.

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Chen, Hong Yun, Yan Qiang Li, Zi Hui Zhang, and Yong Wang. "Test Method for Decision Planning of Autonomous Vehicles Based on DQN Algorithm." E3S Web of Conferences 253 (2021): 03022. http://dx.doi.org/10.1051/e3sconf/202125303022.

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In February 2020, Beijing, China andCalifornia, USA respectively released road test reports of 2019 for autonomous vehicles. Beijing and California respectively represent the highest level of testing and application of autonomous vehicles in the two countries. This article will compare the test items, evaluation criteria and technical defects of each autonomous vehicle company in the road test reports of China and the United States, also analyze the existing problems, and propose an idea for the construction of a comprehensive test site for autonomous vehicles. This article aims to solve the prominently exposed problems in decision-making and planning in autonomous vehicles with DQN algorithm-base vehicle fleet, and to look forward to the future development trend of autonomous driving testing.

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Cao, Yicheng, Haiming Sun, Guisheng Li, Chuan Sun, Haoran Li, Junru Yang, Liangyu Tian, and Fei Li. "Multi-Environment Vehicle Trajectory Automatic Driving Scene Generation Method Based on Simulation and Real Vehicle Testing." Electronics 14, no. 5 (March 1, 2025): 1000. https://doi.org/10.3390/electronics14051000.

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As autonomous vehicles increasingly populate roads, robust testing is essential to ensure their safety and reliability. Due to the limitation that traditional testing methodologies (real-world and simulation testing) are difficult to cover a wide range of scenarios and ensure repeatability, this study proposes a novel virtual-real fusion testing approach that integrates Graph Theory and Artificial Potential Fields (APF) in virtual-real fusion autonomous vehicle testing. Conducted using SUMO software, our strategic lane change and speed adjustment simulation experiments demonstrate that our approach can efficiently handle vehicle dynamics and environmental interactions compared to traditional Rapidly-exploring Random Tree (RRT) methods. The proposed method shows a significant reduction in maneuver completion times—up to 41% faster in simulations and 55% faster in real-world tests. Field experiments at the Vehicle-Road-Cloud Integrated Platform in Suzhou High-Speed Railway New Town confirmed the method’s practical viability and robustness under real traffic conditions. The results indicate that our integrated approach enhances the authenticity and efficiency of testing, thereby advancing the development of dependable, autonomous driving systems. This research not only contributes to the theoretical framework but also has practical implications for improving autonomous vehicle testing processes.

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Kwon, Donghwoon, Ritesh Malaiya, Geumchae Yoon, Jeong-Tak Ryu, and Su-Young Pi. "A Study on Development of the Camera-Based Blind Spot Detection System Using the Deep Learning Methodology." Applied Sciences 9, no. 14 (July 23, 2019): 2941. http://dx.doi.org/10.3390/app9142941.

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One of the recent news headlines is that a pedestrian was killed by an autonomous vehicle because safety features in this vehicle did not detect an object on a road correctly. Due to this accident, some global automobile companies announced plans to postpone development of an autonomous vehicle. Furthermore, there is no doubt about the importance of safety features for autonomous vehicles. For this reason, our research goal is the development of a very safe and lightweight camera-based blind spot detection system, which can be applied to future autonomous vehicles. The blind spot detection system was implemented in open source software. Approximately 2000 vehicle images and 9000 non-vehicle images were adopted for training the Fully Connected Network (FCN) model. Other data processing concepts such as the Histogram of Oriented Gradients (HOG), heat map, and thresholding were also employed. We achieved 99.43% training accuracy and 98.99% testing accuracy of the FCN model, respectively. Source codes with respect to all the methodologies were then deployed to an off-the-shelf embedded board for actual testing on a road. Actual testing was conducted with consideration of various factors, and we confirmed 93.75% average detection accuracy with three false positives.

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Bhavsar, Parth, Plaban Das, Matthew Paugh, Kakan Dey, and Mashrur Chowdhury. "Risk Analysis of Autonomous Vehicles in Mixed Traffic Streams." Transportation Research Record: Journal of the Transportation Research Board 2625, no. 1 (January 2017): 51–61. http://dx.doi.org/10.3141/2625-06.

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The introduction of autonomous vehicles in the surface transportation system could improve traffic safety and reduce traffic congestion and negative environmental effects. Although the continuous evolution in computing, sensing, and communication technologies can improve the performance of autonomous vehicles, the new combination of autonomous automotive and electronic communication technologies will present new challenges, such as interaction with other nonautonomous vehicles, which must be addressed before implementation. The objective of this study was to identify the risks associated with the failure of an autonomous vehicle in mixed traffic streams. To identify the risks, the autonomous vehicle system was first disassembled into vehicular components and transportation infrastructure components, and then a fault tree model was developed for each system. The failure probabilities of each component were estimated by reviewing the published literature and publicly available data sources. This analysis resulted in a failure probability of about 14% resulting from a sequential failure of the autonomous vehicular components alone in the vehicle’s lifetime, particularly the components responsible for automation. After the failure probability of autonomous vehicle components was combined with the failure probability of transportation infrastructure components, an overall failure probability related to vehicular or infrastructure components was found: 158 per 1 million mi of travel. The most critical combination of events that could lead to failure of autonomous vehicles, known as minimal cut-sets, was also identified. Finally, the results of fault tree analysis were compared with real-world data available from the California Department of Motor Vehicles autonomous vehicle testing records.

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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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Cao, Hang, and Máté Zöldy. "An Investigation of Autonomous Vehicle Roundabout Situation." Periodica Polytechnica Transportation Engineering 48, no. 3 (August 4, 2019): 236–41. http://dx.doi.org/10.3311/pptr.13762.

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The aim of this paper is to evaluate the impact of connected autonomous behavior in real vehicles on vehicle fuel consumption and emission reductions. Authors provide a preliminary theoretical summary to assess the driving conditions of autonomous vehicles in roundabout, which attempts exploring the impact of driving behavior patterns on fuel consumption and emissions, and including other key factors of autonomous vehicles to reduce fuel consumption and emissions. After summarizing, driving behavior, effective in-vehicle systems, both roundabout physical parameters and vehicle type are all play an important role in energy using. ZalaZONE’s roundabout is selected for preliminary test scenario establishment, which lays a design foundation for further in-depth testing.

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Li, Mu, Yingqi Liu, and Ruiyu Feng. "How Can China’s Autonomous Vehicle Companies Use Digital Empowerment to Improve Innovation Quality?—The Role of Digital Platform Capabilities and Boundary-Spanning Search." Systems 13, no. 1 (January 10, 2025): 45. https://doi.org/10.3390/systems13010045.

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The acquisition, integration, and exchange of digital technologies considerably contribute to the improvement of corporate innovation quality, as autonomous vehicles are a complex amalgamation of multiple industrial chains. In order to address the intense global competition in the autonomous vehicles industry and help China’s enterprises establish a prominent position in technological innovation, this study innovatively integrates the concepts of digital empowerment, digital platform capabilities, and boundary-spanning search into a cohesive framework, examines the pathways of influence, and methodically builds a multiple-chain mediation model. It employs various quantitative models, such as reliability and validity testing, confirmatory factor analysis, common method bias testing, mediation effect analysis, and robustness testing. The study focuses on over a hundred companies related to autonomous vehicles in China, employing software such as SPSS26.0, AMOS26.0, PROCESS4.0, and MPLUS8.3 to conduct this analysis. The findings indicate that digital empowerment is a critical factor in the improvement of innovation quality within autonomous vehicle companies. The relationship between digital empowerment and innovation quality is partially mediated by digital platform capabilities, and the boundary-spanning search also functions as a partial intermediary. Additionally, the quality of innovation and digital empowerment are mediated by the boundary-spanning search and the capabilities of digital platforms. The results of this study provide valuable insights on how to accurately empower the high-quality development of the autonomous vehicle sector with digital technologies, revealing new perspectives on the innovation quality enhancement pathways for autonomous vehicle companies in China, offering pivotal insights amidst the escalating competition within the global autonomous vehicle sector.

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Dissertations / Theses on the topic "Autonomous vehicle testing"

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Mikesell, David Russell. "Portable automated driver for universal road vehicle dynamics testing." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1198722243.

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Kirsch, Patricia Jean. "Autonomous swarms of unmanned vehicles software control system and ground vehicle testing /." College Park, Md. : University of Maryland, 2005. http://hdl.handle.net/1903/2993.

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Thesis (M.S.) -- University of Maryland, College Park, 2005.
Thesis research directed by: Dept. of Electrical and Computer Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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Hebib, Jasmina, and Sofie Dam. "Vehicle Dynamic Models for Virtual Testing of Autonomous Trucks." Thesis, Linköpings universitet, Fordonssystem, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-155513.

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The simulator in a testing environment for trucks is dependent on accurate vehicle dynamic models. There are multiple models at Volvo, all developed to support the objectives of individual research. A selection of four, named Single Track model (STM), Global Simulation Platform (GSP), One-Track Model with linear slip (OTM) and Volvo Transport Model (VTM), are evaluated to examine the usage of them. Four diﬀerent scenarios are therefore generated to emulate common situations in traﬃc. Depending on the results, the models and their corresponding limitsforusagearedescribed. Theevaluationismadebycomparingallmodelsto the best model for each scenario by measuring the normalized error distribution. It is shown that at certain thresholds, other models can perform close enough to the best model. In the end of the report, future improvements for the evaluated models and external models are suggested.

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Nordenström, Martin. "Future certification of autonomous vehicles and the use of virtual testing methods." Thesis, KTH, Fordonsdynamik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288717.

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One of the biggest obstacles to launching autonomous vehicles is the current legislation, which currently does not cover automation level higher than level 2. Work on developing the legal requirements takes place at UN level within WP29 (The UNECE World Forum for Harmonization of Vehicle Regulations). As a world-leading vehicle manufacturer, Scania is aspiring to pave the way for sustainable transport solutions. At Scania, well-established methodologies on certification of different systems exist, although the process of certification of autonomous driving systems needs to be developed.This master thesis investigates the current situation regarding the elaboration of regulations to cover autonomous vehicles, future certification methods related to these systems, and how this applies to Scania. Particular focus is being on the investigation of virtual certification methods. This can form the basis for various departments at Scania in their work with future autonomous systems and how to get these certified.The future certification work for autonomous vehicles will be based on a validation process based on a process called the ‘Multi-pillars approach’ / ‘Three-pillars approach’. The idea is that the autonomous vehicle should be certified based on a process where the basis for certification is made by validating and justifying its systems. This will be done through simulations and other methods to ensure that the systems are satisfactory. A less extensive work should then be done in the testing of the autonomous vehicle on the test track and in traffic, where only less demanding situations must be validated.The functional requirements of the autonomous vehicle will largely control the validation process that is carried out for the ‘Multi-pillars approach’ / ‘Three-pillars approach’. For example, the definition of ODD (Operational Design Domain) is crucial for the validation that the vehicle will undergo at a later stage.
Ett av de största hindren för att lansera självkörande fordon är den nuvarande lagstiftningen som i dagsläget inte täcker automationsnivå högre än nivå 2. Arbetet med att ta fram lagkraven sker på FN nivå inom WP29 (The UNECE World Forum for Harmonization of Vehicle Regulations). Som en världsledande fordonstillverkare strävar Scania efter att bana väg för hållbara transportlösningar. På Scania finns väletablerade metoder för certifiering av olika system, men processen för certifiering av autonoma fordon måste dock utvecklas.Detta examensarbete undersöker den aktuella situationen när det gäller utformandet av regelverk för att täcka autonoma fordon, framtida certifieringsmetoder relaterade till dessa system och hur detta påverkar Scania. Särskilt fokus ligger på utredning av virtuella certifieringsmetoder. Detta kan ligga till grund för olika avdelningar på Scania i deras arbete med framtida autonoma system och hur man får dessa certifierade.Det framtida certifieringsarbetet för autonoma fordon kommer att bygga på en valideringsprocess som bygger på en process som kallas för ”Multi-pillars approach”/”Three- pillars approach”. Tanken är att fordonet ska certifieras utifrån en process där grunden till certifiering görs genom att validera och rättfärdiga sina system. Detta ska ske genom simulering och andra metoder för att säkerhetsställa att systemen är tillfredställande. Ett mindre omfattande arbete ska sedan göras i testningen av fordonen på testbana och ute i trafik, där endast mindre krävande situationer ska valideras.De funktionella kraven på fordonen kommer till stor del att styra den valideringsprocessen som görs med för ”Multi-pillars approach”/”Three-pillars approach”. Exempelvis är definierandet av ODD (Operational Design Domain) avgörande för den validering som fordonet i ett senare skede ska genomgå.

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Volland, Kirk N. "Design, construction and testing of a prototype holonomic autonomous vehicle." Thesis, Monterey, Calif. : Naval Postgraduate School, 2007. http://bosun.nps.edu/uhtbin/hyperion-image.exe/07Dec%5FVolland.pdf.

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Thesis (M.S. in Applied Physics)--Naval Postgraduate School, December 2007.
Thesis Advisor(s): Harkins, Richard. "December 2007." Description based on title screen as viewed on January 24, 2008. Includes bibliographical references (p. 189-192). Also available in print.

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Arslan, Suat. "Testing and evaluation of the Small Autonomous Underwater Vehicle Navigation System (SANS)." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2000. http://handle.dtic.mil/100.2/ADA376607.

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Thesis (M.S. in Electrical Engineering) Naval Postgraduate School, March 2000.
Thesis advisor(s): Yun, Xiaoping; Bachmann, Eric R. "March 2000." Includes bibliographical references (p. 93-94). Also available online.

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Jun, Hyun Il. "The implementation and testing of a robotic arm on an autonomous vehicle." Thesis, Monterey, Calif. : Naval Postgraduate School, 2007. http://bosun.nps.edu/uhtbin/hyperion-image.exe/07Dec%5FJun.pdf.

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Thesis (M.S. in Applied Physics)--Naval Postgraduate School, December 2007.
Thesis Advisor(s): Harkins, Richard. "December 2007." Description based on title screen as viewed on January 18, 2008. Includes bibliographical references (p. 35-36). Also available in print.

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Doepke, Edward Brady. "DESIGN AND FLIGHT TESTING OF A WARPING WING FOR AUTONOMOUS FLIGHT CONTROL." UKnowledge, 2012. http://uknowledge.uky.edu/me_etds/20.

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Inflatable-wing Unmanned Aerial Vehicles (UAVs) have the ability to be packed in a fraction of their deployed volume. This makes them ideal for many deployable UAV designs, but inflatable wings can be flexible and don’t have conventional control surfaces. This thesis will investigate the use of wing warping as a means of autonomous control for inflatable wings. Due to complexities associated with manufacturing inflatable structures a new method of rapid prototyping deformable wings is used in place of inflatables to decrease cost and design-cycle time. A UAV testbed was developed and integrated with the warping wings and flown in a series of flight tests. The warping wing flew both under manual control and autopilot stabilization.

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Mercer, Anthony Scott. "Autonomous unmanned ground vehicle for non-destructive testing of fiber reinforced polymer bridge decks." Morgantown, W. Va. : [West Virginia University Libraries], 2006. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4943.

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Thesis (M.S.)--West Virginia University, 2006.
Title from document title page. Document formatted into pages; contains x, 100 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 83-86).

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Sevcik, Keith Wayne Oh Paul Yu. "A hardware-in-the-loop testing facility for unmanned aerial vehicle sensor suites and control algorithms /." Philadelphia, Pa. : Drexel University, 2010. http://hdl.handle.net/1860/3262.

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Books on the topic "Autonomous vehicle testing"

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Montilla, Michael A. N. Observations from Autonomous Vehicle Testing in Phoenix, Noteworthy Ways Existing Political Practices and Commuting Behaviors Will Affect Planning for Self-Driving Vehicles. [New York, N.Y.?]: [publisher not identified], 2019.

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Fanelli, Francesco. Development and Testing of Navigation Algorithms for Autonomous Underwater Vehicles. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-15596-4.

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Canis, Bill. Issues in Autonomous Vehicle Testing and Deployment. Independently Published, 2019.

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Testing and Evaluation of the Small Autonomous Underwater Vehicle Navigation System (SANS). Storming Media, 2000.

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Fanelli, Francesco. Development and Testing of Navigation Algorithms for Autonomous Underwater Vehicles. Springer, 2019.

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Stanton, Neville, Patrick Langdon, and Kirsten M. A. Revell. Designing Interaction and Interfaces for Automated Vehicles: User-Centred Ecological Design and Testing. Taylor & Francis Group, 2021.

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Stanton, Neville, Patrick Langdon, and Kirsten M. A. Revell. Designing Interaction and Interfaces for Automated Vehicles: User-Centred Ecological Design and Testing. Taylor & Francis Group, 2021.

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Stanton, Neville, Patrick Langdon, and Kirsten M. A. Revell. Designing Interaction and Interfaces for Automated Vehicles: User-Centred Ecological Design and Testing. Taylor & Francis Group, 2021.

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Designing Interaction and Interfaces for Automated Vehicles: User-Centred Ecological Design and Testing. Taylor & Francis Group, 2021.

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Test and Evaluation of Aircraft Avionics and Weapon Systems. Scitech Publishing, 2014.

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Book chapters on the topic "Autonomous vehicle testing"

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Corey, Jonathan, and Heng Wei. "Autonomous Vehicle Testing." In Disruptive Emerging Transportation Technologies, 105–38. Reston, VA: American Society of Civil Engineers, 2022. http://dx.doi.org/10.1061/9780784415986.ch3.

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Soriano, Bernard C., Stephanie L. Dougherty, Brian G. Soublet, and Kristin J. Triepke. "Regulations for Testing Autonomous Vehicles in California." In Road Vehicle Automation 2, 29–33. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19078-5_3.

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Solmaz, Selim, Franz Holzinger, Marlies Mischinger, Martin Rudigier, and Jakob Reckenzaun. "Novel Hybrid-Testing Paradigms for Automated Vehicle and ADAS Function Development." In Towards Connected and Autonomous Vehicle Highways, 193–228. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-66042-0_8.

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Pataki, Márton, and Zsolt Szalay. "Development of an Advanced Durable Test Target for Autonomous Emergency Brake Testing." In Vehicle and Automotive Engineering 3, 3–17. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-9529-5_1.

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Goetzl, Thomas, Sven Kopacz, and Henrik Liebau. "Digital Twin Concepts for Autonomous and Electric Vehicle Testing." In Proceedings, 73–80. Wiesbaden: Springer Fachmedien Wiesbaden, 2023. http://dx.doi.org/10.1007/978-3-658-42236-3_6.

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Chucholowski, F., C. Gnandt, C. Hepperle, and Sebastian Hafner. "Close to reality surrounding model for virtual testing of autonomous driving and ADAS." In Advanced Vehicle Control AVEC’16, 85–92. CRC Press/Balkema, P.O. Box 11320, 2301 EH Leiden, The Netherlands, e-mail: Pub.NL@taylorandfrancis.com, www.crcpress.com – www.taylorandfrancis.com: Crc Press, 2016. http://dx.doi.org/10.1201/9781315265285-15.

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Saraoğlu, Mustafa, Qihang Shi, Andrey Morozov, and Klaus Janschek. "Virtual validation of autonomous vehicle safety through simulation-based testing." In Proceedings, 419–34. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-29943-9_33.

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Jan, Qazi Hamza, Jan Markus Arnold Kleen, and Karsten Berns. "Simulated Pedestrian Modelling for Reliable Testing of Autonomous Vehicle in Pedestrian Zones." In Communications in Computer and Information Science, 290–307. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89170-1_15.

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Fernández, César Omar Chacón, Sergio Fernández Balaguer, Lucía Isasi de la Iglesia, and Borja Gorriz Espinar. "Autonomous Bus Depot Management: Operator’s Lessons Learned and Cost Analysis Perspective." In Lecture Notes in Mobility, 79–95. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-71793-2_6.

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AbstractThis study delves into autonomous bus depot management at EMT Madrid, the Madrid Public Transport Company, within the Horizon 2020 SHOW project (GA No 875530). Its aim is to boost operational efficiency and optimize resource usage, particularly by addressing unproductive hours for bus drivers. It examines the technical feasibility of automating manual depot tasks like vehicle charging, cleaning, and parking through advanced sensor technology and control systems. The pilot at Carabanchel bus depot involved automated vehicles (AVs) with perception sensors, control mechanisms, and centralized decision-making units, testing services like internal transport, autoparking, and teleoperation. Over eleven months, the AV fleet performed successfully without incidents. The findings indicate automation's promises in reducing operational costs and enhancing resource utilization, though, challenges like initial investments, technical constraints, and regulations persist. Recommendations are made to foster public–private collaboration for innovation in public transport and for market development.

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Pao, Wing Yi, Long Li, Joshua Howorth, Martin Agelin-Chaab, Langis Roy, Julian Knutzen, Alexis Baltazar y Jimenez, and Klaus Muenker. "Wind Tunnel Testing Methodology for Autonomous Vehicle Optical Sensors in Adverse Weather Conditions." In Proceedings, 13–39. Wiesbaden: Springer Fachmedien Wiesbaden, 2023. http://dx.doi.org/10.1007/978-3-658-42236-3_2.

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Conference papers on the topic "Autonomous vehicle testing"

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Gómez, Gabriel, René Játiva, and Gustavo Scaglia. "Commissioning and testing of an autonomous ground vehicle." In 2024 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI), 1–6. IEEE, 2024. http://dx.doi.org/10.1109/colcaci63187.2024.10666545.

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Wang, Weijie, Houping Wu, Chundi Zheng, Tao Liang, Shaozhe Cui, Xikuai Xie, Guojin Feng, Haiyong Gan, and Yingwei He. "Research on calibration method for optical characteristics of pedestrian targets in autonomous vehicle testing." In Optoelectronics Testing and Measurement, edited by Sen Han, 15. SPIE, 2024. https://doi.org/10.1117/12.3047661.

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Silva-Sassaman, Dinithi, Mingi Jeong, Paul Sassaman, Zitong Wu, and Alberto Quattrini Li. "CataBotSim: A Realistic Aquatic Simulator for Autonomous Surface Vehicle Testing." In 2024 Eighth IEEE International Conference on Robotic Computing (IRC), 202–9. IEEE, 2024. https://doi.org/10.1109/irc63610.2024.00043.

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Batet, Gerard, David Sarria, Marta Real, Spartacus Gomariz, Joaquin Del Rio, Narcis Palomeras, and Ivan Masmitja. "Testing autonomous underwater vehicle compatibility with bidirectional acoustic tags for biotelemetry." In 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE), 824–29. IEEE, 2024. http://dx.doi.org/10.1109/case59546.2024.10711493.

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Huang, Yuqi, Xiaoji Zhou, Deng Pan, Qiang Zhang, Jian Zhang, Yufei Chen, and Chengjin Xiao. "Iterative Scenario Searching with PSO: Improving Simulation Efficiency for Autonomous Vehicle Testing." In 2024 IEEE 22nd International Conference on Industrial Informatics (INDIN), 1–6. IEEE, 2024. https://doi.org/10.1109/indin58382.2024.10774382.

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Zhang, Zhiyuan, and Panagiotis Tsiotras. "BuzzRacer: A Palm-sized Autonomous Vehicle Platform for Testing Multi-Agent Adversarial Decision-Making." In 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 8510–15. IEEE, 2024. https://doi.org/10.1109/iros58592.2024.10802853.

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Gao, Hang, Zhen Liu, Xun Gong, and Hong Chen. "Generation of Autonomous Vehicle Testing Trajectories for Cut-In Scenario Integrating Data and Kinematics." In 2024 China Automation Congress (CAC), 4532–37. IEEE, 2024. https://doi.org/10.1109/cac63892.2024.10865443.

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Compere, Marc, Garrett Holden, Otto Legon, and Roberto Martinez Cruz. "MoVE: A Mobility Virtual Environment for Autonomous Vehicle Testing." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-10936.

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Abstract Autonomous vehicle researchers need a common framework in which to test autonomous vehicles and algorithms along a realism spectrum from simulation-only to real vehicles and real people. The community needs an open-source, publicly available framework, with source code, in which to develop, simulate, execute, and post-process multi-vehicle tests. This paper presents a Mobility Virtual Environment (MoVE) for testing autonomous system algorithms, vehicles, and their interactions with real and simulated vehicles and pedestrians. The result is a network-centric framework designed to represent multiple real and multiple virtual vehicles interacting and possibly communicating with each other in a common coordinate frame with a common timestamp. This paper presents a literature review of comparable autonomous vehicle softwares, presents MoVE concepts and architecture, and presents three experimental tests with multiple virtual and real vehicles, with real pedestrians. The first scenario is a traffic wave simulation using a real lead vehicle and 3 real follower vehicles. The second scenario is a medical evacuation scenario with 2 real pedestrians and 1 real vehicles. Real pedestrians are represented using live-GPS-followers streaming GPS position from mobile phones over the cellular network. Time-history and spatial plots of real and virtual vehicles are presented with vehicle-to-vehicle distance calculations indicating where and when potential collisions were detected and avoided. The third scenario highlights the avoid() behavior successfully avoiding other virtual vehicles and 1 real pedestrian in a small outdoor area. The MoVE set of concepts and interfaces are implemented as open-source software available for use and customization within the autonomous vehicle community. MoVE is freely available under the GPLv3 open-source license at gitlab.com/comperem/move.

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Mitrović, Miloš, Dušan Opsenica, Uroš Stanojčić, Pavle Rađenović, and Dragan Stamenković. "Autonomous vehicle testing – Serbia’s experience." In 2023 31st Telecommunications Forum (TELFOR). IEEE, 2023. http://dx.doi.org/10.1109/telfor59449.2023.10372711.

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Aradi, Szilard, Tamas Becsi, and Peter Gaspar. "Experimental vehicle development for testing autonomous vehicle functions." In 2014 IEEE/ASME 10th International Conference on Mechatronic and Embedded Systems and Applications (MESA). IEEE, 2014. http://dx.doi.org/10.1109/mesa.2014.6935534.

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Reports on the topic "Autonomous vehicle testing"

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Smith, Emma, Julie Webster, and Annette Stumpf. Autonomous Transport Innovation : the regulatory environment of autonomous vehicles. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/42025.

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This technical note series under the Autonomous Transport Innovation research program is intended to be a primer on autonomous vehicles (AVs), their testing, and associated infrastructure. A review of the regulatory environment for autonomous vehicles is necessary to define rules imposed on technology or operations of autonomous vehicles in various capacities. Acknowledging such regulation will aid in productive closed-course site development by structuring the course based on what autonomous vehicle developers and manufacturers must program their vehicles to adhere to in a given setting.

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Gross, Matthew, and Julie Webster. Autonomous Transport Innovation : a review of enabling technologies. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/42028.

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This document is the first of the technical note series under the Autonomous Transport Innovation (ATI) research program. The series intends to be an introduction on autonomous vehicles (AVs), their testing, and associated infrastructure. A review of technologies that enable vehicle autonomy is necessary to provide the basis for understanding vehicle performance in testing scenarios and in actual use.

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Rolufs, Angela, Amelia Trout, Kevin Palmer, Clark Boriack, Bryan Brilhart, and Annette Stumpf. Autonomous Transport Innovation (ATI) : integration of autonomous electric vehicles into a tactical microgrid. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/42160.

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The objective of the Autonomous Transport Innovation (ATI) technical research program is to investigate current gaps and challenges then develop solutions to integrate emerging electric transport vehicles, vehicle autonomy, vehicle-to-grid (V2G) charging and microgrid technologies with military legacy equipment. The ATI research area objectives are to: identify unique military requirements for autonomous transportation technologies; identify currently available technologies that can be adopted for military applications and validate the suitability of these technologies to close need gaps; identify research and operational tests for autonomous transport vehicles; investigate requirements for testing and demonstrating of bidirectional vehicle charging within a tactical environment; develop requirements for a sensored, living laboratory that will be used to assess the performance of autonomous innovations; and integrate open standards to promote interoperability and broad-platform compatibility. The research performed resulted in an approach to develop a sensored, living laboratory with operational testing capability to assess the safety, utility, interoperability, and resiliency of autonomous electric transport and V2G technologies in a tactical microgrid. The living laboratory will support research and assessment of emerging technologies and determine the prospect for implementation in defense transport operations and contingency base energy resilience.

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Parker, Michael, Alex Stott, Brian Quinn, Bruce Elder, Tate Meehan, and Sally Shoop. Joint Chilean and US mobility testing in extreme environments. Engineer Research and Development Center (U.S.), November 2021. http://dx.doi.org/10.21079/11681/42362.

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Vehicle mobility in cold and challenging terrains is of interest to both the US and Chilean Armies. Mobility in winter conditions is highly vehicle dependent with autonomous vehicles experiencing additional challenges over manned vehicles. They lack the ability to make informed decisions based on what they are “seeing” and instead need to rely on input from sensors on the vehicle, or from Unmanned Aerial Systems (UAS) or satellite data collections. This work focuses on onboard vehicle Controller Area Network (CAN) Bus sensors, driver input sensors, and some externally mounted sensors to assist with terrain identification and overall vehicle mobility. Analysis of winter vehicle/sensor data collected in collaboration with the Chilean Army in Lonquimay, Chile during July and August 2019 will be discussed in this report.

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Webster, Julie, Emma Smith, Annette Stumpf, and Megan Fuhler. Autonomous vehicle testing : a survey of commercial test sites and features. Engineer Research and Development Center (U.S.), March 2024. http://dx.doi.org/10.21079/11681/48334.

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Connected and autonomous technologies are valuable to the Army because of their recognized potential to reduce the number of personnel exposed to threats in forward operations. The successful integration of such technologies has the potential to reduce Soldier deaths and injuries. Automation of routine tasks can also allow warfighters to focus their time on more strategic efforts. Furthermore, a reduction in manpower is expected to proportionally reduce energy use and material supply and resupply demands while bolstering resilience. To achieve these benefits, the reliability, safety, and utility of connected and autonomous systems must be successfully demonstrated in a variety of conditions before widespread adoption. Therefore, the Army needs a realistic testing environment to develop, test, and evaluate emerging technologies. This environment and its supporting infrastructure should provide a variety of terrain, functional areas, and power scenarios and should be able to demonstrate the viability of connected and autonomous technologies on an operational scale. The primary objective of this research was to survey US commercial facilities associated with autonomous vehicle development, testing, and evaluation.

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Rolufs, Angela, Amelia Trout, Kevin Palmer, Clark Boriack, Bryan Brilhart, and Annette Stumpf. Integration of autonomous electric transport vehicles into a tactical microgrid : final report. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/42007.

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The objective of the Autonomous Transport Innovation (ATI) technical research program is to investigate current gaps and challenges and develop solutions to integrate emerging electric transport vehicles, vehicle autonomy, vehicle-to-grid (V2G) charging and microgrid technologies with military legacy equipment. The ATI research area objectives are to: identify unique military requirements for autonomous transportation technologies; identify currently available technologies that can be adopted for military applications and validate the suitability of these technologies to close need gaps; identify research and operational tests for autonomous transport vehicles; investigate requirements for testing and demonstrating of bidirectional-vehicle charging within a tactical environment; develop requirements for a sensored, living laboratory that will be used to assess the performance of autonomous innovations; and integrate open standards to promote interoperability and broad-platform compatibility. This final report summarizes the team’s research, which resulted in an approach to develop a sensored, living laboratory with operational testing capability to assess the safety, utility, interoperability, and resiliency of autonomous electric transport and V2G technologies in a tactical microgrid. The living laboratory will support research and assessment of emerging technologies and determine the prospect for implementation in defense transport operations and contingency base energy resilience.

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Wang, Shenlong, and David Forsyth. Safely Test Autonomous Vehicles with Augmented Reality. Illinois Center for Transportation, August 2022. http://dx.doi.org/10.36501/0197-9191/22-015.

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This work exploits augmented reality to safely train and validate autonomous vehicles’ performance in the real world under safety-critical scenarios. Toward this goal, we first develop algorithms that create virtual traffic participants with risky behaviors and seamlessly insert the virtual events into real images perceived from the physical world. The resulting composed images are photorealistic and physically grounded. The manipulated images are fed into the autonomous vehicle during testing, allowing the self-driving vehicle to react to such virtual events within either a photorealistic simulator or a real-world test track and real hardware systems. Our presented technique allows us to develop safe, hardware-in-the-loop, and cost-effective tests for self-driving cars to respond to immersive safety-critical traffic scenarios.

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Dunn, Stanley E. The Enhancement of Autonomous Marine Vehicle Testing in the South Florida Testing Facility Range. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada629859.

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Morison, James H. Testing of the Autonomous Microconductivity - Temperature Vehicle and a Direct Technique for the Determination of Turbulent Fluxes With Autonomous Underwater Vehicles. Fort Belvoir, VA: Defense Technical Information Center, June 2003. http://dx.doi.org/10.21236/ada414847.

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Morison, James H. Testing of the Autonomous Microconductivity-Temperature Vehicle and a Direct Technique for the Determination of Turbulent Fluxes with Autonomous Underwater Vehicles. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada629666.

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