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Innovation in Ecosystem Business Models: an Application to Maas and Autonomous Vehicles in Urban Mobility System
Innovation in ecosystem business models : An application to MaaS and Autonomous vehicles in urban mobility system Rodrigo Gandia To cite this version: Rodrigo Gandia. Innovation in ecosystem business models : An application to MaaS and Autonomous vehicles in urban mobility system. Economics and Finance. Université Paris-Saclay; University of Lavras, UFLA (Brésil), 2020. English. NNT : 2020UPASC018. tel-02895349 HAL Id: tel-02895349 https://tel.archives-ouvertes.fr/tel-02895349 Submitted on 9 Jul 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Innovation in Ecosystem Business Models: An Application to MaaS and Autonomous Vehicles in Urban Mobility System Thèse de doctorat de l'université Paris-Saclay École doctorale n° 573 Interfaces : approches interdisciplinaires, fon- dements, applications et innovation (Interfaces) Spécialité de doctorat : Ingénierie des systèmes complexes Unité de recherche : Université Paris-Saclay, CentraleSupélec, Laboratoire Genie Industriel, 91190, Gif-sur-Yvette, France. Référent : CentraleSupélec Thèse présentée et -
Autonomous Vehicle, Sensing and Communication Survey 1 Introduction
Autonomous Vehicle, Sensing and Communication Survey Edited and submitted by Shraga Shoval Prepared by Shlomi Hacohen and Oded Medina Department of Mechanical Engineering, Ariel University, Ariel, Israel. August 2020 Abstract Autonomous vehicles introduce dramatic changes to the way in which we travel. This technology has the potential to impact the transportation across a wide array of categories including safety, congestion, and travel behavior. In this report we review the main issues involved in autonomous driving as discussed in the literature and shed light on topics that we believe require further development. 1 Introduction The challenges in autonomous driving require a combination of many capabilities, among them: localization, motion planning, vehicle’s systems control (steering, acceleration/deceleration, signaling, etc.), road perception, prediction of other road-users behavior, awareness of dangers, etc. These capabilities have a various level of importance for various levels of driving automation. Even though the first autonomous vehicle (AV) was experimented in 1926 [104], a real-modern autonomous vehicle was first presented in 1986 by a team from Carnegie Mellon University [58]. Since 2010, many major automotive manufacturers, such as GM, Mercedes Benz, Ford, Toyota, and many more are developing AVs [90]. A demonstration of AV equipped with numerous sensors and communication systems was presented by Toyota in 2013 [10]. In 2016, Google’s AV has passed over one million kilometers. These events present a glimpse to the landmarks in the development of AV that, due to the complexity of the task, progresses slowly with considerable amount of attention to safety and reliability. AVs need a large amount of data for reliable decision making. -
*仅供参考 * for Identification Purpose Only
*仅供参考 * For identification purpose only 2020年3月 Mar. 2020 1 声明 Disclaimer 本介绍片由长城汽车股份有限公司(「公司」)编制,只作企业通讯和一般参考之用。公司无意在任 何司法管辖区使用本介绍片作为出售和招揽他人购买公司任何证券的要约,或用作投资公司证券的决 定基础。未经咨询专业意见的情况下,不得使用或依赖此等全部资料。本介绍纯属简报性质,并非完 整地描述公司、公司业务、目前或过去的经营业绩或业务未来前景。 公司不会为本介绍片发出任何明文或隐含的保证或声明。公司特此强调,不会对任何人使用或依赖本 介绍片的任何资料(财务或其它资料)承担任何责任。 This presentation is prepared by Great Wall Motor Company Limited (the “Company”) and is solely for the purpose of corporate communication and general reference only. The presentation is not intended as an offer to sell, or to solicit an offer to buy or form any basis of investment decision for any class of securities of the Company in any jurisdiction. All such information should not be used or relied on without professional advice. The presentation is a brief summary in nature and do not purport to be a complete description of the Company, its business, its current or historical operating results or its future prospects. This presentation is provided without any warranty or representation of any kind, either expressed or implied. The Company specifically disclaims all responsibilities in respect of any use or reliance of any information, whether financial or otherwise, contained in this presentation. 2 2 业绩摘要 Results Highlights 2019 VS 2018 962.11亿元 营业总收入 992.30亿元 RMB96.211 billion Total operating revenue RMB99.230 billion 105.86万辆 销量 104.37万辆 1,058,648 units Sales volume 1,043,707 units 45.31亿元 净利润 52.48亿元 RMB4.531 billion Net profit RMB5.248 billion 543.99亿元 净资产 526.89亿元 RMB54.399 billion Net assets RMB52.689 billion 33 目录 Contents 行业情况 Auto Industry Overview 公司经营情况 Operations Review 4 第一部分 Section 1 行业情况 Auto Industry Overview 55 行业运行情况 Auto Industry Overview 中国汽车市场正在经历至暗时刻 The PRC’s auto market faced its darkest hour 2018年及2019年全球销量前五国家 单位:百万台 Top 5 countries in terms of global car sales in 2018 and 2019 Mn units 千人保有量仍有增长空间 30 Room for growth for car ownership per 1,000 people 25.8 25 单位:台 units 1,000 20 900 837 17.0 800 700 15 591 589 600 500 10 400 373 5.2 300 5 3.8 3.6 200 173 100 22 0 0 中国 美国 日本 印度 德国 美国U.S. -
Using Fuzzy Logic in Automated Vehicle Control
Intelligent Transportation Systems Using Fuzzy Logic in Automated Vehicle Control José E. Naranjo, Carlos González, Ricardo García, and Teresa de Pedro, Instituto de Automática Industrial Miguel A. Sotelo, Universidad de Alcalá de Henares ntil recently, in-vehicle computing has been largely relegated to auxiliary U tasks such as regulating cabin temperature, opening doors, and monitoring Automated versions fuel, oil, and battery-charge levels. Now, however, computers are increasingly assum- of a mass-produced ing driving-related tasks in some commercial models. Among those tasks are vehicle use fuzzy logic • maintaining a reference velocity or keeping a safe nomous robots and fuzzy control systems and the distance from other vehicles, Universidad de Alcalá de Henares’s knowledge of techniques to both • improving night vision with infrared cameras, and artificial vision. (The “Intelligent-Vehicle Systems” • building maps and providing alternative routes. sidebar discusses other such projects.) We’re devel- address common oping a testbed infrastructure for vehicle driving that Still, many traffic situations remain complex and includes control-system experimentation, strategies, challenges and difficult to manage, particularly in urban settings. and sensors. All of our facilities and instruments are The driving task belongs to a class of problems that available for collaboration with other research groups incorporate human depend on underlying systems for logical reasoning in this field. So far, we’ve automated and instru- and dealing with uncertainty. So, to move vehicle mented two Citroën Berlingo mass-produced vans procedural knowledge computers beyond monitoring and into tasks related to carry out our objectives. to environment perception or driving, we must inte- into the vehicle control grate aspects of human intelligence and behaviors Automated-vehicle equipment so that vehicles can manage driving actuators in a Figure 1 shows two mass-produced electric Cit- algorithms. -
Olivetree Financial, NDR New York
AMBARELLA.COM AMBARELLA.COM January 15, 2020 COPYRIGHT COPYRIGHT AMBARELLA 2019 Olivetree Financial, NDR New York Louis Gerhardy, Corporate Development 1 Forward-Looking Statements This presentation contains forward-looking statements that are subject to many risks and uncertainties. All statements made in this presentation other than statements of historical facts are forward-looking statements, including, without limitation, statements regarding Ambarella’s strategy, future operations, financial targets, future revenues, projected costs, prospects, plans and objectives for future operations, future product introductions, future rate of our revenue growth, the size of markets addressed by the company's solutions and the growth rate of those markets, technology trends, our ability to address market and customer demands and to timely develop new or enhanced solutions to meet those demands, our ability to achieve design wins, and our ability to retain and expand our customer and partner relationships. In some cases, you can identify forward-looking statements by terms such as "may," "will," "should," "could," "would," "expects," "plans," "anticipates," "believes," "estimates," "projects," "predicts," "potential," or the negative of those terms, and similar expressions and comparable terminology intended to identify forward-looking statements. We have based forward-looking statements largely on our estimates of our financial results and our current expectations and projections about future events, markets and financial trends that we believe -
Connected and Autonomous Vehicles: Implications for Policy and Practice in City and Transportation Planning
Connected and Autonomous Vehicles: Implications for Policy and Practice in City and Transportation Planning by Charles Ng supervised by Laura Taylor A Major Paper submitted to the Faculty of Environmental Studies in partial fulfillment of the requirements for the degree of Master in Environmental Studies York University, Toronto, Ontario, Canada December 8, 2017 Acknowledgments This paper could not have been completed without the help and support of the caring individuals that I am thankful to have in my life. I would like to thank and acknowledge my mother, Maria, and my sister, Ka Lang for providing me with love and support; my advisor, Peter Timmerman, and my supervisor, Laura Taylor, for providing me with academic and non-academic support; and my invaluable friends that I have made in the MES program for their encouragement, support and relief. i Foreword My Area of Concentration for my Plan of Study is sustainable transportation planning for growth management. Connected and Autonomous Vehicles will change the urban landscape, the roles of governments and present new challenges to planners. This paper has allowed me to view transportation planning through the lens of emerging technologies and how this affects cities in the short and long term. There are many sustainability and growth management implications with Connected and Autonomous Vehicles. For example, automated vehicles can foster decentralization because it easily enables travel however, if utilized correctly, automated vehicles can also compliment local transit systems to support intensification. This is especially important in Ontario (Canada’s first province to allow testing of autonomous vehicles on public roads) as it directly relates to the goals and policies related to sprawl and sustainability as outlined in Ontario’s four provincial land use plans: The Growth Plan for the Greater Golden Horseshoe (GGH), The Greenbelt Plan, The Oak Ridges Moraine Conservation Plan and the Niagara Escarpment Plan. -
The Study on Innovation, Development and Implementation
ISSN (Online) 2581-9429 IJAR SCT ISSN (Print) 2581-XXXX International Journal of Advanced Research in Science, Communication and Technology (IJARSCT) Volume 11, Issue 1, November 2020 Impact Factor: 4.819 The Study on Innovation, Development and Implementation of the Self-driving Car Aniruddha Chaki Student, Department of Electrical Engineering Siliguri Institute of Technology, Siliguri, India Abstract: The development of the self-driving car is one of the greatest inventions of the century. With the technological advancement, the implementation of the autonomous vehicle has become the major attention among the researchers. This paper discusses the brief history of self-driving cars, its research and development, key technologies behind the self-driving, main aspects of implementing self-driving cars. The paper also describes some challenges with possible solutions to the fully autonomous vehicle in mass implementation. Keywords: Advanced Driver Assistance System (ADAS), autonomous, navigation, positioning, self- driving technology, radar, lidar, path planning, obstacle avoidance, Full Self driving (FSD), accidents, protests, advantages, challenges. I. INTRODUCTION In this 21st-century progress in technology has made man as omnipotent, omniscient and omnipresent as a god. It is being tried to find out and accomplish any work with higher efficiency, lesser cost, and least possible effort. This makes researchers explore the domain of Automation, Machine learning, and Artificial Intelligence to handle the hardest of the jobs which were once tedious and cumbersome for humans [1]. We are driving towards the future where humans will only be involved in high mental ability skills and all the other works will be automated [2]. In this paper, the previous researches in the field of self-driving have been studied. -
Study on Electrical Vehicle and Its Scope in Future
© 2018 JETIR February 2018, Volume 5, Issue 2 www.jetir.org (ISSN-2349-5162) Study on Electrical Vehicle and Its Scope in Future Divya Sharma, Department of Electrical Engineering Galgotias University, Yamuna Expressway Greater Noida, Uttar Pradesh ABSTRACT: The cars are based on programming in advanced time to give the individual driver relaxed driving. In the automobile industry, various opportunities are known, which makes a car automatic. Google, the largest network, has been working on self-driving cars since 2010 and yet an innovative adaptation to present a mechanised vehicle in a radically new model is continuing to be launched. The modelling, calibration and study of changes in city morphology in autonomous vehicles (AVs). Transport system are utilized to travel among the tangential houses as well as the intermediate work and necessitate transportation space. The main benefits of an autonomous vehicle areit can be operated day parking area for other uses, mitigatemetropolitanground. We also reduce the cost per kilometre of driving. Researchers are interested in the area of automotive automation, where most applications are found in different places. The technology in this research paper will help to understand the quick, present and future technologies used or used in the automotive field to render automotive automation. KEYWORDS: Autonomous Vehicle, Linriccan Wonder, Robotic Van, Self-Driving Car, Tesla corporation. INTRODUCTION Users all over the world are delighted with the introduction of an automated vehicle for the general -
Forecasting Americans' Long-Term Adoption of Connected And
FORECASTING AMERICANS’ LONG-TERM ADOPTION OF CONNECTED AND AUTONOMOUS VEHICLE TECHNOLOGIES 1 Prateek Bansal 2 Graduate Research Assistant 3 Department of Civil, Architectural and Environmental Engineering 4 The University of Texas at Austin 5 [email protected] 6 Phone: 512-293-1802 7 Kara M. Kockelman 8 (Corresponding Author) 9 E.P. Schoch Professor in Engineering 10 Department of Civil, Architectural and Environmental Engineering 11 The University of Texas at Austin 12 [email protected] 13 14 15 The following paper is a pre-print, the final publication can be found in 16 Transportation Research Part A: Policy and Practice, 95:49-63 (2017). 17 18 19 ABSTRACT 20 Automobile enterprises, researchers, and policymakers are interested in knowing the future of 21 connected and autonomous vehicles (CAVs). To this end, this study proposes a new simulation- 22 based framework to forecast Americans’ long-term (year 2015 to 2045) adoption levels of CAV 23 technologies under eight different scenarios based on: 5% and 10% annual drops in technology 24 prices; 0%, 5%, and 10% annual increments in Americans’ willingness to pay (WTP); and 25 changes in government regulations. This simulation was calibrated with the data obtained from a 26 survey of 2,167 Americans, in order to obtain their preferences for CAV technologies and their 27 household’s annual vehicle transaction decisions. 28 29 Results indicate that the average WTP (of respondents with a non-zero WTP) to add connectivity 30 and Level 3 and Level 4 automations are $110, $5,551, and $14,589, respectively. Long-term 31 fleet evolution suggests that the privately held light-duty vehicle fleet will have 24.8% Level 4 32 AV penetration by 2045 under an annual 5% price drop and constant WTP values. -
From Local Academic Spin-Off to International Firm: the Case of Vislab
International Business Research; Vol. 13, No. 6; 2020 ISSN 1913-9004 E-ISSN 1913-9012 Published by Canadian Center of Science and Education From Local Academic Spin-Off to International Firm: The Case of VisLab Maria Cristina Arcuri1, Elisa Bocchialini2 & Gino Gandolfi2 1 Department of Economics and Management, University of Florence, Florence, Italy 2 Department of Economics and Management, University of Parma, Parma, Italy Correspondence: Elisa Bocchialini, Department of Economics and Management, University of Parma, Via J.F. Kennedy, 6 – 43125 Parma, Italy. Received: April 7, 2020 Accepted: May 8, 2020 Online Published: May 22, 2020 doi:10.5539/ibr.v13n6p100 URL: https://doi.org/10.5539/ibr.v13n6p100 Abstract Universities play an important role in developing and transferring technology. In Italy, much innovation takes place where universities are located outside large towns, as in the case of VisLab. VisLab, the Vision and Intelligent Systems Laboratory, founded by Prof. Alberto Broggi of Parma University, is a pioneer in perception systems and autonomous vehicle research. It is also the spin-off of the University of Parma acquired by Silicon Valley company Ambarella Inc., in July 2015 for $30 million. After the deal, VisLab remained in Italy and all the staff, about thirty researchers, were hired by VisLab for the Parma location. This paper examines the university-industry interaction and, in particular, academic spin-off, as a source of economic growth, pointing out the importance of the context. The study describes the main characteristics of the VisLab case, including the possible alternative strategies, the structure of the final M&A deal and the advantages deriving from Parma and surrounding area. -
Terramax Vision at the Urban Challenge 2007
1 TerraMax Vision at the Urban Challenge 2007 Alberto Broggi, Andrea Cappalunga, Claudio Caraffi, Stefano Cattani, Stefano Ghidoni, Paolo Grisleri, Pier Paolo Porta, Matteo Posterli, Paolo Zani VisLab – Dipartimento di Ingegneria dell’Informazione Universita` degli Studi di Parma, ITALY www.vislab.it fbroggi,kappa,caraffi,cattani,ghidoni,grisleri,portap,posterli,[email protected] Abstract—This paper presents the TerraMax vision systems used during the 2007 DARPA Urban Challenge. First a descrip- tion of the different vision systems is provided, focusing on their hardware configuration, calibration method and tasks. Then each componentis described in details, focusing on the algorithms and sensor fusion opportunities: obstacle detection, road markings detection and vehicle detection. The conclusions summarize the lesson learned from the developing of the passive sensing suite and its succesful fielding in the Urban Challenge. I. INTRODUCTION The Challenges organized by DARPA are considered some of the most important milestones in the field of vehicular Fig. 1. The TerraMax vehicle. robotics. Not only did DARPA provide a vigorous help in the flourishing of new technological solutions, but the many researchers who accepted these challenges demonstrated that in order to decide on the action to be taken, it is not sufficient the current technology is indeed mature enough to drive to model the vehicle itself like it happens on the control side, vehicles in off-road and urban-like environments. but it is mandatory to model the real world as well; therefore, The design and realization of autonomous vehicles capable a huge number of situations must be taken into account. of handling unknown and dynamic situations involve different Different technologies have been tested and implemented aspects, spanning from new technologies to implementation, on the robotic vehicles that participated in the DARPA Urban from concept to hardware issues, challenging many different Challenge, ranging from conservative products up to com- research fields. -
2014 Automated Vehicles Symposium Proceedings
2014 Automated Vehicles Symposium Proceedings 2014 Automated Vehicle Symposium – Synopsis of Proceedings DISCLAIMER The opinions, findings, and conclusions expressed in this publication are those of the speakers and contributors to the Automated Vehicle Symposium and not necessarily those of the United States Department of Transportation. The United States Government assumes no liability for its contents or use thereof. If trade names manufacturers’ names or specific products are mentioned, it is because they are considered essential to the object of the publication and should not be construed as an endorsement. The United States Government does not endorse products or manufacturers. 2014 Automated Vehicles Symposium Proceedings—Final December 2014 Publication Number: FHWA-JPO-14-176 Prepared by: Volpe National Transportation Systems Center Cambridge, MA 02142 Prepared for: Intelligent Transportation Systems Joint Program Office Office of the Assistant Secretary for Research and Technology 1200 New Jersey Avenue, S.E. Washington, DC 20590 2 Acknowledgments The 2014 Automated Vehicles Symposium (AVS 2014) was produced through a partnership between the Association of Unmanned Vehicle Systems International (AUVSI) and Transportation Research Board (TRB), and is indebted to its many volunteer contributors and speakers who developed the symposium content, produced sessions, and contributed to the development of these proceedings. AVS 2014 also benefitted from the direct financial contributions of its commercial benefactors, and the institutional support of the many companies and agencies that supported the time, travel, and participation for their staff. The organizing committee gratefully acknowledges the United States Department of Transportation (U.S. DOT) Intelligent Transportation Systems Joint Program Office (ITS JPO) for the level of its support to AVS 2014 and for these proceedings.