Journal articles on the topic 'Automated vehicles – Research'
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1
Shladover, S. E. "Automated vehicles for highway operations (automated highway systems)." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 219, no. 1 (February 1, 2005): 53–75. http://dx.doi.org/10.1243/095440705x9407.
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Considerable research effort has been devoted within the past 15 years to automating the driving of highway vehicles in order to improve their safety and efficiency of operation and to help to reduce traffic congestion. Although the highway environment is in some ways more structured than other environments in which automated vehicles have been proposed to operate, the density and complexity of road traffic still make the sensing and control problems challenging. Because highway vehicles are not ‘unmanned’ but are expected to carry passengers and to coexist with other passenger-carrying vehicles, the reliability and safety considerations in the design of their control systems are much more important than they are for vehicles that are truly unmanned. This paper reviews the progress that has been made in recent research on highway vehicle automation and indicates the important research challenges that still need to be addressed before highway automation can become an everyday reality.
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Peng, Huei. "Connected and Automated Vehicles." Mechanical Engineering 138, no. 12 (December 1, 2016): S5—S11. http://dx.doi.org/10.1115/1.2016-dec-2.
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This article focuses on dynamics and control of connected and automated vehicles. The complexity and difficulty can grow significantly from low automation levels to higher levels. The paper briefly highlights three challenges, i.e., sensing, localization, and perception. The Mobility Transformation Center (MTC) is a public/private research and development partnership led by the University of Michigan. MTC aims to develop the foundations for a viable ecosystem of CAVs. A popular alternative to test high-automation-level AVs is the Naturalistic-Field Operational Test (N-FOT). In an N-FOT, a number of equipped vehicles are tested under naturalistic driving conditions over an extended period. In the near future, connected and automated vehicle technologies are expected to be deployed rapidly. While there has been a lot of research in, and attention to, the field of sensing, localization, and perception, this paper aims to point out a few areas related to the field of dynamics and control that are opportunities for further research.
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Mirnig, Alexander G., Sandra Trösterer, Alexander Meschtscherjakov, Magdalena Gärtner, and Manfred Tscheligi. "Trust in Automated Vehicles." i-com 17, no. 1 (April 25, 2018): 79–90. http://dx.doi.org/10.1515/icom-2017-0031.
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Abstract Increasing degrees of automation in on-road vehicles bear great potential for heightened driver safety and traffic efficiency in both the near and far future. The more the driver delegates control to the vehicle, the more salient the issue of trust in automated technology becomes. Misaligned trust can lead to mishandling of automation controls in individual instances and decreases the general acceptance of on-road automation on a broader scale. In this paper, we apply insights from trust research for dynamic web service interaction to the novel automated driving domain, in order to scope the problem space regarding trust in automated vehicles. We conclude that the appropriate communication of trustworthiness, the necessity to calibrate trust, the importance of intervention capabilities by the driver, and the unambiguous transparency of locus of control are all important aspects when in comes to understanding trust in automated vehicles.
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Zhang, Yong, Lei Shi, Jing Chen, and Xuefeng Li. "Analysis of an Automated Vehicle Routing Problem in Logistics considering Path Interruption." Journal of Advanced Transportation 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/1624328.
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The application of automated vehicles in logistics can efficiently reduce the cost of logistics and reduce the potential risks in the last mile. Considering the path restriction in the initial stage of the application of automated vehicles in logistics, the conventional model for a vehicle routing problem (VRP) is modified. Thus, the automated vehicle routing problem with time windows (AVRPTW) model considering path interruption is established. Additionally, an improved particle swarm optimisation (PSO) algorithm is designed to solve this problem. Finally, a case study is undertaken to test the validity of the model and the algorithm. Four automated vehicles are designated to execute all delivery tasks required by 25 stores. Capacities of all of the automated vehicles are almost fully utilised. It is of considerable significance for the promotion of automated vehicles in last-mile situations to develop such research into real problems arising in the initial period.
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Noei, Shirin, Mohammadreza Parvizimosaed, and Mohammadreza Noei. "Longitudinal Control for Connected and Automated Vehicles in Contested Environments." Electronics 10, no. 16 (August 18, 2021): 1994. http://dx.doi.org/10.3390/electronics10161994.
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The Society of Automotive Engineers (SAE) defines six levels of driving automation, ranging from Level 0 to Level 5. Automated driving systems perform entire dynamic driving tasks for Levels 3–5 automated vehicles. Delegating dynamic driving tasks from driver to automated driving systems can eliminate crashes attributed to driver errors. Sharing status, sharing intent, seeking agreement, or sharing prescriptive information between road users and vehicles dedicated to automated driving systems can further enhance dynamic driving task performance, safety, and traffic operations. Extensive simulation is required to reduce operating costs and achieve an acceptable risk level before testing cooperative automated driving systems in laboratory environments, test tracks, or public roads. Cooperative automated driving systems can be simulated using a vehicle dynamics simulation tool (e.g., CarMaker and CarSim) or a traffic microsimulation tool (e.g., Vissim and Aimsun). Vehicle dynamics simulation tools are mainly used for verification and validation purposes on a small scale, while traffic microsimulation tools are mainly used for verification purposes on a large scale. Vehicle dynamics simulation tools can simulate longitudinal, lateral, and vertical dynamics for only a few vehicles in each scenario (e.g., up to ten vehicles in CarMaker and up to twenty vehicles in CarSim). Conventional traffic microsimulation tools can simulate vehicle-following, lane-changing, and gap-acceptance behaviors for many vehicles in each scenario without simulating vehicle powertrain. Vehicle dynamics simulation tools are more compute-intensive but more accurate than traffic microsimulation tools. Due to software architecture or computing power limitations, simplifying assumptions underlying convectional traffic microsimulation tools may have been a necessary compromise long ago. There is, therefore, a need for a simulation tool to optimize computational complexity and accuracy to simulate many vehicles in each scenario with reasonable accuracy. This research proposes a traffic microsimulation tool that employs a simplified vehicle powertrain model and a model-based fault detection method to simulate many vehicles with reasonable accuracy at each simulation time step under noise and unknown inputs. Our traffic microsimulation tool considers driver characteristics, vehicle model, grade, pavement conditions, operating mode, vehicle-to-vehicle communication vulnerabilities, and traffic conditions to estimate longitudinal control variables with reasonable accuracy at each simulation time step for many conventional vehicles, vehicles dedicated to automated driving systems, and vehicles equipped with cooperative automated driving systems. Proposed vehicle-following model and longitudinal control functions are verified for fourteen vehicle models, operating in manual, automated, and cooperative automated modes over two driving schedules under three malicious fault magnitudes on transmitted accelerations.
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Yan, Jin, Feng Lin, Zhen Zhou Ye, and Jian Wen Shao. "The Design of Automated Parking Brake Performance Test Equipment." Advanced Materials Research 945-949 (June 2014): 2551–54. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.2551.
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In order to test the parking brake performance of in-use vehicle, in this research, we designed a set of automated test system which could calculate the parking brake performance. The automated test system which was composed of four parts: vehicles weighing device, automatic traction gear, force cell, and intelligent control unit would calculate the braking force based on the traction force and the total mass of the vehicle. The results indicate that this test equipment is found to be convenient application, small floor coverage and reliable.
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Zou, Yunfei, Jie Wen, Siyuan Tang, Hongmao Zhou, Panpan Zhang, and Weiting Ning. "Research on the application of autonomous driving technology in port." Highlights in Science, Engineering and Technology 9 (September 30, 2022): 14–18. http://dx.doi.org/10.54097/hset.v9i.1709.
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Automatic driving technology is one of the most popular emerging technologies at present. It has been preliminarily applied in the field of transportation, especially in the automatic container terminal of the port. Automated guided vehicles for freight container(AGV), intelligent container truck(ICT) and intelligent guided vehicle for container(IGV) applying automatic driving technology in the port are briefly introduced. ICT and IGV are especially suitable for the automation transformation of traditional container terminals, and have gradually become the main force of horizontal transportation equipment in automatic container terminals. The main problems existing in the port application of automatic driving technology are emphatically analyzed, and the key research direction is put forward.
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Cauffman, Stephen J., Mei Lau, Yulin Deng, Christopher Cunningham, David B. Kaber, and Jing Feng. "Research and Design Considerations for Presentation of Non-Safety Related Information via In-Vehicle Displays during Automated Driving." Applied Sciences 12, no. 20 (October 19, 2022): 10538. http://dx.doi.org/10.3390/app122010538.
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As automated vehicles become more prevalent on roadways, it is necessary to study driver behaviors in interacting with such systems. With higher levels of vehicle automation, drivers may become less engaged with the roadway environment. As a result, how to effectively bring non-safety related information (e.g., guide and service sign content) to a driver’s attention is an open research question. In this review, we summarize current literature on three domains of research, including: (1) the design and effectiveness of traditional road signage, (2) human factors considerations in vehicle automation design, and (3) current design guidelines for in-vehicle information presentation. Based on the review, including empirical studies, we identify knowledge relevant to communicating road signage information in automated vehicles. We propose a framework highlighting various factors that could determine the effectiveness of in-vehicle messaging. The framework is intended to motivate future research on development of in-vehicle interfaces for highly automated driving.
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Morozov, E. V. "Methodology and algorithms for buildinga telematic automated vehicle movement control system." Вестник гражданских инженеров 17, no. 6 (2020): 206–13. http://dx.doi.org/10.23968/1999-5571-2020-17-6-206-213.
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The article proposes promising trends of research in the field of building automated systems for controlling the movement of transport vehicles (TS) in order to ensure a continuous monitoring and operational control. A method for substantiating technical requirements and assessing the characteristics of measuring instruments for automated control of vehicle movement, an algorithm for determining the optimal values of characteristics of measuring tools and an algorithm for choosing the optimal version of telematic automatic control devices (TASK) for vehicle movement have been developed. The concept of a telematic automated control system for controlling the movement of vehicles (TASU CD TS) is formulated. The presented results make it possible to build the TASU CD of the vehicle based on the optimal choice of TASK movement and the assessment of the effectiveness of their application. Creation of a local telematic automated control system for controlling the movement of the vehicle will effectively manage traffic flows through the implementation of continuous control and monitoring of the vehicle along the entire route of movement, and operational coordination of the interactions of all road users, special services and departments.
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Zhao, Qianru, Shouwen Ji, Dong Guo, Xuemin Du, and Hongxuan Wang. "Research on Cooperative Scheduling of Automated Quayside Cranes and Automatic Guided Vehicles in Automated Container Terminal." Mathematical Problems in Engineering 2019 (November 3, 2019): 1–15. http://dx.doi.org/10.1155/2019/6574582.
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According to previous research studies, automated quayside cranes (AQCs) and automated guided vehicles (AGVs) in automated container terminals have a high potential synergy. In this paper, a collaborative scheduling model for AQCs and AGVs is established and the capacity limitation of the transfer platform on AQCs is considered in the model. The minimum total energy consumption of automated quayside cranes (AQCs) and Automatic Guided Vehicles (AGVs) is taken as the objective function. A two-stage taboo search algorithm is adopted to solve the problem of collaborative scheduling optimization. This algorithm integrates AQC scheduling and AGV scheduling. The optimal solution to the model is obtained by feedback from the two-stage taboo search process. Finally, the Qingdao Port is taken as an example of a data experiment. Ten small size test cases are solved to evaluate the performance of the proposed optimization methods. The results show the applicability of the two-stage taboo search algorithm since it can find near-optimal solutions, precisely and accurately.
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Nuñez Velasco, Juan Pablo, Anouk de Vries, Haneen Farah, Bart van Arem, and Marjan P. Hagenzieker. "Cyclists’ Crossing Intentions When Interacting with Automated Vehicles: A Virtual Reality Study." Information 12, no. 1 (December 24, 2020): 7. http://dx.doi.org/10.3390/info12010007.
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Most of cyclists’ fatalities originate from collisions with motorized vehicles. It is expected that automated vehicles (AV) will be safer than human-driven vehicles, but this depends on the nature of interactions between non-automated road users, among them cyclists. Little research on the interactions between cyclists and AVs exists. This study aims to determine the main factors influencing cyclists’ crossing intentions when interacting with an automated vehicle as compared to a conventional vehicle (CV) using a 360° video-based virtual reality (VR) method. The considered factors in this study included vehicle type, gap size between cyclist and vehicle, vehicle speed, and right of way. Each factor had two levels. In addition, cyclist’s self-reported behavior and trust in automated vehicles were also measured. Forty-seven participants experienced 16 different crossing scenarios in a repeated measures study using VR. These scenarios are the result of combinations of the studied factors at different levels. In total, the experiment lasted 60 min. The results show that the gap size and the right of way were the primary factors affecting the crossing intentions of the individuals. The vehicle type and vehicle speed did not have a significant effect on the crossing intentions. Finally, the 360° video-based VR method scored relatively high as a research method and comparable with the results of a previous study investigating pedestrians’ crossing intentions confirming its suitability as a research methodology to study cyclists’ crossing intentions.
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Darimireddy, Naresh K., U. Mohan Rao, Chan-Wang Park, I. Fofana, M. Sujatha, and Anant K. Verma. "Perspectives of Convertors and Communication Aspects in Automated Vehicles, Part 2: Printed Antennas and Sensors for Automotive Radars." Energies 14, no. 6 (March 17, 2021): 1656. http://dx.doi.org/10.3390/en14061656.
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Automated vehicles are becoming popular across the communities of e-transportation across the globe. Hybrid electric vehicles and autonomous vehicles have been subjected to critical research for decades. The research outcomes pertinent to this topic in the literature have been motivated by the industry and researchers to emphasize automated vehicles. Part 1 of this survey addressed the critical aspects that concern the bidirectional converter topologies and condition monitoring activities. In the present part, 24- and 77-GHz low-profile printed antennas are studied for automotive radar applications. These antennas are mounted on automated vehicles to avoid collision and are used for radio tracking applications. The present paper states the types of antenna structures, feed mechanisms, dielectric material requirements, design techniques, performance parameters, and challenges at 24- and 77-GHz resonating frequency applications. The recent developments in feed methodologies, beam scanning concepts, and the effect of sidelobe levels are addressed. Furthermore, the reasons behind the transition from 24 to 77 GHz are reported in detail. The recent advances in the application of various sensor schemes in an automated vehicle have also been discussed.
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Pappas, Georgios, Joshua E. Siegel, Eva Kassens-Noor, Jacob Rutkowski, Konstantinos Politopoulos, and Antonis A. Zorpas. "Game-Based Simulation and Study of Pedestrian-Automated Vehicle Interactions." Automation 3, no. 3 (June 29, 2022): 315–36. http://dx.doi.org/10.3390/automation3030017.
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We identify the need for enhanced pedestrian–vehicle simulation tools and build such a tool to explore the interaction among pedestrian “players” and virtual human- and automated-vehicles for different scenarios taking place in an urban environment. We first present contemporary research tools and then propose the design and development of a new desktop application that facilitates pedestrian-point-of-view research. We then conduct a three-step user experience experiment, in which a small number of participants answer questions before and after using the application to interact with virtual human and automated vehicles in diverse road-crossing scenarios. Behavioral results observed in virtuality, especially when motivated by consequence, tend to simulate real life sufficiently well to inform design choices. From the simulation, we observed valuable insights into human–vehicle interactions. Upon completing this preliminary testing, we iterated the tool’s design and ultimately conducted an 89-participant study of human–vehicle interactions for three scenarios taking place in a virtual environment. Our tool raised participant awareness of autonomous vehicles and their capabilities and limitations, which is an important step in overcoming public distrust of AVs. We additionally saw that participants trust humans and technology less as drivers than in other contexts, and that pedestrians feel safer around vehicles with autonomy indicators. Further, we note that study participants increasingly feel safe with automated vehicles with increased exposure. These preliminary results, as well as the efficacy of the tool’s design, may inform future socio-technical design for automated vehicles and their human interactions.
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Stopka, Ondrej. "Modeling the Delivery Routes Carried out by Automated Guided Vehicles when Using the Specific Mathematical Optimization Method." Open Engineering 10, no. 1 (March 10, 2020): 166–74. http://dx.doi.org/10.1515/eng-2020-0027.
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AbstractDistribution tasks or transportation problems when using Operations Research methods are mostly addressed by vehicle routing problem methods dealing with an issue of supplying to several nodes, wherein the route begins in a point of origin and, after accomplishing deliveries to individual nodes, vehicle returns to an initial point. Each node can be operated only once, the order of nodes is not determined; however, the major objective is to find the shortest route possible. The aim of this research study is to formulate options to model delivery routes executed by automated guided vehicles in an extensive logistics areal by applying the specific mathematical optimization method. After description of several fundamental aspects and attributes related to automated guided vehicles, distribution tasks and vehicle routing problems which are discussed in introductory chapters, the most important parts containing the specification of Greedy algorithm, as a very useful optimization method for the given purpose, as well as the very models of cargo delivery by automated guided vehicles without / with initial distance optimization are presented.
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Orosz, Gábor, Jin I. Ge, Chaozhe R. He, Sergei S. Avedisov, Wubing B. Qin, and Linjun Zhang. "Seeing Beyond the Line of Site – Controlling Connected Automated Vehicles." Mechanical Engineering 139, no. 12 (December 1, 2017): S8—S12. http://dx.doi.org/10.1115/1.2017-dec-8.
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This article discusses past, present, and future research on connected automated vehicles and their impact on road transportation. From the 1980s, microcontrollers started to penetrate production vehicles through various subsystems such as engine control units, and anti-lock braking systems. Soon the need for different microcontrollers to communicate with each other led to the invention of the controller area network bus. In the 1990s, onboard sensors were introduced to monitor the environment and the motion of neighboring vehicles. These sensors, combined with more powerful computers, allowed vehicles to perform lateral and longitudinal control such as lane keeping and car following. Starting from the mid-2000s, wireless communication technologies such as WiFi and 4G/LTE have been adopted in order to facilitate vehicle-to-vehicle and vehicle-to-infrastructure communication. These are often referred to as vehicle-to-everything (V2X) communication, where X also includes pedestrians, bicyclists, etc. In particular, in the United States, dedicated short-range communication has been standardized based on IEEE 802.11p protocol, which allows low-latency, ad-hoc, and peer-to-peer communication with 10-Hz update frequency.
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van der Heijden, Matthieu, Mark Ebben, Noud Gademann, and Aart van Harten. "Scheduling vehicles in automated transportation systems." OR Spectrum 24, no. 1 (February 1, 2002): 31–58. http://dx.doi.org/10.1007/s291-002-8199-x.
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He, Dengbo, Dina Kanaan, and Birsen Donmez. "A Taxonomy of Strategies For Supporting Time-Sharing With Non-Driving Tasks in Automated Driving." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (November 2019): 2088–92. http://dx.doi.org/10.1177/1071181319631283.
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Driver distraction is one of the leading causes of vehicle crashes. The introduction of higher levels of vehicle control automation is expected to alleviate the negative effects of distraction by delegating the driving task to automation, thus enabling drivers to engage in non-driving-related tasks more safely. However, before fully automated vehicles are realized, drivers are still expected to play a supervisory role and intervene with the driving task if necessary while potentially having more spare capacity for engaging in non-driving-related tasks. Traditional distraction mitigation perspectives need to be shifted for automated vehicles from mainly preventing the occurrence of non-driving-related tasks to dynamically coordinating time-sharing between driving and non-driving-related tasks. In this paper, we provide a revised and expanded taxonomy of driver distraction mitigation strategies, discuss how the different strategies can be used in an automated driving context, and propose directions for future research in supporting time-sharing in automated vehicles.
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Kim, Kap Hwan, Su Min Jeon, and Kwang Ryel Ryu. "Deadlock prevention for automated guided vehicles in automated container terminals." OR Spectrum 28, no. 4 (June 3, 2006): 659–79. http://dx.doi.org/10.1007/s00291-006-0055-2.
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Lee, Wooseop, Min-Hee Kang, Jaein Song, and Keeyeon Hwang. "The Design of Preventive Automated Driving Systems Based on Convolutional Neural Network." Electronics 10, no. 14 (July 19, 2021): 1737. http://dx.doi.org/10.3390/electronics10141737.
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As automated vehicles have been considered one of the important trends in intelligent transportation systems, various research is being conducted to enhance their safety. In particular, the importance of technologies for the design of preventive automated driving systems, such as detection of surrounding objects and estimation of distance between vehicles. Object detection is mainly performed through cameras and LiDAR, but due to the cost and limits of LiDAR’s recognition distance, the need to improve Camera recognition technique, which is relatively convenient for commercialization, is increasing. This study learned convolutional neural network (CNN)-based faster regions with CNN (Faster R-CNN) and You Only Look Once (YOLO) V2 to improve the recognition techniques of vehicle-mounted monocular cameras for the design of preventive automated driving systems, recognizing surrounding vehicles in black box highway driving videos and estimating distances from surrounding vehicles through more suitable models for automated driving systems. Moreover, we learned the PASCAL visual object classes (VOC) dataset for model comparison. Faster R-CNN showed similar accuracy, with a mean average precision (mAP) of 76.4 to YOLO with a mAP of 78.6, but with a Frame Per Second (FPS) of 5, showing slower processing speed than YOLO V2 with an FPS of 40, and a Faster R-CNN, which we had difficulty detecting. As a result, YOLO V2, which shows better performance in accuracy and processing speed, was determined to be a more suitable model for automated driving systems, further progressing in estimating the distance between vehicles. For distance estimation, we conducted coordinate value conversion through camera calibration and perspective transform, set the threshold to 0.7, and performed object detection and distance estimation, showing more than 80% accuracy for near-distance vehicles. Through this study, it is believed that it will be able to help prevent accidents in automated vehicles, and it is expected that additional research will provide various accident prevention alternatives such as calculating and securing appropriate safety distances, depending on the vehicle types.
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Jiang, Haobin, Jie Zhou, Aoxue Li, Xinchen Zhou, and Shidian Ma. "Human-like trapezoidal steering angle model on two-lane urban curves." International Journal of Advanced Robotic Systems 16, no. 4 (July 2019): 172988141986761. http://dx.doi.org/10.1177/1729881419867614.
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With the rapid development of automated vehicles, there is currently a significant amount of automated driving research. Giving automated vehicles capabilities similar to those of experienced drivers will allow them to share the road harmoniously with manned vehicles, especially on two-lane urban curves. To represent the steering behavior of experienced drivers, a series of curve feature distances are proposed, which is determined by multi-regression. These series of curve feature distances are used to generate a trapezoidal steering angle model which imitates the steering behavior of the experienced test drivers. To verify the feasibility and human-likeness of the proposed trapezoidal steering angle model, the model is used with constant vehicle speed to plan a human-like trajectory which is tracked using model predictive control. The simulation results show that the proposed trapezoidal steering angle model is human-like and could be used to give automated vehicles human-like driving capability when driving on two-lane curves.
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ENDACHEV, Denis V., Sergey V. BAKHMUTOV, Vladimir V. EVGRAFOV, and Nikolay P. MEZENTCEV. "ELECTRONIC SYSTEMS OF INTELLIGENT VEHICLES." Mechanics of Machines, Mechanisms and Materials 4, no. 53 (December 2020): 5–10. http://dx.doi.org/10.46864/1995-0470-2020-4-53-5-10.
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Modern automotive engineering is closely related to the implementation of information systems. In automobile transport, the range of such developments is considerably wide: from driver assistance systems (ADAS — Advanced Driver Assistance System) to full autopilot systems. The article provides a brief overview of the state of the problem and presents the main directions of development of the State Research Center of the Russian Federation FSUE “NAMI” in the field of ADAS and highly automated (unmanned) vehicles. Descriptions of on-board vehicle systems of a high level of automation are given developed by the State Research Center of the Russian Federation FSUE “NAMI” with the participation of manufacturers. The article also describes the key technologies of machine vision systems, test sites for highly automated vehicles.
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He, Dengbo, and Birsen Donmez. "Influence of Driving Experience on Distraction Engagement in Automated Vehicles." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 9 (May 4, 2019): 142–51. http://dx.doi.org/10.1177/0361198119843476.
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State-of-the-art vehicle automation requires drivers to visually monitor the driving environment and the automation (through interfaces and vehicle’s actions) and intervene when necessary. However, as evidenced by recent automated vehicle crashes and laboratory studies, drivers are not always able to step in when the automation fails. Research points to the increase in distraction or secondary-task engagement in the presence of automation as a potential reason. However, previous research on secondary-task engagement in automated vehicles mainly focused on experienced drivers. This issue may be amplified for novice drivers with less driving skill. In this paper, we compared secondary-task engagement behaviors of novice and experienced drivers both in manual (non-automated) and automated driving settings in a driving simulator. A self-paced visual-manual secondary task presented on an in-vehicle display was utilized. Phase 1 of the study included 32 drivers (16 novice) who drove the simulator manually. In Phase 2, another set of 32 drivers (16 novice) drove with SAE-level-2 automation. In manual driving, there were no differences between novice and experienced drivers’ rate of manual interactions with the secondary task (i.e., taps on the display). However, with automation, novice drivers had a higher manual interaction rate with the task than experienced drivers. Further, experienced drivers had shorter average glance durations toward the task than novice drivers in general, but the difference was larger with automation compared with manual driving. It appears that with automation, experienced drivers are more conservative in their secondary-task engagement behaviors compared with novice drivers.
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Eichberger, Arno, Gerald Markovic, Zoltan Magosi, Branko Rogic, Cornelia Lex, and Sajjad Samiee. "A Car2X sensor model for virtual development of automated driving." International Journal of Advanced Robotic Systems 14, no. 5 (September 1, 2017): 172988141772562. http://dx.doi.org/10.1177/1729881417725625.
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Automated driving requires a reliable digital representation of the environment, which is achieved by various vehicle sensors. Wireless devices for communication between vehicles and infrastructure (Car2X communication) provide additional data beyond the vehicle’s sensor range. In order to reduce the amount of on-road testing, there has been an increased use of numerical simulation in the development of automated driving functions, which demands accurate simulation models for the sensors involved. The present research deals with the development of Car2X sensor models for conceptual, automated driving investigations based on relatively simple yet computationally efficient mathematical models featuring parameters derived from on-road hardware testing. For analysis purposes, variations in range and reliability in different driving situations were measured and depicted in Google Earth. For the sensor model, a combination of geometric and stochastic models was chosen. The modeling is based on a link budget calculation that considers system and path losses, where wave propagation is described using Nakagami probability density functions. For intersections, an additional term is added to account for the path loss with geometric parameters of the intersection. After model parametrization, an evaluation was conducted. In addition, as a sample case, Car2X was added to an adaptive cruise control, and the improved functionality was demonstrated using vehicle dynamics simulation. This extended adaptive cruise control used information from the indicator of surrounding vehicles to react faster to lane changes by these vehicles.
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Saykin, A. M., and S. E. Buznikov. "Principles of building competitive motion control systems for highly automated vehicles." Journal of Physics: Conference Series 2061, no. 1 (October 1, 2021): 012133. http://dx.doi.org/10.1088/1742-6596/2061/1/012133.
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Abstract The relevance of the issue of development of efficient motion control systems for highly automated vehicles capable to successfully compete with foreign systems of similar purpose is defined by importance of the issue of creation of competitive high-tech products under modern market economy conditions. The research objective was to scientifically justify the building principles for motion control systems for highly automated vehicles providing directed search for solution options for the issue of multi-criterion optimization in the software and hardware space. The research involved methods of system analysis and modern control theory. The research result is a set or complex of building principles for motion control systems for highly automated vehicles providing minimization of hardware environment while keeping observability of all vehicle state coordinates significant for safe control and their dynamic boundaries, as well as ensuring controllability via the channels of traction, braking and direction. The conceptual core or base of such integrated intelligent control systems is mathematical and programming support (software) of indirect measurements of the parameters of motion and control of traction, brakes and direction adapting to the vehicle state and environment changes.
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Do, Wooseok, Omid M. Rouhani, and Luis Miranda-Moreno. "Simulation-Based Connected and Automated Vehicle Models on Highway Sections: A Literature Review." Journal of Advanced Transportation 2019 (June 26, 2019): 1–14. http://dx.doi.org/10.1155/2019/9343705.
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This study provides a literature review of the simulation-based connected and automated intelligent-vehicle studies. Media and car-manufacturing companies predict that connected and automated vehicles (CAVs) would be available in the near future. However, society and transportation systems might not be completely ready for their implementation in various aspects, e.g., public acceptance, technology, infrastructure, and/or policy. Since the empirical field data for CAVs are not available at present, many researchers develop micro or macro simulation models to evaluate the CAV impacts. This study classifies the most commonly used intelligent-vehicle types into four categories (i.e., adaptive cruise control, ACC; cooperative adaptive cruise control, CACC; automated vehicle, AV; CAV) and summarizes the intelligent-vehicle car-following models (i.e., Intelligent Driver Model, IDM; MICroscopic Model for Simulation of Intelligent Cruise Control, MIXIC). The review results offer new insights for future intelligent-vehicle analyses: (i) the increase in the market-penetration rate of intelligent vehicles has a significant impact on traffic flow conditions; (ii) without vehicle connections, such as the ACC vehicles, the roadway-capacity increase would be marginal; (iii) none of the parameters in the AV or CAV models is calibrated by the actual field data; (iv) both longitudinal and lateral movements of intelligent vehicles can reduce energy consumption and environmental costs compared to human-driven vehicles; (v) research gap exists in studying the car-following models for newly developed intelligent vehicles; and (vi) the estimated impacts are not converted into a unified metric (i.e., welfare economic impact on users or society) which is essential to evaluate intelligent vehicles from an overall societal perspective.
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Luo, Yugong, Gang Yang, Mingchang Xu, Zhaobo Qin, and Keqiang Li. "Cooperative Lane-Change Maneuver for Multiple Automated Vehicles on a Highway." Automotive Innovation 2, no. 3 (September 2019): 157–68. http://dx.doi.org/10.1007/s42154-019-00073-1.
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Abstract With the development of vehicle-to-vehicle (V2V) communication, it is possible to share information among multiple vehicles. However, the existing research on automated lane changes concentrates only on the single-vehicle lane change with self-detective information. Cooperative lane changes are still a new area with more complicated scenarios and can improve safety and lane-change efficiency. Therefore, a multi-vehicle cooperative automated lane-change maneuver based on V2V communication for scenarios of eight vehicles on three lanes was proposed. In these scenarios, same-direction and intersectant-direction cooperative lane changes were defined. The vehicle that made the cooperative decision obtained the information of surrounding vehicles that were used to cooperatively plan the trajectories, which was called cooperative trajectory planning. The cooperative safety spacing model was proposed to guarantee and improve the safety of all vehicles, and it essentially developed constraints for the trajectory-planning task. Trajectory planning was treated as an optimization problem with the objective of maximizing safety, comfort, and lane-change efficiency under the constraints of vehicle dynamics and the aforementioned safety spacing model. Trajectory tracking based on a model predictive control method was designed to minimize tracking errors and control increments. Finally, to verify the validity of the proposed maneuver, an integrated simulation platform combining MATLAB/Simulink with CarSim was established. Moreover, a hardware-in-the-loop test bench was performed for further verification. The results indicated that the proposed multi-vehicle cooperative automated lane-change maneuver can achieve lane changes of multiple vehicles and increase lane-change efficiency while guaranteeing safety and comfort.
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Raju, Narayana, Pallav Kumar, Aayush Jain, Shriniwas S. Arkatkar, and Gaurang Joshi. "Application of Trajectory Data for Investigating Vehicle Behavior in Mixed Traffic Environment." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 43 (July 31, 2018): 122–33. http://dx.doi.org/10.1177/0361198118787364.
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The research work reported here investigates driving behavior under mixed traffic conditions on high-speed, multilane highways. With the involvement of multiple vehicle classes, high-resolution trajectory data is necessary for exploring vehicle-following, lateral movement, and seeping behavior under varying traffic flow states. An access-controlled, mid-block road section was selected for video data collection under varying traffic flow conditions. Using a semi-automated image processing tool, vehicular trajectory data was developed for three different traffic states. Micro-level behavior such as lateral placement of vehicles as a function of speed, instant responses, vehicle-following behavior, and hysteresis phenomenon were evaluated under different traffic flow states. It was found that lane-wise behavior degraded with increase in traffic volume and vehicles showed a propensity to move towards the median at low flow and towards the curb-side at moderate and heavy flows. Further, vehicle-following behavior was also investigated and it was found that with increase in flow level, vehicles are more inclined to mimic the leader vehicle’s behavior. In addition to following time, perceiving time of subject vehicle for different leading vehicles was also evaluated for different vehicle classes. From the analysis, it was inferred that smaller vehicles are switching their leader vehicles more often to escape from delay, resulting in less following and perceiving time and aggressive gap acceptance. The present research work reveals the need for high-quality, micro-level data for calibrating driving behavior models under mixed traffic conditions.
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Li, Shuo, Yanghanzi Zhang, Simon Edwards, and Philip T. Blythe. "Exploration into the Needs and Requirements of the Remote Driver When Teleoperating the 5G-Enabled Level 4 Automated Vehicle in the Real World—A Case Study of 5G Connected and Automated Logistics." Sensors 23, no. 2 (January 10, 2023): 820. http://dx.doi.org/10.3390/s23020820.
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Connected and automated vehicles have the potential to deliver significant environmental, safety, economic and social benefits. The key advancement for automated vehicles with higher levels of automation (SAE Level 4 and over) is fail-operational. One possible solution for the failsafe mode of automated vehicles is a 5G-enabled teleoperation system controlled by remote drivers. However, knowledge is missing regarding understanding of the human–machine interaction in teleoperation from the perspective of remote drivers. To address this research gap, this study qualitatively investigated the acceptance, attitudes, needs and requirements of remote drivers when teleoperating a 5G-enabled Level 4 automated vehicle (5G L4 AV) in the real world. The results showed that remote drivers are positive towards the 5G L4 AV. They would like to constantly monitor the driving when they are not controlling the vehicle remotely. Improving their field of vision for driving and enhancing the perception of physical motion feedback are the two key supports required by remote drivers in 5G L4 AVs. The knowledge gained in this study provides new insights into facilitating the design and development of safe, effective and user-friendly teleoperation systems in vehicle automation.
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Wei Sheng, Goh, Wan Isni Sofiah Wan Din, Quadri Waseem, and Azlee Zabidi. "Investigation and Analysis of Crack Detection using UAV and CNN: A Case Study of Hospital Raja Permaisuri Bainun." International Journal of Software Engineering and Computer Systems 9, no. 1 (January 31, 2023): 10–26. http://dx.doi.org/10.15282/ijsecs.9.1.2023.2.0106.
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Crack detection in old buildings has been shown to be inefficient, with many technical challenges such as physical inspection and difficult measurements. It is important to have an automatic, fast visual inspection of these building components to detect cracks by evaluating their conditions (impact) and the level of their risk. Unmanned Aerial Vehicles (UAV) can automate, avoid visual inspection, and avoid other physical check-ups of these buildings. Automated crack detection using Machine Learning Algorithms (MLA), especially a Conventional Neural Network (CNN), along with an Unmanned Aerial Vehicle (UAV), can be effective and both can efficiently work together to detect the cracks in buildings using image processing techniques. The purpose of this research project is to evaluate currently available crack detection systems and to develop an automated crack detection system using Aggregate Channel Features (ACF)that can be used with unmanned aerial vehicles (UAV). Therefore, we conducted a real-world experiment of crack detection at Hospital Raja Permaisuri Bainun using DJI Mavic Air (Drone Hardware) and DJI GO 4(Drone Software) using CNN through MATLAB software with CNN-SVM method with the accuracy rate of3.0 percent increased from 82.94%to 85.94%. in comparison with other ML algorithms like CNN Random Forest (RF), Support Vector Machine (SVM) and Artificial Neural Network (ANN).
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Calvert, S. C., W. J. Schakel, and J. W. C. van Lint. "Will Automated Vehicles Negatively Impact Traffic Flow?" Journal of Advanced Transportation 2017 (2017): 1–17. http://dx.doi.org/10.1155/2017/3082781.
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With low-level vehicle automation already available, there is a necessity to estimate its effects on traffic flow, especially if these could be negative. A long gradual transition will occur from manual driving to automated driving, in which many yet unknown traffic flow dynamics will be present. These effects have the potential to increasingly aid or cripple current road networks. In this contribution, we investigate these effects using an empirically calibrated and validated simulation experiment, backed up with findings from literature. We found that low-level automated vehicles in mixed traffic will initially have a small negative effect on traffic flow and road capacities. The experiment further showed that any improvement in traffic flow will only be seen at penetration rates above 70%. Also, the capacity drop appeared to be slightly higher with the presence of low-level automated vehicles. The experiment further investigated the effect of bottleneck severity and truck shares on traffic flow. Improvements to current traffic models are recommended and should include a greater detail and understanding of driver-vehicle interaction, both in conventional and in mixed traffic flow. Further research into behavioural shifts in driving is also recommended due to limited data and knowledge of these dynamics.
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Rauniyar, Ashish, Desta Haileselassie Hagos, and Manish Shrestha. "A Crowd-Based Intelligence Approach for Measurable Security, Privacy, and Dependability in Internet of Automated Vehicles with Vehicular Fog." Mobile Information Systems 2018 (2018): 1–14. http://dx.doi.org/10.1155/2018/7905960.
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With the advent of Internet of things (IoT) and cloud computing technologies, we are in the era of automation, device-to-device (D2D) and machine-to-machine (M2M) communications. Automated vehicles have recently gained a huge attention worldwide, and it has created a new wave of revolution in automobile industries. However, in order to fully establish automated vehicles and their connectivity to the surroundings, security, privacy, and dependability always remain a crucial issue. One cannot deny the fact that such automatic vehicles are highly vulnerable to different kinds of security attacks. Also, today’s such systems are built from generic components. Prior analysis of different attack trends and vulnerabilities enables us to deploy security solutions effectively. Moreover, scientific research has shown that a “group” can perform better than individuals in making decisions and predictions. Therefore, this paper deals with the measurable security, privacy, and dependability of automated vehicles through the crowd-based intelligence approach that is inspired from swarm intelligence. We have studied three use case scenarios of automated vehicles and systems with vehicular fog and have analyzed the security, privacy, and dependability metrics of such systems. Our systematic approaches to measuring efficient system configuration, security, privacy, and dependability of automated vehicles are essential for getting the overall picture of the system such as design patterns, best practices for configuration of system, metrics, and measurements.
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Hester, Michelle, Kevin Lee, and Brian P. Dyre. "“Driver Take Over”: A Preliminary Exploration of Driver Trust and Performance in Autonomous Vehicles." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 1969–73. http://dx.doi.org/10.1177/1541931213601971.
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Automated vehicles are becoming more prominent in research and development. These automated vehicles introduce issues that have been seen in other autonomous systems such as decreases in situation awareness, complacency, and trust. Previous literature has looked at the effects of alerts and voice agents on driving performance. This preliminary study compares different in-car alerts (no alert, sound alert, task irrelevant voice alert, and task relevant voice alert) on trust and the driver’s ability to get back in-the-loop when the automation has failed. Participants were asked to monitor a simulated automated vehicle as it drove down a straight two-lane road. The main statistical results of our study show no difference in trust between the four different conditions; however, more participants avoided collision with a leading car in the task relevant voice condition in comparison to the three other conditions. These preliminary findings have important implications for the design of automated vehicles.
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Prochowski, Leon, Patryk Szwajkowski, and Mateusz Ziubiński. "Research Scenarios of Autonomous Vehicles, the Sensors and Measurement Systems Used in Experiments." Sensors 22, no. 17 (August 31, 2022): 6586. http://dx.doi.org/10.3390/s22176586.
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Automated and autonomous vehicles are in an intensive development phase. It is a phase that requires a lot of modelling and experimental research. Experimental research into these vehicles is in its initial state. There is a lack of findings and standardized recommendations for the organization and creation of research scenarios. There are also many difficulties in creating research scenarios. The main difficulties are the large number of systems for simultaneous checking. Additionally, the vehicles have a very complicated structure. A review of current publications allowed for systematization of the research scenarios of vehicles and their components as well as the measurement systems used. These include perception systems, automated response to threats, and critical situations in the area of road safety. The scenarios analyzed ensure that the planned research tasks can be carried out, including the investigation of systems that enable autonomous driving. This study uses passenger cars equipped with highly sophisticated sensor systems and localization devices. Perception systems are the necessary equipment during the conducted study. They provide recognition of the environment, mainly through vision sensors (cameras) and lidars. The research tasks include autonomous driving along a detected road lane on a curvilinear track. The effective maintenance of the vehicle in this lane is assessed. The location used in the study is a set of specialized research tracks on which stationary or moving obstacles are often placed.
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Andrei, Liliana, Oana Luca, and Florian Gaman. "Insights from User Preferences on Automated Vehicles: Influence of Socio-Demographic Factors on Value of Time in Romania Case." Sustainability 14, no. 17 (August 30, 2022): 10828. http://dx.doi.org/10.3390/su141710828.
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New transport technologies, such as autonomous vehicles, are increasingly discussed in the debate on the transition to a sustainable urban future. Automated vehicles (AVs) are expected to reduce the value of travel time (VoT), allowing the use of time for other types of activities during travel, including working, reading, sleeping, entertainment, etc. Our study aims to provide empirical insights on future modal choice preferences for regular trips for Romanian citizens, using a sample of 309 respondents to a web survey on issues related to automated vehicles. Using multinomial logistic models (MNL), we analysed the relationship between three mode choices: regular car, private automated vehicle, and shared automated vehicle, along with the individual and household characteristics. In addition, we calculated the VoT for each mode choice based on the results of MNL analysis. Results showed that VoT is strongly influenced by travel cost and travel time, by socio-economic characteristics such as age, gender, and education, and has the lowest value for the shared AV compared with a regular car or a private AV. Future research may conduct comparable studies in European countries but also explore the opinions and perceptions of vulnerable road users on AVs and VoT.
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Amelichkin, Aleksei Viktorovich. "On the legal problems of operation of highly automated vehicles in road traffic." Административное и муниципальное право, no. 3 (March 2021): 59–73. http://dx.doi.org/10.7256/2454-0595.2021.3.35319.
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The subject of this research is the system of legal relations in area of ensuring road safety in terms of operation of highly automated vehicles on public roads. The object of this research is social relations arising in the context of operation of highly automated vehicles traffic on public roads. The goal of this article consists in examination of the normative legal framework that regulates the peculiarities of operation of highly automated vehicles, as well as in development of recommendations for improving the normative legal framework. The author explores the issues of normative legal regulation of operation of highly automated vehicles on public roads. Special attention is given to the current issues of legal nature. The novelty is defined by the need to improve legal mechanism for the operation of highly automated vehicles on public roads. The author identifies the problems and offers solution on enhancing road safety in terms of operation of highly automated vehicles on public roads for protecting the road users. The conclusion is made on the need to revise the normative legal acts in the area of ensuring road safety for the purpose of achieving a positive result from implementation of highly automated vehicles into road traffic. The acquired results can be used in the legislative activity of government authorities, law enforcement practice, educational process of the educational institutions, scientific research of the experts on ensuring road safety, improvement of the branches of the Russian legal system.
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Stampf, Annika, Mark Colley, and Enrico Rukzio. "Towards Implicit Interaction in Highly Automated Vehicles - A Systematic Literature Review." Proceedings of the ACM on Human-Computer Interaction 6, MHCI (September 19, 2022): 1–21. http://dx.doi.org/10.1145/3546726.
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The inclusion of in-vehicle sensors and increased intention and state recognition capabilities enable implicit in-vehicle interaction. Starting from a systematic literature review (SLR) on implicit in-vehicle interaction, which resulted in 82 publications, we investigated state and intention recognition methods based on (1) their used modalities, (2) their underlying level of automation, and (3) their considered interaction focus. Our SLR revealed a research gap addressing implicit interaction in highly automated vehicles (HAVs). Therefore, we discussed how the requirements for implicit state and intention recognition methods and interaction based on them are changing in HAVs. With this, open questions and opportunities for further research in this area were identified.
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Tomasevic, Nebojsa, Kristie L. Young, Tim Horberry, and Brian Fildes. "A Path towards Sustainable Vehicle Automation: Willingness to Engage in Level 3 Automated Driving." Sustainability 14, no. 8 (April 12, 2022): 4602. http://dx.doi.org/10.3390/su14084602.
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This paper describes a driving simulator study exploring driver willingness to engage in automated driving. The study aimed to explore factors that may influence willingness to engage (WTE) in automated driving and willingness to resume control (WTRC) in Level 3 automated vehicles during everyday driving. Automated driving is an emerging technology that promises a range of benefits. The first step towards sustainable automated driving is the successful introduction of Level 3 automated vehicles. This study investigates key factors that influence the driver’s willingness to engage in automated driving in a Level 3 automated vehicle. A purpose-built driving simulator was used. Forty participants were exposed to driving situations of differing complexity in both manual and automated driving modes, and their willingness to engage or disengage automated driving and perception of safety were recorded. Results demonstrated a strong negative effect of perceived situation complexity on willingness to engage in automated driving. Other significant factors that determine drivers’ willingness to engage in automated driving were trust in automation and driving enjoyment. The identification of perceived situation complexity as a significant factor in drivers’ willingness to engage the automated driving vehicle control mode was the major finding of this research. This finding suggests that it is possible to improve the rate of uptake and sustainability of automated driving with external interventions (technological, regulatory and publicity).
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Chen, Bo, Darrell Robinette, Mahdi Shahbakhti, Kuilin Zhang, Jeff Naber, Jeremy Worm, Christopher Pinnow, and Christopher Morgan. "Connected Vehicles and Powertrain Optimization." Mechanical Engineering 139, no. 09 (September 1, 2017): S12—S18. http://dx.doi.org/10.1115/1.2017-sep-5.
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This article discusses the basic concept of connected and automated vehicles (CAV) technology. The common methods to improve fuel economy are also introduced. The effects of connectivity on vehicle/powertrain control and optimization are also elaborated. The Michigan Tech NEXTCAR project is also presented to provide a more detailed view of predictive vehicle/powertrain control enabled by CAV technologies. The U.S. Department of transportation (DOT) and other federal/state funding agencies have supported research and pilot deployment efforts to develop crosscutting CV technologies and evaluate the effectiveness of CV technologies in real-world transportation systems. The concurrent development of connected and automated vehicle technologies is anticipated to provide synergistic benefits to improve traffic safety, mobility, and energy efficiency. It is observed that increased CAV technologies are being deployed in real-world transportation systems.
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Hashimoto, Naohisa, Yusuke Takinami, and Makoto Yamamoto. "Experimental Study on Different Types of Curves for Ride Comfort in Automated Vehicles." Journal of Advanced Transportation 2021 (October 1, 2021): 1–14. http://dx.doi.org/10.1155/2021/9297218.
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Vehicle automation is among the best possible solutions for traffic issues, including traffic accidents, traffic jams, and energy consumption. However, the user acceptance of automated vehicles is critical and is affected by riding comfort. In addition, human factors in automated vehicle control should be clear. This study evaluates the effect of different courses on driving comfort in automated vehicles using field experiments with 25 subjects. This study focused on lateral motion, but speed control was not targeted. Further, generating a path for obstacle avoidance and lane keeping, which have several constraining conditions, was also not targeted. Rendering a comfortable path is beneficial for developing an acceptable system as a car developer and for building new curves for automated or driving assistance systems from the perspective of construction. The automated vehicle drove at a speed of 30 km/h on four courses, namely, clothoid, two types of spline curves, and arc, based on the real intersection. Each participant sat on both the driver and passenger seat and answered a questionnaire. The experimental data indicated the clothoid course to be the most comfortable, while the arc was most uncomfortable for a significance level of 1%. These tendencies are applicable to driver and passenger seats, all genders, and experiences and will be beneficial for human factor research in automated vehicle control.
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Lee, Geonil, and Jae-il Jung. "Decentralized Platoon Join-in-Middle Protocol Considering Communication Delay for Connected and Automated Vehicle." Sensors 21, no. 21 (October 27, 2021): 7126. http://dx.doi.org/10.3390/s21217126.
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Cooperative driving is an essential component of intelligent transport systems (ITSs). It promises greater safety, reduced accidents, efficient traffic flow, and fuel consumption reduction. Vehicle platooning is a representative service model for ITS. The principal sub-systems of platooning systems for connected and automated vehicles (CAVs) are cooperative adaptive cruise control (CACC) systems and platoon management systems. Based on vehicle state information received through vehicle-to-vehicle (V2V) communication, the CACC system allows platoon vehicles to maintain a narrower safety distance. In addition, the platoon management system using V2V communications allows vehicles to perform platoon maneuvers reliably and accurately. In this paper, we propose a CACC system with a variable time headway and a decentralized platoon join-in-middle maneuver protocol with a trajectory planning system considering the V2V communication delay for CAVs. The platoon join-in-middle maneuver is a challenging research subject as the research must consider the requirement of a more precise management protocol and lateral control for platoon safety and string stability. These CACC systems and protocols are implemented on a simulator for a connected and automated vehicle system, PreScan, and we validated our approach using a realistic control system and V2V communication system provided by PreScan.
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Kettwich, Carmen, Andreas Schrank, and Michael Oehl. "Teleoperation of Highly Automated Vehicles in Public Transport: User-Centered Design of a Human-Machine Interface for Remote-Operation and Its Expert Usability Evaluation." Multimodal Technologies and Interaction 5, no. 5 (May 5, 2021): 26. http://dx.doi.org/10.3390/mti5050026.
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Paving the way to future mobility, teleoperation of vehicles promises a reachable solution to effectively use the benefits of automated driving as long as fully automated vehicles (SAE 5) are not entirely feasible. Safety and reliability are assured by a human operator who remotely observes the vehicle and takes over control in cases of disturbances that exceed the vehicle automation’s skills. In order to integrate the vehicle’s automation and human remote-operation, we developed a novel user-centered human-machine interface (HMI) for teleoperation. It is tailored to the remote-operation of a highly automated shuttle (SAE 4) by a public transport control center and based on a systematic analysis of scenarios, of which detailed requirements were derived. Subsequently, a paper-pencil prototype was generated and refined until a click-dummy emerged. This click-dummy was evaluated by twelve control center professionals. The experts were presented the prototype in regular mode and were then asked to solve three scenarios with disturbances in the system. Using structured interview and questionnaire methodology, the prototype was evaluated regarding its usability, situation awareness, acceptance, and perceived workload. Results support our HMI design for teleoperation of a highly automated shuttle, especially regarding usability, acceptance, and workload. Participant ratings and comments indicated particularly high satisfaction with the interaction design to resolve disturbances and the presentation of camera images. Participants’ feedbacks provide valuable information for a refined HMI design as well as for further research.
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Roy, Debjit, René De Koster, and René Bekker. "Modeling and Design of Container Terminal Operations." Operations Research 68, no. 3 (May 2020): 686–715. http://dx.doi.org/10.1287/opre.2019.1920.
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The design of container terminal operations is complex because multiple factors affect operational performance. These factors include numerous choices for handling technology, terminal topology, and design parameters and stochastic interactions between the quayside, stackside, and vehicle transport processes. In this research, we propose new integrated queuing network models for rapid design evaluation of container terminals with automated lift vehicles and automated guided vehicles. These models offer the flexibility to analyze alternate design variations and develop insights. For instance, the effect of different vehicle dwell point policies and efficient terminal layouts are analyzed. We show the relation among the dwell point–dependent waiting times and also show their asymptotic equivalence at heavy traffic conditions. These models form the building blocks for design and analysis of large-scale terminal operations. We test the model efficacy using detailed simulation experiments and real-terminal validation.
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Boric, Sandra, Edgar Schiebel, Christian Schlögl, Michaela Hildebrandt, Christina Hofer, and Doris M. Macht. "Research in Autonomous Driving – A Historic Bibliometric View of the Research Development in Autonomous Driving." International Journal of Innovation and Economic Development 7, no. 5 (December 2021): 27–44. http://dx.doi.org/10.18775/ijied.1849-7551-7020.2015.74.2003.
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Autonomous driving has become an increasingly relevant issue for policymakers, the industry, service providers, infrastructure companies, and science. This study shows how bibliometrics can be used to identify the major technological aspects of an emerging research field such as autonomous driving. We examine the most influential publications and identify research fronts of scientific activities until 2017 based on a bibliometric literature analysis. Using the science mapping approach, publications in the research field of autonomous driving were retrieved from Web of Science and then structured using the bibliometric software BibTechMon by the AIT (Austrian Institute of Technology). At the time of our analysis, we identified four research fronts in the field of autonomous driving: (I) Autonomous Vehicles and Infrastructure, (II) Driver Assistance Systems, (III) Autonomous Mobile Robots, and (IV) IntraFace, i.e., automated facial image analysis. Researchers were working extensively on technologies that support the navigation and collection of data. Our analysis indicates that research was moving towards autonomous navigation and infrastructure in the urban environment. A noticeable number of publications focused on technologies for environment detection in automated vehicles. Still, research pointed at the technological challenges to make automated driving safe.
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Boric, Sandra, Edgar Schiebel, Christian Schlögl, Michaela Hildebrandt, Christina Hofer, and Doris M. Macht. "Research in Autonomous Driving – A Historic Bibliometric View of the Research Development in Autonomous Driving." International Journal of Innovation and Economic Development 7, no. 5 (December 2021): 27–44. http://dx.doi.org/10.18775/10.18775/ijied.1849-7551-7020.2015.75.2003.
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Autonomous driving has become an increasingly relevant issue for policymakers, the industry, service providers, infrastructure companies, and science. This study shows how bibliometrics can be used to identify the major technological aspects of an emerging research field such as autonomous driving. We examine the most influential publications and identify research fronts of scientific activities until 2017 based on a bibliometric literature analysis. Using the science mapping approach, publications in the research field of autonomous driving were retrieved from Web of Science and then structured using the bibliometric software BibTechMon by the AIT (Austrian Institute of Technology). At the time of our analysis, we identified four research fronts in the field of autonomous driving: (I) Autonomous Vehicles and Infrastructure, (II) Driver Assistance Systems, (III) Autonomous Mobile Robots, and (IV) IntraFace, i.e., automated facial image analysis. Researchers were working extensively on technologies that support the navigation and collection of data. Our analysis indicates that research was moving towards autonomous navigation and infrastructure in the urban environment. A noticeable number of publications focused on technologies for environment detection in automated vehicles. Still, research pointed at the technological challenges to make automated driving safe.
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Ojieabu, Clement E. "Developed Automated Vehicle Traffic Light Controller System for Cities in Nigeria." Journal of Advances in Science and Engineering 1, no. 1 (April 30, 2018): 19–25. http://dx.doi.org/10.37121/jase.v1i1.6.
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This paper presents a research work that was carried out to resolve challenges of traffic light system. This work employs the use of a microcontroller, an inductive loop which acts as the vehicle detector and LED’s (light emitting diodes) for simulating the red, yellow and green light in a traffic light. The inductive loop is embedded in pavement along the road which senses the presence of vehicle. When a vehicle passes across the loop, the magnetic field changes and the inductance of the coil is decreased resulting in a frequency change of the oscillator which is detected by the controller. The interrupt is set to make the traffic light allow the movement of vehicles on the lane with many vehicles on it according to information on the counter. This means that when the system discovers the lane with many vehicles by the number on the counter, the interrupt function comes into operation by interrupting the counting process and allowing the system to allow movement in that lane. Then the system resumes back to counting after this process is done. The test results show that the system can be physically and successfully implemented.
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Cai, Jinkang, Weiwen Deng, Haoran Guang, Ying Wang, Jiangkun Li, and Juan Ding. "A Survey on Data-Driven Scenario Generation for Automated Vehicle Testing." Machines 10, no. 11 (November 21, 2022): 1101. http://dx.doi.org/10.3390/machines10111101.
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Automated driving is a promising tool for reducing traffic accidents. While some companies claim that many cutting-edge automated driving functions have been developed, how to evaluate the safety of automated vehicles remains an open question, which has become a crucial bottleneck. Scenario-based testing has been introduced to test automated vehicles, and much progress has been achieved. While data-driven and knowledge-based approaches are hot research topics, this survey is mainly about Data-Driven Scenario Generation (DDSG) for automated vehicle testing. Rather than describe the contributions of every study respectively, in this survey, methodologies from various studies are anatomized as solutions for several significant problems and compared with each other. This way, scholars and engineers can quickly find state-of-the-art approaches to the issues they might encounter. Furthermore, several critical challenges that might hinder DDSG are described, and responding solutions are presented at the end of this survey.
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Klinich, Kathleen D., Andrew Leslie, Sumie Hariya, Carol A. C. Flannagan, Matthew P. Reed, and Jason Hallman. "U.S. vehicle occupancy trends relevant to future automated vehicles and mobility services." Traffic Injury Prevention 22, sup1 (October 4, 2021): S116—S121. http://dx.doi.org/10.1080/15389588.2021.1964491.
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Qu, Dayi, Shaojie Wang, Haomin Liu, and Yiming Meng. "A Car-Following Model Based on Trajectory Data for Connected and Automated Vehicles to Predict Trajectory of Human-Driven Vehicles." Sustainability 14, no. 12 (June 9, 2022): 7045. http://dx.doi.org/10.3390/su14127045.
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Connected and Automated Vehicles (CAV) have been rapidly developed, which, inevitably, renders that human-driven and autonomous vehicles share the road. Thus, trajectory prediction is an important research topic, which helps each CAV to efficiently follow a Human-Driven Vehicle (HV). In a wider scope, trajectory prediction, also, helps to improve the throughput of traffic flow and enhance its stability. To realize the trajectory prediction of Connected and Automated Vehicles to Human-Driven Vehicles, a car-following model, which is based on trajectory data, was established. Adding deep neural networks and an Attention mechanism, this paper established a data-driven car-following model, based on CNN-BiLSTM-Attention for CAV, to predict trajectory, by referring to the modeling idea of the traditional car-following model. The trajectory data in the next-generation-simulation (NGSIM) datasets that match the car-following characteristics were selected. In addition, noise-reduction pre-processing of the trajectory data was performed, to make it match the actual car-following situation. Experiments, for selecting the optimal structure of the model and the method of trajectory prediction, were carried out. The data-driven car-following models, such as LSTM, GRU, and CNN-BiLSTM, were selected for comparative analysis of trajectory prediction. The results show that the CNN-BiLSTM-Attention model has the smallest MAE and MSE as well as the largest R2. The CNN-BiLSTM-Attention model has the highest accuracy in vehicle-trajectory prediction. The model can, effectively, realize vehicle-trajectory prediction and provide a theoretical basis for vehicle-trajectory-based velocity guidance of Human-Driven Vehicles. In the future, the model can, also, provide the theoretical basis for Connected and Automated Vehicles, to make car-following decisions in mixed traffic flow.
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Aldulaimi, Hamid Shimal, and Bassem Ben Hamed. "Highway Vehicles’ Overtaking Classification." Transport and Telecommunication Journal 23, no. 4 (November 1, 2022): 284–92. http://dx.doi.org/10.2478/ttj-2022-0023.
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Abstract Highway users can apprehension to certain subjects with utilizing of Vehicular Ad-hoc Networks (VANET) applications if the rules for safe overtaking movement are violated to make the lane change maneuver between vehicles on the highway road. In our research, we suggest an algorithm for semi-automated vehicles S-AV compliant lane change to emphasize rules for safe overtaking between vehicles on the highway. The proposed algorithm technique classify the safe overtaking into major categories and critically analyzed them depending on various classes of lane change movements between vehicles interrelated to road condition based on different performance criteria; this technique will add awareness to drivers traveling on highway to increasing the comfort and safety of driving. Finally, we have conclude and suggest research issues associated to Vehicular Ad-hoc Networks to investigate and ensure the real-time decision of safe overtaking between vehicles on the highway, which is important research task to motivate researchers to connect the semi-automated vehicles with driver face emotion detection and increase driving safety.
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Deb, Shuchisnigdha, Md Mahmudur Rahman, Lesley J. Strawderman, and Teena M. Garrison. "Pedestrians’ Receptivity Toward Fully Automated Vehicles: Research Review and Roadmap for Future Research." IEEE Transactions on Human-Machine Systems 48, no. 3 (June 2018): 279–90. http://dx.doi.org/10.1109/thms.2018.2799523.
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