Autonomous Driving — a Challenge for the Automotive Industry

Bardt, Hubertus

doi:10.1007/s10272-017-0668-5

Cited by 6 publications

(3 citation statements)

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“…Second, knowledge development in an AV TIS features a high level of sectoral diversity. While a large share of knowledge development activity can be attributed to automotive OEMs (e.g., Ford, Toyota, Nissan, GM, and BMW) and component suppliers (e.g., Robert Bosch, Continental, and Denso), companies from the electronics sector (e.g., Marvell, Sony, and LG) and the internet sector (e.g., Google) as well as universities (e.g., Carnegie Mellon, Chinese Academy of Science, and MIT) and public research institutes (e.g., DARPA) are also making significant contributions (Fang and Li, 2016;Bardt, 2017;Youtie et al, 2017). In line with the studies listed in Table 1, this study seeks to enhance our understanding of the patterns of knowledge development and diffusion in an AV TIS.…”

Section: Literature Reviewmentioning

confidence: 99%

Patterns of knowledge development and diffusion in the global autonomous vehicle technological innovation system: a patent-based analysis

Meng

Cai

et al. 2019

IJATM

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This study focuses on assessing the knowledge development and diffusion functions of the global autonomous vehicle (AV) technological innovation system (TIS). To that end, this study uses patent portfolio analysis. A comprehensive and dynamic picture is depicted through our evolutionary analysis covering 5,986 AV patents applied for from 1997 to 2016 worldwide, which were assigned to seven relevant sectors (automotive, machinery, aircraft/defence, electronics, information/software service, mobility/logistics service, and research) and focused on five key technology categories (control and actuation, perception and localisation, computation, communication, and system integration). Three key findings from our study are: 1) sectors differ in terms of the amount of knowledge they developed and the distribution of knowledge across technology categories; 2) different sectors and technology categories have uneven roles in the global knowledge diffusion network; 3) knowledge development and diffusion patterns exhibit significant evolutionary tendencies. Our research deepens the current understanding of the dynamics of AV innovation and contributes to TIS theory.

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Section: Literature Reviewmentioning

confidence: 99%

Patterns of knowledge development and diffusion in the global autonomous vehicle technological innovation system: a patent-based analysis

Meng

Cai

et al. 2019

IJATM

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“…Furthermore, ADS are subject to different research challenges (technical, non-technical, social, and policy) [13]. In particular, different driving scenarios related to traffic and humans bring new system requirements to ADS [14]. These cases induce that certification of an automated system can only be achieved with the support of modelling and simulation [15].…”

Section: Introductionmentioning

confidence: 99%

Phenomenological Modelling of Camera Performance for Road Marking Detection

Tarik

Arefnezhad

et al. 2021

Energies

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With the development of autonomous driving technology, the requirements for machine perception have increased significantly. In particular, camera-based lane detection plays an essential role in autonomous vehicle trajectory planning. However, lane detection is subject to high complexity, and it is sensitive to illumination variation, appearance, and age of lane marking. In addition, the sheer infinite number of test cases for highly automated vehicles requires an increasing portion of test and validation to be performed in simulation and X-in-the-loop testing. To model the complexity of camera-based lane detection, physical models are often used, which consider the optical properties of the imager as well as image processing itself. This complexity results in high efforts for the simulation in terms of modelling as well as computational costs. This paper presents a Phenomenological Lane Detection Model (PLDM) to simulate camera performance. The innovation of the approach is the modelling technique using Multi-Layer Perceptron (MLP), which is a class of Neural Network (NN). In order to prepare input data for our neural network model, massive driving tests have been performed on the M86 highway road in Hungary. The model’s inputs include vehicle dynamics signals (such as speed and acceleration, etc.). In addition, the difference between the reference output from the digital-twin map of the highway and camera lane detection results is considered as the target of the NN. The network consists of four hidden layers, and scaled conjugate gradient backpropagation is used for training the network. The results demonstrate that PLDM can sufficiently replicate camera detection performance in the simulation. The modelling approach improves the realism of camera sensor simulation as well as computational effort for X-in-the-loop applications and thereby supports safety validation of camera-based functionality in automated driving, which decreases the energy consumption of vehicles.

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“…Especially the automotive industry is well known for entering a new era, driven by changing business models and amended value chains. Several technological developments currently have the potential to substantially transform this type of industry branch (Bardt, 2017). In this vein, the hardest part of successful leading an organizational transformation is the cultural mindset with strong values that shape a corporate's identity.…”

Section: Introductionmentioning

confidence: 99%

Linking Corporate Culture Values and Organizational Agility: An Empirical Analysis within the Automotive Industry

Ahl

2020

MBRQ

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The purpose of this paper is to analyze the link of corporate values with respect to the concept of organizational agility. The motivation has been one of discovery within corporations from the automotive industry, dealing in uncertain and turbulent environments. The paper offers an overview of literature on agility frameworks, comparing overlapping areas of corporate values from the 10 largest premium automo ve manufacturers. Survey data from over 186 respondents provide quantitative validity to establish understanding of how organizational agility is translated into values and behaviors. A conceptual framework for synthesizing the relationships is proposed based on the case studies' empirical findings. As a result, organizations can benefit from its development in two ways: (1) it helps measuring the agility-values fit with an integra ve perspec ve, and (2) it provides valuable insights into critical elements of their organizational culture. Moreover, a wide range of values under theoretical and practical situations is proposed. This study will enable executives, especially from the automotive industry, to identify suitable characteristics that would simultaneously improve an organization's agile performance by considering aspects of corporate culture. Consequently, this study is more industry-specific and less inclusive.

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Autonomous Driving — a Challenge for the Automotive Industry

Cited by 6 publications

References 0 publications

Patterns of knowledge development and diffusion in the global autonomous vehicle technological innovation system: a patent-based analysis

Patterns of knowledge development and diffusion in the global autonomous vehicle technological innovation system: a patent-based analysis

Phenomenological Modelling of Camera Performance for Road Marking Detection

Linking Corporate Culture Values and Organizational Agility: An Empirical Analysis within the Automotive Industry

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