Table Of Content

Big Data Analytics for Connected Vehicles and Smart Cities For a complete listing of titles in the Artech House Power Engineering Series, turn to the back of this book. Big Data Analytics for Connected Vehicles and Smart Cities Bob McQueen Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the U.S. Library of Congress. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library. Cover design by John Gomes ISBN 13: 978-1-63081-321-5 © 2017 ARTECH HOUSE 685 Canton Street Norwood, MA 02062 All rights reserved. Printed and bound in the United States of America. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without permission in writing from the publisher. All terms mentioned in this book that are known to be trademarks or service marks have been appropriately capitalized. Artech House cannot attest to the accuracy of this information. Use of a term in this book should not be regarded as affecting the validity of any trademark or service mark. 10 9 8 7 6 5 4 3 2 1 Contents Preface xv 1 Introduction 1 1.1 Introduction 1 1.2 Informational Objectives of This Chapter 1 1.3 Chapter Word Cloud 2 1.4 Background 2 1.5 Why This Subject and Why Now? 4 1.6 Intended Readership Groups for the Book 5 1.7 Overview of Contents 6 References 12 2 Questions to Be Addressed 13 2.1 Informational Objectives of This Chapter 13 2.2 Chapter Word Cloud 13 2.3 Introduction 13 v vi Big Data Analytics for Connected Vehicles and Smart Cities Contents vii 2.4 Questions Instead of Answers 15 2.5 Overview of the Questions 15 2.6 Safety-Related Questions 20 2.7 Efficiency-Related Questions 21 2.8 User Experience-Related Questions 27 2.9 What Do We Do with the Questions? 29 References 29 3 What Is Big Data? 31 3.1 Informational Objectives of This Chapter 31 3.2 Chapter Word Cloud 31 3.3 Introduction 31 3.4 How Is Big Data Measured? 32 3.5 What Is Big Data? 33 3.6 Challenges 42 3.7 Big Data in Transportation 46 3.8 Transportation Systems Management and Operations 51 References 53 4 Connected and Autonomous Vehicles 55 4.1 Informational Objectives 55 4.2 Chapter Word Cloud 55 4.3 Introduction 56 4.4 What Is a Connected Vehicle? 58 4.5 Connected Vehicle Challenges 60 4.6 What Is an Autonomous Vehicle? 67 vi Big Data Analytics for Connected Vehicles and Smart Cities Contents vii 4.7 Autonomous Vehicle Challenges 69 4.8 Summary of the Differences between Connected and Autonomous Vehicles 72 4.8 Connected and Autonomous Vehicles within a Smart City 73 4.9 The Likely Impact of the Connected and the Autonomous Vehicle on Transportation 74 4.10 Big Data and Connectivity 75 4.11 Connected and Autonomous Vehicles within a Smart City 75 4.12 The Likely Effect of Connected and Autonomous Vehicles on the Automotive Industry 77 4.13 Summary 79 References 80 5 Smart Cities 81 5.1 Informational Objectives 81 5.2 Chapter Word Cloud 81 5.3 Introduction 81 5.4 What Is a Smart City? 83 5.5 Smart City Objectives 91 5.6 Steps Toward a Smart City 92 5.7 Smart City Frameworks 98 5.8 Evaluating the Effects of Investments 104 5.9 Smart City Challenges 104 5.10 Smart City Opportunities 106 5.11 Lessons Learned from the London Congestion Charge Project 108 viii Big Data Analytics for Connected Vehicles and Smart Cities Contents ix 5.12 The Sentient City 113 5.13 Summary 114 References 114 6 What Are Analytics? 117 6.1 Informational Objectives 117 6.2 Introduction 117 6.3 Chapter Word Cloud 118 6.4 What Is an Analytic? 119 6.5 Why Analytics Are Valuable 120 6.6 Smart City Services Analytics 122 6.7 Analytical Performance Management for a Smart City 132 6.8 How Do Analytics and Data Lakes Fit Together? 133 6.9 How to Identify Data Needs Associated with Analytics 134 6.10 Summary 134 References 135 7 The Practical Application of Analytics to Transportation 137 7.1 Informational Objectives of This Chapter 137 7.2 Chapter Word Cloud 138 7.3 Introduction 138 7.4 Integrated Payment Systems—What Are They? 139 7.5 Why Does Integrated Payment Make a Good Departure Point for a Smart City? 140 7.6 Integrated Payment System Analytics and Their Practical Application 141 7.7 MaaS—What Is It? 141 viii Big Data Analytics for Connected Vehicles and Smart Cities Contents ix 7.8 Why Does MaaS Make a Good Departure Point for a Smart City? 144 7.9 MaaS Analytics and Their Practical Application 144 7.10 Traffic Management—What Is It? 144 7.11 Why Does Traffic Management Make a Good Departure Point for a Smart City? 146 7.12 Traffic Management Analytics and Their Practical Application 146 7.13 Transit Management—What Is It? 146 7.14 Why Does Transit Management Make a Good Departure Point for a Smart City? 148 7.15 Transit Management Analytics and Their Practical Application 149 7.16 Performance Management—What Is It? 149 7.17 Why Does Performance Management Make a Good Departure Point for a Smart City? 151 7.18 Performance Management Analytics and Their Practical Application 151 7.19 Summary 152 References 154 8 Transportation Use Cases 155 8.1 Informational Objectives of This Chapter 155 8.2 Chapter Word Cloud 155 8.3 Introduction 156 8.4 What Is a Use Case? 157 8.5 Smart City Transportation Use Case Examples 158 8.6 Summary 160 References 161