Connected and Automated Vehicles: the Long and Winding Road Glenn N
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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 -
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. -
Towards Autonomous Vehicles Report # MATC-UI
Report # MATC-UI: 117 Final Report 25-1121-0003-117 Towards Autonomous Vehicles ® Chris Schwarz, Ph.D. Associate Research Engineer National Advanced Driving Simulator University of Iowa Geb Thomas, Ph.D. Associate Professor Kory Nelson, B.S. Student Michael McCrary, B.S. Student Nicholas Schlarmann Student Matthew Powell Student 2013 A Coopertative Research Project sponsored by U.S. Department of Tranportation-Research, Innovation and Technology Innovation Administration The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. This document is disseminated under the sponsorship of the Department of Transportation University Transportation Centers Program, in the interest of information exchange. The U.S. Government assumes no liability for the contents or use thereof. Towards Autonomous Vehicles Chris Schwarz, Ph.D. Michael McCrary, B.S. Associate Research Engineer Student National Advanced Driving Simulator Electrical and Computer Engineering The University of Iowa The University of Iowa Geb Thomas, Ph.D. Nicholas Schlarmann Associate Professor Student Mechanical and Industrial Engineering Department of Mathematics The University of Iowa The University of Iowa Kory Nelson, B.S. Matthew Powell Student Student Mechanical and Industrial Engineering Electrical and Computer Engineering The University of Iowa The University of Iowa A Report on Research Sponsored by Mid-America Transportation Center University of Nebraska–Lincoln December 2013 Technical Report Documentation Page 1. Report No. 2. Government Accession No. 3. Recipient's Catalog No. 25-1121-0003-117 4. Title and Subtitle 5. Report Date Towards Autonomous Vehicles November 2013 6. Performing Organization Code 7. Author(s) 8. -
Self-Driving Cars: a Survey Claudine Badue A,∗, Rânik Guidolini A, Raphael Vivacqua Carneiro A, Pedro Azevedo A, Vinicius B
Expert Systems With Applications 165 (2021) 113816 Contents lists available at ScienceDirect Expert Systems With Applications journal homepage: www.elsevier.com/locate/eswa Review Self-driving cars: A survey Claudine Badue a,<, Rânik Guidolini a, Raphael Vivacqua Carneiro a, Pedro Azevedo a, Vinicius B. Cardoso a, Avelino Forechi b, Luan Jesus a, Rodrigo Berriel a, Thiago M. Paixão c, Filipe Mutz c, Lucas de Paula Veronese a, Thiago Oliveira-Santos a, Alberto F. De Souza a a Departamento de Informática, Universidade Federal do Espírito Santo, Av. Fernando Ferrari 514, 29075-910, Goiabeiras, Vitória, Espírito Santo, Brazil b Coordenadoria de Engenharia Mecânica, Instituto Federal do Espírito Santo, Av. Morobá 248, 29192–733, Morobá, Aracruz, Espírito Santo, Brazil c Coordenadoria de Informática, Instituto Federal do Espírito Santo, ES-010 Km-6.5, 29173-087, Manguinhos, Serra, Espírito Santo, Brazil ARTICLEINFO ABSTRACT Keywords: We survey research on self-driving cars published in the literature focusing on autonomous cars developed Self-driving cars since the DARPA challenges, which are equipped with an autonomy system that can be categorized as SAE Robot localization level 3 or higher. The architecture of the autonomy system of self-driving cars is typically organized into Occupancy grid mapping the perception system and the decision-making system. The perception system is generally divided into many Road mapping subsystems responsible for tasks such as self-driving-car localization, static obstacles mapping, moving obstacles Moving objects detection Moving objects tracking detection and tracking, road mapping, traffic signalization detection and recognition, among others. The Traffic signalization detection decision-making system is commonly partitioned as well into many subsystems responsible for tasks such as Traffic signalization recognition route planning, path planning, behavior selection, motion planning, and control. -
Comparison Review on Autonomous Vehicles Vs Connected Vehicles
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 09 | Sep 2019 www.irjet.net p-ISSN: 2395-0072 Comparison Review on Autonomous vehicles vs Connected Vehicles Arun Kumar. N Mechanical Engineer, Anna University Chennai, Tamil Nadu, India ---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract – The automotive industry is expanding its technical From the 1960s through the second DARPA Grand Challenge innovations, in which the autonomous cars and connected cars in 2005, automated vehicle research in the U.S. was primarily are two major trends in automotive industry. The development funded by DARPA, the US Army, and the U.S. Navy, yielding of autonomous cars and connected cars is a revolution which incremental advances in speeds, driving competence in more will change the perspective of driving comfort and safety of the complex conditions, controls, and sensor systems. passengers. This paper is presented in order to give a Companies and research organizations have developed comparison review on autonomous cars vs connected cars. prototypes. Key Words: Autonomous car, Connected car, Driverless 1.2 TECHNICAL CHALLENGES vehicle, Connectivity, Self-driving car. There are different systems that help the self-driving car 1. AUTONOMOUS VEHICLES control the car. Systems that currently need improvement include the car navigation system, the location system, the A self-driving car, also known as an autonomous car, electronic map, the map matching, the global path planning, driverless car, or robotic car, is a vehicle that is capable of the environment perception, the laser perception, the radar sensing its environment and moving safely with little or no perception, the visual perception, the vehicle control, the human input [1]. -
Auto and Tech Companies – the Drive for Autonomous Vehicles
Chapter 3 Auto and tech companies – the drive for autonomous vehicles In 2004, the United States (U.S.) Defense The automobile industry has been envisioning self Department staged a novel off-road race in the driving2 or autonomous vehicles at least since General Mojave Desert. The novelty lay in it being open Motors presented its “Futurama” concept at the 1939 only to driverless or self-drive cars. First prize World’s Fair. Even in those early days, GM was not for winning the “Grand Challenge” over the the only one dreaming of a selfdriving future, and 240km course was $1 million. Nobody lifted the several attempts toward realization of AVs were made prize, because nobody finished the race.1 in subsequent years. But it is since the mid2000s that huge advances in robotics and, particularly, artificial But a year later, the Department’s Defense intelligence (AI)3 have begun to turn a longheld aspira Advanced Research Projects Agency (DARPA) tion into something closer to reality. staged the competition again and doubled the prize. It attracted dozens of entrants and this The AV industry is still in its infancy and fully autono time a number completed the course. The desert mous vehicles (Level 5) are years from reaching the race was won by “Stanley,” an autonomous market. Nevertheless, robotics and AI are already vehicle (AV) entered by Stanford University, with reshaping the car industry – so much so that new vehicles from Carnegie Mellon University (CMU) technologies are posing a significant existential threat taking second and third places. to the incumbent automakers. -
Urban Challenge
Developing a Self-Driving Car for the 2007 DARPA Urban Challenge Seth Teller CS and AI Laboratory EECS Department MIT Joint work with: Matt Antone, David Barrett, Mitch Berger, Bryt Bradley, Ryan Buckley, Stefan Campbell, Alexander Epstein, Gaston Fiore, Luke Fletcher, Emilio Frazzoli, Jonathan How, Albert Huang, Troy Jones, Sertac Karaman, Olivier Koch, Yoshi Kuwata, Victoria Landgraf, John Leonard, Keoni Maheloni, David Moore, Katy Moyer, Edwin Olson, Andrew Patrikalakis, Steve Peters, Stephen Proulx, Nicholas Roy, Chris Sanders, Justin Teo, Robert Truax, Matthew Walter, Jonathan Williams Urban Challenge (2007) • Novel elements: – Urban road network – Moving traffic • Human and robotic! – No course inspection – 60 miles in 6 hours • Scored by speed, safety • $3.5M prize pool – 89 entering teams Source: DARPA Urban Challenge • Program goals Participants Briefing, May 2006 – Safe (collision-free, polite) driving at up to 30mph – Capable (turns, stops, intersections, merging, parking, …) – Robust (blocked roads, erratic drivers, sparse waypoints, GPS degradation and outages, …) 23 Apr 2008 1 Program Scope • In scope: – Following -- Emergency stops – Intersections -- Timely left turns across traffic – Passing, Merging -- Potholes, construction sites – Parking, U-turns -- Blockages, replanning • Out of scope: – Pedestrians – High speed (> 30 mph) – Traffic signals, signage – Difficult off-road terrain – Highly inclement weather 23 Apr 2008 DARPA-Provided Inputs • USB stick w/ two files: • RNDF = Road Network Intersection not Description File called out in RNDF – Topology of road network – “Sparse” GPS waypoints – Parking zones Vehicle navigates roads with – Provided 48 hours ahead sparse waypoints • MDF = Mission Description – List of RNDF way-points to Sparse waypoints be visited by autonomous car on curved road – Provided 5 minutes ahead Source: DARPA Participants Briefing, May 2006 23 Apr 2008 2 Why tackle this problem? • Fatalities and injuries from driving accidents – Tens of thousands of fatalities per year in U.S. -
Autonomous Cars: Past, Present and Future
Autonomous Cars: Past, Present and Future A Review of the Developments in the Last Century, the Present Scenario and the Expected Future of Autonomous Vehicle Technology Keshav Bimbraw Mechanical Engineering Department, Thapar University, P.O. Box 32, Patiala, Punjab, India Keywords: Autonomous Cars, Autonomous Vehicles, Cars, Mechatronics Systems, Intelligent Transportation Technologies and Systems, Automation. Abstract: The field of autonomous automation is of interest to researchers, and much has been accomplished in this area, of which this paper presents a detailed chronology. This paper can help one understand the trends in autonomous vehicle technology for the past, present, and future. We see a drastic change in autonomous vehicle technology since 1920s, when the first radio controlled vehicles were designed. In the subsequent decades, we see fairly autonomous electric cars powered by embedded circuits in the roads. By 1960s, autonomous cars having similar electronic guide systems came into picture. 1980s saw vision guided autonomous vehicles, which was a major milestone in technology and till date we use similar or modified forms of vision and radio guided technologies. Various semi-autonomous features introduced in modern cars such as lane keeping, automatic braking and adaptive cruise control are based on such systems. Extensive network guided systems in conjunction with vision guided features is the future of autonomous vehicles. It is predicted that most companies will launch fully autonomous vehicles by the advent of next decade. The future of autonomous vehicles is an ambitious era of safe and comfortable transportation. 1 INTRODUCTION ‘Linriccan Wonder’. Significant advances in autonomous car technology has been made after the Consumers all around the whole world are enthusiastic advent of the vision guided Mercedes-Benz robotic about the advent of autonomous cars for public. -
Climate Change Issue
FALL 2020 The founders, investors, corporations, and policies helping solve CLIWe climate change. MATE can CHAN fix GEit. 06 A home for Tough Tech founders. The Engine, built by MIT, is a venture frm that invests in early-stage companies solving the world’s biggest problems through the convergence of breakthrough science, engineering, and leadership. Our mission is to accelerate the path to market for Tough Tech companies by providing access to a unique combination of investment, infrastructure, and a vibrant ecosystem. Tough Tech Publication 06 October,2020 The Engine, Built by MIT Edited & Produced by: Nathaniel Brewster Design: www.draft.cl Print by: Puritan Capital, NH & MA CONTENTS 04 Introduction 06 Cleantech’s Comeback 12 Thoughts on a Changing Climate 28 A Survey of Companies and Technologies 56 The Engine Portfolio Companies 76 The Engine Network 77 Tough Tech’s New Home INTRODUCTION A Climate of Hope In an era of great uncertainty, I remain optimistic. For every group of founders in which we invest, dozens of others are also pursuing solutions to challenges like climate change. | TOUGH TECH 06 4 Last month, as multiple hurricanes those at the forefront of the cleantech existential imperative of deploying barreled toward the Gulf Coast and revolution, recording their perspectives capital in cleantech startups as well wildfre spread unchecked through on the present and future of sustain- as the necessity of an infrastructure the West, the threat of climate change able technologies, climate policy, and to support technology and business became tangible for many Americans. investment. I suspect you will fnd their development as effciently as possible. -
Analýza Autonomních Vozidel
Analýza autonomních vozidel Petr Jedlička Lukáš Houska © Česká asociace pojišťoven, 2017, 2020 Obsah 4 Představení analýzy autonomních vozidel 6 1 Úvodem: Očekávané přínosy z autonomních vozidel 11 2 Technologický vývoj 18 3 Etické aspekty provozu autonomních vozidel 22 4 Zastoupení autonomních vozidel ve vozovém parku 27 5 Dopady na redukci rizika 34 6 Právní a další metodické aspekty budoucí odpovědnosti a fungování pojištění 53 7 Použité zdroje 56 Příloha 1: Technologický vývoj 81 Příloha 2: Zkratky spojené s asistenčními systémy Česká asociace pojišťoven 4 Analýza autonomních vozidel Představení analýzy autonomních vozidel Tento materiál se zabývá v poslední době často loautonomním vozidlům, která po většinu času diskutovaným fenoménem autonomních vozi- řídí již samostatně, řidič však musí být připraven del (která ke svému chodu nepotřebují řidiče). k převzetí řízení pro případ neočekávané (krizové) Na uvedené téma se dívá z celé řady úhlů pohledu situace. (technologie, etika, právo, dopady na pojištění…). Nejprve poukazuje na technologické inovace z mi- Třetí kapitola se zabývá etickými aspekty spoje- nulosti a dále na to, jak zásadní změnu mohou nými s autonomními vozidly, jež ovlivňují nasta- autonomní vozidla v budoucnu přinést, nejen co vení algoritmu autonomního řízení. Následující do redukce rizika. dvě kapitoly naznačují, jak se může změnit trh pojištění vozidel v důsledku postupného proniká- Na problematiku autonomních vozidel tento doku- ní vozidel s asistenčními systémy (automatizo- ment nahlíží důsledně evolučně, tj. rozlišuje mezi: vaná vozidla = zařízení umožňující automatické provádění některých operací řízení vozidla) přes ● vizí na konci vývoje, která je spojená s vozi- poloautonomní vozidla (většinu času řídí sama, dlem bez jakéhokoliv vlivu osoby na jeho řízení ale v krizových situacích je nutný zásah řidiče) a která se dá očekávat v horizontu desítek let, po (plně) autonomní vozidla (která provádějí v závislosti na výsledcích testování, schvalování všechny operace bez řidiče). -
Autonomous Driving and Related Technologies
Paper ID #26395 Autonomous Driving and Related Technologies Dr. Rendong Bai, Eastern Kentucky University Dr. Rendong Bai received his PhD degree in Computer Science from University of Kentucky in 2008. From 2007 to 2008, he worked at Eastern Kentucky University in the Department of Computer Science as a Visiting Assistant Professor. He was an Assistant/Associate Professor in the School of Technology at Eastern Illinois University from 2008 to 2018. In Fall 2018, he joined the Applied Engineering and Technology department at Eastern Kentucky University. His research interests include mobile comput- ing, server technology, network security, multimedia and web technologies, computer-aided design and manufacturing, quality management, and renewable energy. Dr. Wutthigrai Boonsuk, Eastern Illinois University Dr. Wutthigrai Boonsuk is an associate professor of Applied Engineering and Technology at Eastern Illi- nois University. He earned his master’s and doctorate degrees in Industrial and Manufacturing System Engineering from Iowa State University. Dr. Boonsuk also received his second master’s degree in Human Computer Interaction from the same university. His research interests include 3D stereoscopic applica- tions, Manufacturing Systems, Rapid Prototyping, Robotic and Controller Systems, Virtual Reality, and Geographic Information System (GIS). Dr. Boonsuk may be reached at [email protected] Peter P. Liu c American Society for Engineering Education, 2019 Autonomous Driving and Related Technologies Dr. Rendong Bai, Eastern Kentucky University, Richmond, KY 40475, 859-622- 1181, [email protected] Dr. Wutthigrai Boonsuk, Eastern Illinois University, Charleston, IL 61920, 217- 581-5772, [email protected] Dr. Peter Ping Liu, Eastern Illinois University, Charleston, IL 61920, 217-581- 6267, [email protected] Abstract We’re in the middle of a rapid evolution of the way vehicles are operated on road.