Highway Traffic Monitoring and Data Quality

263 Pages·2008·2.419 MB·English

by  Dalgleish, Michael, Hoose, Neil

Highway Traffic Monitoring and Data Quality
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Highway Traffic Monitoring and Data Quality
Michael Dalgleish
Neil Hoose
artechhouse.com
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Cover design by Yekaterina Ratner
ISBN 13: 978-1-59693-715-5
© 2008 Michael Dalgleish and Neil Hoose

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 pho-
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All terms mentioned in this book that are known to be trademarks or service marks have been
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10 9 8 7 6 5 4 3 2 1
To Maurice Watson
for helping the idea come to life

Contents
Foreword xix
Introduction xxi
1 Applications of Traffic Data 1
1.1 Introduction 1
1.2 A City Center Congestion-Reduction Scheme 2
1.3 Traffic Control Centers 3
1.4 Urban Area Speed-Reduction Scheme 6
1.5 Motorway Accident Reduction System 7
1.6 Increasing the Capacity of a Motorway by Speed Control 8
1.7 Increasing the Capacity of a Motorway by Lane Control 8
1.8 Increasing the Capacity of a Motorway by Access Control 9
1.9 Transport Modeling and Forecasting 10
1.10 Traffic Regulation Enforcement 10
1.11 Private Finance Initiative Payment Mechanisms 11
1.12 Summary 13
Reference 14
vii
viii Highway Traffic Monitoring and Data Quality Contents ix
2 Statistical Essentials 15
2.1 Introduction 15
2.2 Why Are Statistics Necessary? 16
2.3 The Normal Distribution 16
2.4 Mean 17
2.5 Standard Deviation 18
2.6 Central Limit Theorem 18
2.7 Standard Deviation of the Sample Means 19
2.8 Illustrating the Distribution of Sample Means 20
2.9 Confidence Interval of the Mean 20
2.10 Minimum Sample Size When Finding the Mean for
Quantitative Data 22
2.11 More about Confidence Intervals 23
2.12 Confidence Interval of Individual Reports 24
2.13 Expression of Results 26
2.14 Probability Distributions 27
2.15 Summary 28
3 Errors in Traffic Data 29
3.1 Introduction 29
3.2 Errors in Traffic Data 29
3.2.1 Types of Errors 29
3.2.2 Truth, Ground Truth, and True Value 30
3.2.3 Accepted Reference Value 30
3.2.4 Common Causes of Errors 31
3.2.5 Error Versus Uncertainty 32
3.2.6 Errors Must Be Quantified by Survey 33
3.2.7 Empirical Versus Theoretical Methods 33
3.2.8 Combination of Bias or Systematic Errors 34
3.2.9 Combination of Absolute Random Errors 34
3.2.10 Combination of Standard Deviation–Type Random Errors 34
viii Highway Traffic Monitoring and Data Quality Contents ix
3.3 Quantifying the Size of Errors 35
3.3.1 Mean Error 35
3.3.2 Confidence Limits of the Mean Error 36
3.4 Limitations 37
3.5 Overcount Errors in Vehicle Detectors 38
3.6 Undercount Errors in Vehicle Detectors 38
3.7 Axle Detector Errors 38
3.8 Data for Miscount Assessment 39
3.9 Data Collection Examples from the Three Methods 40
3.9.1 Mean Error Rate 41
3.9.2 Confidence Interval of the Mean 41
3.10 Different Types of Statistical Data 42
3.10.1 Confidence Interval of the Mean Using Multiple-Sample Data 43
3.10.2 Confidence Interval of the Mean Error Using Categorical
Analysis 43
3.10.3 Continuous Sampling Method 44
3.10.4 Poisson Distribution Method 45
3.10.5 Binomial Distribution Method 46
3.10.6 Summary of Categorical Analysis 47
3.10.7 Example Calculation 48
3.11 Confidence Interval of the Mean Using the Total Count
Assuming a K Ratio 48
3.11.1 Theoretical Basis 48
3.11.2 Example Calculation 50
3.12 Confidence Interval of the Mean Using the Total Count
Assuming P or M to Be Zero 50
3.12.1 Derivation of the Formula When P or M Is Zero 50
3.12.2 Example Calculation 52
3.13 Discussion of Confidence Interval of the Mean Methods 52
3.13.1 Multiple-Sample (Attribute-Based) Method 52
3.13.2 Total Count Using P and M Counts 53
3.13.3 Total Count Assuming P/M Ratio Method 53
3.13.4 Total Count Assuming P or M Zero Method 54