Current challenges in autonomous driving

Barabás, István; Todoruț, Adrian; Cordoș, Nicolae; Molea, Andreia

doi:10.1088/1757-899x/252/1/012096

Cited by 74 publications

(28 citation statements)

References 1 publication

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“…Regulation To date, adequate standards and regulations for autonomous systems do not exist. There have been numerous high-profile accidents involving Tesla's current automobiles, as well as other automotive and autonomous vehicles [9].…”

Section: A Technical and Social Challenges Of Autonomous Vehiclesmentioning

confidence: 99%

A Comprehensive Review on 3D Object Detection and 6D Pose Estimation With Deep Learning

Hoque

Arafat

et al. 2021

IEEE Access

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Nowadays, computer vision with 3D (dimension) object detection and 6D (degree of freedom) pose assumptions are widely discussed and studied in the field. In the 3D object detection process, classifications are centered on the object's size, position, and direction. And in 6D pose assumptions, networks emphasize 3D translation and rotation vectors. Successful application of these strategies can have a huge impact on various machine learning-based applications, including the autonomous vehicles, the robotics industry, and the augmented reality sector. Although extensive work has been done on 3D object detection with a pose assumption from RGB images, the challenges have not been fully resolved. Our analysis provides a comprehensive review of the proposed contemporary techniques for complete 3D object detection and the recovery of 6D pose assumptions of an object. In this review research paper, we have discussed several proposed sophisticated methods in 3D object detection and 6D pose estimation, including some popular data sets, evaluation matrix, and proposed method challenges. Most importantly, this study makes an effort to offer some possible future directions in 3D object detection and 6D pose estimation. We accept the autonomous vehicle as the sample case for this detailed review. Finally, this review provides a complete overview of the latest in-depth learning-based research studies related to 3D object detection and 6D pose estimation systems and also points out a comparison between some popular frameworks. To be more concise, we propose a detailed summary of the state-of-the-art techniques of modern deep learningbased object detection and pose estimation models.

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Section: A Technical and Social Challenges Of Autonomous Vehiclesmentioning

confidence: 99%

A Comprehensive Review on 3D Object Detection and 6D Pose Estimation With Deep Learning

Hoque

Arafat

et al. 2021

IEEE Access

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“…For example, the AVs need to make decisions fast in a very short time, which also includes many moral dilemmas. 34 The driverless aspect of the AVs makes the legal aspects significantly different from the conventional vehicles. The legal aspects of AVs involve not only technical aspects but also ethical aspects, such as data sharing in the process of AVP 35 and SAVs.…”

Section: Challenges Of Autonomous Vehiclesmentioning

confidence: 99%

Business models and cost analysis of automated valet parking and shared autonomous vehicles assisted by internet of things

Chen

Gao

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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With the rapid development of autonomous vehicles, it is necessary to explore new business opportunities, especially under the assistance of internet of things, which accelerate the penetration in vehicle markets. Automated valet parking and shared autonomous vehicles will be the most active cases promoted by autonomous driving. In this paper, the business models of automated valet parking and shared autonomous vehicles were proposed, further, the cost structures of autonomous vehicles under two cases were investigated from points of car users and owners. In the business models, autonomous driving packages, internet of things devices, and service provider companies are considered as new stakeholders. The cost structure of automated valet parking users changes greatly, with the development of autonomous driving packages whose cost share decreases from ~60% to ~5%. The total cost of automated valet parking users is much higher than conventional parking before 2024. Additionally, the use of shared vehicles relieves financial burden, without trouble of periodical maintenance. For station-based and free-floating car sharing, the price drop of autonomous driving package brings about huge benefits for companies. Peer-to-peer car sharing business effectively decreases financial burden of car owners such that the decrease is less than 20% starting from 2017.

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“…However, to date, there has been little research focused on ensuring that unaccompanied children can ride safely in AVs (Child Safety in a Self-Driving World, 2017; Lee & Mirman, 2018; Morris, 2017; Nooteboom, 2017; Schwebel, 2018; Silver, 2016). Meager consideration of children’s needs is likely due to the large amount of attention being devoted to other topics related to AVs, such as ensuring that the technology underlying these vehicles is robust (Barabás, Todoruţ, Cordoş, & Molea, 2017), confirming that AVs will actually be as safe or safer to use than traditional vehicles (Koopman & Wagner, 2017; Koopman & Wagner, 2018; Sivak & Schoettle, 2015), understanding how AVs will make decisions when preventing someone from harm is not possible (Bonnefon, Shariff, & Rahwan, 2016; Spangler, 2017), and understanding the impacts of AV technologies on infrastructure, economics, and society (Frey, 2017; Litman, 2018).…”

Section: Background and Motivationmentioning

confidence: 99%

Transporting Children in Autonomous Vehicles: An Exploratory Study

Tremoulet

Seacrist²,

McIntosh³

et al. 2019

Hum Factors

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Objective Identify factors that impact parents’ decisions about allowing an unaccompanied child to ride in an autonomous vehicle (AV). Background AVs are being tested in several U.S. cities and on highways in multiple states. Meanwhile, suburban parents are using ridesharing services to shuttle children from school to extracurricular activities. Parents may soon be able to hire AVs to transport children. Method Nineteen parents of 8- to 16-year-old children, and some of their children, rode in a driving simulator in autonomous mode, then were interviewed. Parents also participated in focus groups. Topics included minimum age for solo child passengers, types of trips unaccompanied children might take, and vehicle features needed to support child passengers. Results Parents would require two-way audio communication and prefer video feeds of vehicle interiors, seatbelt checks, automatic locking, secure passenger identification, and remote access to vehicle information. Parents cited convenience as the greatest benefit and fear that AVs could not protect passengers during unplanned trip interruptions as their greatest concern. Conclusion Manufacturers have an opportunity to design family-friendly AVs from the outset, rather than retrofit them to be safe for child passengers. More research, especially usability studies where families interact with technology prototypes, is needed to understand how AV design impacts child passengers. Application Potential applications of this research include not only designing vehicles that can be used to safely transport children, seniors who no longer drive, and individuals with disabilities but also developing regulations, policies, and societal infrastructure to support safe child transport via AVs.

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Current challenges in autonomous driving

Cited by 74 publications

References 1 publication

A Comprehensive Review on 3D Object Detection and 6D Pose Estimation With Deep Learning

A Comprehensive Review on 3D Object Detection and 6D Pose Estimation With Deep Learning

Business models and cost analysis of automated valet parking and shared autonomous vehicles assisted by internet of things

Transporting Children in Autonomous Vehicles: An Exploratory Study

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