vehicle automation
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2022 ◽  
Vol 14 (1) ◽  
pp. 483
Author(s):  
Jianguo Gong ◽  
Xiucheng Guo ◽  
Lingfeng Pan ◽  
Cong Qi ◽  
Ying Wang

Research on the influence of age on various automated driving conditions will contribute to an understanding of driving behavior characteristics and the development of specific automated driving systems. This study aims to analyze the relationship between age and takeover behavior in automated driving, where 16 test conditions were taken into consideration, including two driving tasks, two warning times and four driving scenarios. Forty-two drivers in Beijing, China in 2020 were recruited to participate in a static driving simulator with Level 3 (L3) conditional automation to obtain detailed test information of the recorded takeover time, mean speed and mean lateral offset. An ANOVA test was proposed to examine the significance among different age groups and conditions. The results confirmed that reaction time increased significantly with age and the driving stability of the older group was worse than the young and middle groups. It was also indicated that the older group could not adapt to complex tasks well when driving due to their limited cognitive driving ability. Additionally, the higher urgency of a scenario explained the variance in the takeover quality. According to the obtained influencing mechanisms, policy implications for the development of vehicle automation, considering the various driving behaviors of drivers, were put forward, so as to correctly identify the high-risk driving conditions in different age groups. For further research, on-road validation will be necessary in order to check for driving simulation-related effects.


2022 ◽  
pp. 890-909
Author(s):  
David A. Thurlow ◽  
Ben D. Sawyer

New advancements in vehicle automation, electrification, data connectivity, and digital methods of sharing—known collectively as New Mobility—are poised to revolutionize transportation as it is known today. Exactly what results this disruption will lead to, however, remains unknown, as indeed the technologies and their uses are still taking shape amidst myriad interests. The impacts of this shift to New Mobility could be enormous, shaping economies, cities, and the lives of people in them. It is therefore vitally important for public interests to play a strong role in the development and deployment of these technologies. With the current trajectory of these technologies warning of the potential for increased energy use, environmental costs, and social inequity, interests at the community level need to be included and influential as soon as possible.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Chenglong Liu ◽  
Yuchuan Du ◽  
Yiheng Ge ◽  
Difei Wu ◽  
Cong Zhao ◽  
...  

The new generation of smart highway (NGSH) has become an irresistible global trend to improve transport efficiency and safety. The exploration of the features and framework for NGSH can guide us to upgrade the current highway system. This paper summarizes the fundamental features of the NGSH from the perspective of the interactive evolution of automobile industry and road transport. In line with the popularity of automated and connected vehicles, the primary technical features of the NGSH are proposed as (I) complete elements sensing, (II) cyber-physical systems, (III) cooperative vehicle-infrastructure applications, and (IV) 5th generation mobile communication technology. The corresponding physical framework and data flow are introduced, in which three data attributes (data accuracy, dimensionality, and freshness) are highlighted to describe the data requirements for various scenarios. The development path of the NGSH is further discussed in terms of the different vehicle automation levels. The characteristics of five levels of NGSH are identified from R1 to R5. Different combinations of NGSH level and vehicle automation level lead to distinct system functions. Several urgent problems in the current stage are pointed out in terms of system compatibility, standard specification, and information security. This paper provides new insights for sustainable and reproducible highway reformation, drawing some implications for NGSH design.


Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8079
Author(s):  
Jose V. Riera ◽  
Sergio Casas ◽  
Marcos Fernández ◽  
Francisco Alonso ◽  
Sergio A. Useche

Motion platforms have been widely used in Virtual Reality (VR) systems for decades to simulate motion in virtual environments, and they have several applications in emerging fields such as driving assistance systems, vehicle automation and road risk management. Currently, the development of new VR immersive systems faces unique challenges to respond to the user’s requirements, such as introducing high-resolution 360° panoramic images and videos. With this type of visual information, it is much more complicated to apply the traditional methods of generating motion cues, since it is generally not possible to calculate the necessary corresponding motion properties that are needed to feed the motion cueing algorithms. For this reason, this paper aims to present a new method for generating non-real-time gravito-inertial cues with motion platforms using a system fed both with computer-generated—simulation-based—images and video imagery. It is a hybrid method where part of the gravito-inertial cues—those with acceleration information—are generated using a classical approach through the application of physical modeling in a VR scene utilizing washout filters, and part of the gravito-inertial cues—the ones coming from recorded images and video, without acceleration information—were generated ad hoc in a semi-manual way. The resulting motion cues generated were further modified according to the contributions of different experts based on a successive approximation—Wideband Delphi-inspired—method. The subjective evaluation of the proposed method showed that the motion signals refined with this method were significantly better than the original non-refined ones in terms of user perception. The final system, developed as part of an international road safety education campaign, could be useful for developing further VR-based applications for key fields such as driving assistance, vehicle automation and road crash prevention.


2021 ◽  
Vol 12 ◽  
pp. 100495
Author(s):  
Monica Grosso ◽  
Loan Cristinel Raileanu ◽  
Jette Krause ◽  
María Alonso Raposo ◽  
Amandine Duboz ◽  
...  
Keyword(s):  

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7744
Author(s):  
Pablo Fondo-Ferreiro ◽  
David Candal-Ventureira ◽  
Francisco Javier González-Castaño ◽  
Felipe Gil-Castiñeira

Vehicle automation is driving the integration of advanced sensors and new applications that demand high-quality information, such as collaborative sensing for enhanced situational awareness. In this work, we considered a vehicular sensing scenario supported by 5G communications, in which vehicle sensor data need to be sent to edge computing resources with stringent latency constraints. To ensure low latency with the resources available, we propose an optimization framework that deploys User Plane Functions (UPFs) dynamically at the edge to minimize the number of network hops between the vehicles and them. The proposed framework relies on a practical Software-Defined-Networking (SDN)-based mechanism that allows seamless re-assignment of vehicles to UPFs while maintaining session and service continuity. We propose and evaluate different UPF allocation algorithms that reduce communications latency compared to static, random, and centralized deployment baselines. Our results demonstrated that the dynamic allocation of UPFs can support latency-critical applications that would be unfeasible otherwise.


2021 ◽  
pp. 335-358
Author(s):  
Sunil Kr. Sharma ◽  
Sunil Kr. Singh ◽  
Subhash C. Panja

2021 ◽  
Vol 13 (22) ◽  
pp. 12405
Author(s):  
Yuche Chen ◽  
Ruixiao Sun ◽  
Xuanke Wu

Vehicle automation requires new onboard sensors, communication equipment, and/or data processing units, and may encourage modifications to existing onboard components (such as the steering wheel). These changes impact the vehicle’s mass, auxiliary load, coefficient of drag, and frontal area, which then change vehicle performance. This paper uses the powertrain simulation model FASTSim to quantify the impact of autonomy-related design changes on a vehicle’s fuel consumption. Levels 0, 2, and 5 autonomous vehicles are modeled for two battery-electric vehicles (2017 Chevrolet Bolt and 2017 Nissan Leaf) and a gasoline powered vehicle (2017 Toyota Corolla). Additionally, a level 5 vehicle is divided into pessimistic and optimistic scenarios which assume different electronic equipment integration format. The results show that 4–8% reductions in energy economy can be achieved in a L5 optimistic scenario and an 10–15% increase in energy economy will be the result in a L5 pessimistic scenario. When looking at impacts on different power demand sources, inertial power is the major power demand in urban driving conditions and aerodynamic power demand is the major demand in highway driving conditions.


Author(s):  
Andreas Riegler ◽  
Andreas Riener ◽  
Clemens Holzmann

Abstract While augmented reality (AR) interfaces have been researched extensively over the last decades, studies on their application in vehicles have only recently advanced. In this paper, we systematically review 12 years of AR research in the context of automated driving (AD), from 2009 to 2020. Due to the multitude of possibilities for studies with regard to AR technology, at present, the pool of findings is heterogeneous and non-transparent. From a review of the literature we identified N = 156 papers with the goal to analyze the status quo of existing AR studies in AD, and to classify the related literature into application areas. We provide insights into the utilization of AR technology used at different levels of vehicle automation, and for different users (drivers, passengers, pedestrians) and tasks. Results show that most studies focused on safety aspects, driving assistance, and designing non-driving related tasks. AR navigation, trust in automated vehicles (AVs), and interaction experiences also marked a significant portion of the published papers, however a wide range of different parameters was investigated by researchers. Among other things, we find that there is a growing trend toward simulating AR content within virtual driving simulators. We conclude with a discussion of open challenges, and give recommendation for future research in automated driving at the AR side of the reality-virtuality continuum.


2021 ◽  
Vol 13 (20) ◽  
pp. 11264
Author(s):  
Tamás Hegedűs ◽  
Dániel Fényes ◽  
Balázs Németh ◽  
Péter Gáspár

The concept of vehicle automation is a promising approach to achieve sustainable transport systems, especially in an urban context. Automation requires the integration of learning-based approaches and methods in control theory. Through the integration, a high amount of information in automation can be incorporated. Thus, a sustainable operation, i.e., energy-efficient and safe motion with automated vehicles, can be achieved. Despite the advantages of integration with learning-based approaches, enhanced vehicle automation poses crucial safety challenges. In this paper, a novel closed-loop matching method for control-oriented purposes in the context of vehicle control systems is presented. The goal of the method is to match the nonlinear vehicle dynamics to the dynamics of a linear system in a predefined structure; thus, a control-oriented model is obtained. The matching is achieved by an additional control input from a neural network, which is designed based on the input–output signals of the nonlinear vehicle system. In this paper, the process of closed-loop matching, i.e., the dataset generation, the training, and the evaluation of the neural network, is proposed. The evaluation process of the neural network through data-driven reachability analysis and statistical performance analysis methods is carried out. The proposed method is applied to achieve the path following functionality, in which the nonlinearities of the lateral vehicle dynamics are handled. The effectiveness of the closed-loop matching and the designed control functionality through high fidelity CarMaker simulations is illustrated.


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