Autonomous Road Vehicles
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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 -
Tesla Autopilot : Semi Autonomous Driving, an Uptick for Future Autonomy
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 03 Issue: 09 | Sep-2016 www.irjet.net p-ISSN: 2395-0072 Tesla Autopilot : Semi Autonomous Driving, an Uptick for Future Autonomy Shantanu Ingle1, Madhuri Phute2 1Department of E&TC, Pune Institute of Computer Technology, Pune, Maharashtra, India 2 Department of E&TC, Pune Institute of Computer Technology, Pune, Maharashtra, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Manual driving has certainly changed the way response to traffic conditions. Once the driver arrives at the we travel and explore different parts of the globe, with total destination, Model S or Model X scans for a parking space human control and with human intuitions and previous and parallel parks on the driver's command[2]. In the new driving experiences. But manual control doesn’t ensure safety Autopilot, the instrument cluster’s new driver focused and zero fatalities in every possible driving condition. design shows the real-time information used by the car to Autonomous driving is the answer to that problem. However, intelligently determine the vehicle’s behavior in that artificial intelligence hasn't yet touched every aspect of moment relative to its surroundings[3]. Along with the technology. In this paper we present a brief overview about autopilot feature, the driving behavior of each Tesla car, how Tesla Motor’s semi autonomous driving technology called while navigating through different road conditions, is shared Tesla Autopilot is changing the way we navigate and transport to its central server. Based on machine learning and Tesla by incorporating state of the art current artificial intelligence design engineer recommendations, a new feature update is and hardware technology, and enhancing the next generation developed and launched to every other Tesla car on planet. -
Autonomous Vehicles
10/27/2017 Looming on the Horizon: Autonomous Vehicles Jim Hedlund Highway Safety North MN Toward Zero Deaths Conference October 26, 2017 St. Paul, MN In the next 25 minutes • AV 101 . What’s an autonomous vehicle (AV)? . What’s on the road now? . What’s coming and when? . What does the public think about AVs? . What are current state laws on AVs? • Traffic safety issues for states . AV testing . AV operations . What should states do . What should national organizations do 2 1 10/27/2017 Report released Feb. 2, 2017 3 Autonomous = self-driving, right? So what’s the challenge? • When all vehicles are autonomous: . The passenger economy: transportation as a service . No crashes (at least none due to driver error – about 94% currently) • And it’s coming soon . 26 states and DC with AV legislation or executive orders (and AVs probably can operate in most states without law changes) 4 2 10/27/2017 NCSL October 2017 www.ghsa.org @GHSAHQ 5 But … • It’s far more complicated than that 6 3 10/27/2017 What’s an AV? • Level 0: no automation, driver in complete control • Level 1: driver assistance . Cruise control or lane position, driver monitors at all times • Level 2: occasional self-driving . Control both speed and lane position in limited situations, like Interstates; driver monitors at all times ************** • Level 3: limited self-driving in some situations, like Interstates . Vehicle in full control, informs when driver must take control • Level 4: full self-driving under certain conditions . Vehicle in full control for entire trip, such as urban ride-sharing • Level 5: full self-driving at all times 7 What’s on the road now? • Level 1 available for many years . -
3.17.2020 Request for Feedback on AV Legislation Staff Draft Sections
TO: Majority and Minority Staff of Senate Commerce, Science, and Transportation Committee and House Energy and Commerce Committee FROM: Advocates for Highway and Auto Safety, Consumer Federation of America, KidsAndCars.org, and Trauma Foundation DATE: March 17, 2020 RE: Request for Input on Draft Autonomous Vehicle Legislative Language Introduction Thank you for the opportunity to provide feedback to the final seven sections of potential autonomous vehicle (AV) legislation. Please note that in the attached redlined draft legislative language, there may be additional recommendations not necessarily included in this memo. Similarly, in this memo we detail concerns which may not be directly attached to the redlined legislative language as well as provide justifications for changes we did redline. As you have announced that you have completed the distribution of draft legislative sections, we would like to reiterate that stakeholder feedback should be shared publicly to provide transparency and the opportunity for collaboration as well as the identification of shared policy priorities in order to forge a path forward on the Nation’s first AV law. Because this law will have long-lasting and wide-reaching impacts on safety for all road users, infrastructure, mobility, accessibility, the environment and land use, public transit, first responders and law enforcement, it must be done with robust discussion, debate and deliberation. We would like to begin by reiterating our safety priorities and policy positions that are also included in more detail in our previous memos. They remain relevant and vital in developing any legislation on AVs. In sum, they are: • Our Nation’s first law on AVs must ensure the safe development and deployment of all AVs, including partially automated vehicles whether for sale or use as a pay-for mobility option. -
In the Court of Chancery of the State of Delaware
EFiled: Sep 06 2016 07:12PM EDT Transaction ID 59520160 Case No. 12723- IN THE COURT OF CHANCERY OF THE STATE OF DELAWARE ELLEN PRASINOS, derivatively on behalf ) TESLA MOTORS, INC., ) ) Plaintiff, ) ) vs. ) ) C.A. No. ELON MUSK, BRAD W. BUSS, ROBYN ) M. DENHOLM, IRA EHRENPREIS, ) ANTONIO J. GRACIAS, STEPHEN T. ) JURVETSON, KIMBAL MUSK, ) LYNDON RIVE, PETER RIVE, JOHN H. ) N. FISHER, JEFFREY B. STRAUBEL, D ) SUBSIDIARY, INC., AND SOLARCITY ) CORPORATION, ) ) Defendants, ) ) -and- ) ) TESLA MOTORS, INC., a Delaware ) Corporation, ) ) Nominal Defendant ) VERIFIED STOCKHOLDER DERIVATIVE COMPLAINT Plaintiff Ellen Prasinos (“Plaintiff”), by and through her undersigned counsel, assert this action derivatively on behalf of Tesla Motors, Inc. (“Telsa” or the “Company”) against defendants Elon Musk, Brad W. Buss, Robyn M. Denholm, Ira Ehrenpreis, Antonio J. Gracias, Stephen T. Jurvetson and Kimbal Musk (collectively, the “Board” or the “Director Defendants”), along with Lyndon Rive, Peter Rive, John H. N. Fisher, J.B. Straubel, D Subsidiary, Inc., and 1 ME1 23271632v.1 SolarCity Corporation (“SolarCity”). Plaintiff alleges, upon information and belief based upon, inter alia , the investigation made by her attorneys, except as to those allegations that pertain to the Plaintiff herself, which are alleged upon knowledge, as follows: SUMMARY OF THE ACTION 1. Elon Musk (“Musk”), a smart and charismatic businessman, wants to save the world by “making life multi-planetary”, and “expedit[ing] the move from a mine-and-burn hydrocarbon economy towards a solar electric economy.” While Musk’s goal to save the world may be admirable, he uses unethical and illegal tactics to achieve that goal, especially when his personal financial interests and legacy are at stake. -
AN ADVANCED VISION SYSTEM for GROUND VEHICLES Ernst
AN ADVANCED VISION SYSTEM FOR GROUND VEHICLES Ernst Dieter Dickmanns UniBw Munich, LRT, Institut fuer Systemdynamik und Flugmechanik D-85577 Neubiberg, Germany ABSTRACT where is it relative to me and how does it move? (VT2) 3. What is the likely future motion and (for subjects) intention of the object/subject tracked? (VT3). These ‘Expectation-based, Multi-focal, Saccadic’ (EMS) vision vision tasks have to be solved by different methods and on has been developed over the last six years based on the 4- different time scales in order to be efficient. Also the D approach to dynamic vision. It is conceived around a fields of view required for answering the first two ‘Multi-focal, active / reactive Vehicle Eye’ (MarVEye) questions are quite different. Question 3 may be answered with active gaze control for a set of three to four more efficiently by building on the results of many conventional TV-cameras mounted fix relative to each specific processes answering question 2, than by resorting other on a pointing platform. This arrangement allows to image data directly. both a wide simultaneous field of view (> ~ 100°) with a Vision systems for a wider spectrum of tasks in central region of overlap for stereo interpretation and high ground vehicle guidance have been addresses by a few resolution in a central ‘foveal’ field of view from one or groups only. The Robotics Institute of Carnegie Mellon two tele-cameras. Perceptual and behavioral capabilities University (CMU) [1-6] and DaimlerChrysler Research in are now explicitly represented in the system for improved Stuttgart/Ulm [7-12] (together with several university flexibility and growth potential. -
An Introduction of Autonomous Vehicles and a Brief Survey
Journal of Critical Reviews ISSN- 2394-5125 Vol 7, Issue 13, 2020 AN INTRODUCTION OF AUTONOMOUS VEHICLES AND A BRIEF SURVEY 1Tirumalapudi Raviteja, 2Rajay Vedaraj I.S 1Research Scholar, School of Mechanical Engineering, Vellore instutite of technology, Tamilnadu, India, Email: [email protected] . 2Professor, School of Mechanical Engineering, Vellore instutite of technology, Tamilnadu, India, Email: [email protected] Received: 09.04.2020 Revised: 10.05.2020 Accepted: 06.06.2020 Abstract: An autonomous car is also called a self-driving car or driverless car or robotic car. Whatever the name but the aim of the technology is the same. Down the memory line, autonomous vehicle technology experiments started in 1920 only and controlled by radio technology. Later on, trails began in 1950. From the past few years, updating automation technology day by day and using all aspects of using in regular human life. The present scenario of human beings is addicted to automation and robotics technology using like agriculture, medical, transportation, automobile and manufacturing industries, IT sector, etc. For the last ten years, the automobile industry came forward to researching autonomous vehicle technology (Waymo Google, Uber, Tesla, Renault, Toyota, Audi, Volvo, Mercedes-Benz, General Motors, Nissan, Bosch, and Continental's autonomous vehicle, etc.). Level-3 Autonomous cars came out in 2020. Everyday autonomous vehicle technology researchers are solving challenges. In the future, without human help, robots will manufacture autonomous cars using IoT technology based on customer requirements and prefer these vehicles are very safe and comfortable in transportation systems like human traveling or cargo. Autonomous vehicles need data and updating continuously, so in this case, IoT and Artificial intelligence help to share the information device to the device. -
Assessing the Sustainability Implications of Autonomous Vehicles: Recommendations for Research Community Practice
sustainability Review Assessing the Sustainability Implications of Autonomous Vehicles: Recommendations for Research Community Practice Eric Williams 1,*, Vivekananda Das 1 and Andrew Fisher 2 1 Golisano Institute for Sustainability, Rochester Institute of Technology, Rochester, NY 14623, USA; [email protected] 2 Environmental Resources Management, Fairport, NY 14450, USA; [email protected] * Correspondence: [email protected] Received: 3 February 2020; Accepted: 25 February 2020; Published: 3 March 2020 Abstract: Autonomous vehicles (AV) are poised to induce disruptive changes, with significant implications for the economy, the environment, and society. This article reviews prior research on AVs and society, and articulates future needs. Research to assess future societal change induced by AVs has grown dramatically in recent years. The critical challenge in assessing the societal implications of AVs is forecasting how consumers and businesses will use them. Researchers are predicting the future use of AVs by consumers through stated preference surveys, finding analogs in current behaviors, utility optimization models, and/or staging empirical “AV-equivalent” experiments. While progress is being made, it is important to recognize that potential behavioral change induced by AVs is massive in scope and that forecasts are difficult to validate. For example, AVs could result in many consumers abandoning private vehicles for ride-share services, vastly increased travel by minors, the elderly and other groups unable to drive, and/or increased recreation and commute miles driven due to increased utility of in-vehicle time. We argue that significantly increased efforts are needed from the AVs and society research community to ensure 1) the important behavioral changes are analyzed and 2) models are explicitly evaluated to characterize and reduce uncertainty. -
Introducing Driverless Cars to UK Roads
Introducing Driverless Cars to UK Roads WORK PACKAGE 5.1 Deliverable D1 Understanding the Socioeconomic Adoption Scenarios for Autonomous Vehicles: A Literature Review Ben Clark Graham Parkhurst Miriam Ricci June 2016 Preferred Citation: Clark, B., Parkhurst, G. and Ricci, M. (2016) Understanding the Socioeconomic Adoption Scenarios for Autonomous Vehicles: A Literature Review. Project Report. University of the West of England, Bristol. Available from: http://eprints.uwe.ac.uk/29134 Centre for Transport & Society Department of Geography and Environmental Management University of the West of England Bristol BS16 1QY UK Email enquiries to [email protected] VENTURER: Introducing driverless cars to UK roads Contents 1 INTRODUCTION .............................................................................................................................................. 2 2 A HISTORY OF AUTONOMOUS VEHICLES ................................................................................................ 2 3 THEORETICAL PERSPECTIVES ON THE ADOPTION OF AVS ............................................................... 4 3.1 THE MULTI-LEVEL PERSPECTIVE AND SOCIO-TECHNICAL TRANSITIONS ............................................................ 4 3.2 THE TECHNOLOGY ACCEPTANCE MODEL ........................................................................................................ 8 3.3 SUMMARY ................................................................................................................................................... -
Perception, Planning, Control, and Coordination for Autonomous Vehicles
machines Article Perception, Planning, Control, and Coordination for Autonomous Vehicles Scott Drew Pendleton 1,*, Hans Andersen 1, Xinxin Du 2, Xiaotong Shen 2, Malika Meghjani 2, You Hong Eng 2, Daniela Rus 3 and Marcelo H. Ang Jr. 1 1 Department of Mechanical Engineering, National University of Singapore, Singapore 119077, Singapore; [email protected] (H.A.); [email protected] (M.H.A.J.) 2 Future Urban Mobility, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; [email protected] (X.D.); [email protected] (X.S.); [email protected] (M.M.); [email protected] (Y.H.E.) 3 Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; [email protected] * Correspondence: [email protected] Academic Editor: Robert Parkin Received: 3 January 2017; Accepted: 13 February 2017; Published: 17 February 2017 Abstract: Autonomous vehicles are expected to play a key role in the future of urban transportation systems, as they offer potential for additional safety, increased productivity, greater accessibility, better road efficiency, and positive impact on the environment. Research in autonomous systems has seen dramatic advances in recent years, due to the increases in available computing power and reduced cost in sensing and computing technologies, resulting in maturing technological readiness level of fully autonomous vehicles. The objective of this paper is to provide a general overview of the recent developments in the realm of autonomous vehicle software systems. Fundamental components of autonomous vehicle software are reviewed, and recent developments in each area are discussed. -
Autonomous Vehicle Technology: a Guide for Policymakers
Autonomous Vehicle Technology A Guide for Policymakers James M. Anderson, Nidhi Kalra, Karlyn D. Stanley, Paul Sorensen, Constantine Samaras, Oluwatobi A. Oluwatola C O R P O R A T I O N For more information on this publication, visit www.rand.org/t/rr443-2 This revised edition incorporates minor editorial changes. Library of Congress Cataloging-in-Publication Data is available for this publication. ISBN: 978-0-8330-8398-2 Published by the RAND Corporation, Santa Monica, Calif. © Copyright 2016 RAND Corporation R® is a registered trademark. Cover image: Advertisement from 1957 for “America’s Independent Electric Light and Power Companies” (art by H. Miller). Text with original: “ELECTRICITY MAY BE THE DRIVER. One day your car may speed along an electric super-highway, its speed and steering automatically controlled by electronic devices embedded in the road. Highways will be made safe—by electricity! No traffic jams…no collisions…no driver fatigue.” Limited Print and Electronic Distribution Rights This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited. Permission is given to duplicate this document for personal use only, as long as it is unaltered and complete. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial use. For information on reprint and linking permissions, please visit www.rand.org/pubs/permissions.html. The RAND Corporation is a research organization that develops solutions to public policy challenges to help make communities throughout the world safer and more secure, healthier and more prosperous. -
Connected and Automated Vehicles: the Long and Winding Road Glenn N
Connected and Automated Vehicles: The Long and Winding Road Glenn N. Havinoviski, PE Iteris, Inc. © 2016 Iteris, Inc. All rights reserved. © 2016 Iteris, Inc. All rights reserved. Overview • Historical Perspective • Yes, It’s Really Happening • What are the Impacts? • Where We are Headed 2 © 2016 Iteris, Inc. All rights reserved. March 6, 2018 Historical Perspective 3 © 2016 Iteris, Inc. All rights reserved. March 6, 2018 Historical Perspective 4 © 2016 Iteris, Inc. All rights reserved. Timeline to Automation • 1939 – NY World’s Fair Demo by GM • 1945 – First Cruise Control • 1950-60s – RCA and GM test automated highways (guide by wire) • 1960s-80s – Assorted tests and vehicle sensor tests, led by Japan / Europe 5 © 2016 Iteris, Inc. All rights reserved. March 6, 2018 Automated Highway System Demo (1997) • ISTEA (1991) authorized National Automated Highway System Consortium • Focus on safety, efficiency, throughput • 7.6 mile corridor in San Diego (I-15) • On-vehicle sensors tracked lane guidance markers, supported adaptive But…… cruise control, collision avoidance Clear outcome was not defined! • Limited testing of automated bus 6 © 2016 Iteris, Inc. All rights reserved. Setting the stage (2000s) • Main USDOT focus “Connected Vehicles” (vehicle-to- infrastructure, vehicle-to-vehicle communications) using 5.9 GHz DSRC • Research initiatives addressed AV’s for military and urban use (not using V2V or V2I) o Carnegie-Mellon Navlab (1995) o DARPA Challenge (2004, 2005, 2007) KAT-5 (2005) o Team behind 2005 winner developed Google (now Waymo) Gray Insurance (Metairie, LA) & Car Tulane University • High-definition mapping, real-time updates a core element of AV’s (and a link to concept of CV’s) 7 © 2016 Iteris, Inc.