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Author Dalgleish, Michael
Title Highway Traffic Monitoring and Data Quality
Imprint Norwood : Artech House, 2008
©2008
book jacket
Descript 1 online resource (262 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Note Highway Traffic Monitoring and Data Quality -- Contents -- Foreword -- Introduction -- 1 Applications of Traffic Data -- 1.1 Introduction -- 1.2 A City Center Congestion-Reduction Scheme -- 1.3 Traffic Control Centers -- 1.4 Urban Area Speed-Reduction Scheme -- 1.5 Motorway Accident Reduction System -- 1.6 Increasing the Capacity of a Motorway by Speed Control -- 1.7 Increasing the Capacity of a Motorway by Lane Control -- 1.8 Increasing the Capacity of a Motorway by Access Control -- 1.9 Transport Modeling and Forecasting -- 1.10 Traffic Regulation Enforcement -- 1.11 Private Finance Initiative Payment Mechanisms -- 1.12 Summary -- Reference -- 2 Statistical Essentials -- 2.1 Introduction -- 2.2 Why Are Statistics Necessary? -- 2.3 The Normal Distribution -- 2.4 Mean -- 2.5 Standard Deviation -- 2.6 Central Limit Theorem -- 2.7 Standard Deviation of the Sample Means -- 2.8 Illustrating the Distribution of Sample Me -- 2.9 Confidence Interval of the Mean -- 2.10 Minimum Sample Size When Finding the Mean for Quantitative Data -- 2.11 More about Confidence Intervals -- 2.12 Confidence Interval of Individual Reports -- 2.13 Expression of Results -- 2.14 Probability Distributions -- 2.15 Summary -- 3 Errors in Traffic Data -- 3.1 Introduction -- 3.2 Errors in Traffic Data -- 3.2.1 Types of Errors -- 3.2.2 Truth, Ground Truth, and True Value -- 3.2.3 Accepted Reference Value -- 3.2.4 Common Causes of Errors -- 3.2.5 Error Versus Uncertainty -- 3.2.6 Errors Must Be Quantifi ed by Survey -- 3.2.7 Empirical Versus Theoretical Methods -- 3.2.8 Combination of Bias or Systematic Errors -- 3.2.9 Combination of Absolute Random Errors -- 3.2.10 Combination of Standard Deviation-Type Random Errors -- 3.3 Quantifying the Size of Errors -- 3.3.1 Mean Error -- 3.3.2 Confidence Limits of the Mean Er -- 3.4 Limitations -- 3.5 Overcount Errors in Vehicle Detectors
3.6 Undercount Errors in Vehicle Detectors -- 3.7 Axle Detector Errors -- 3.8 Data for Miscount Assessment -- 3.9 Data Collection Examples from the Three Methods -- 3.9.1 Mean Error Rate -- 3.9.2 Confidence Interval of the Mean -- 3.10 Different Types of Statistical Data -- 3.10.1 Confidence Interval of the Mean Using Multiple-Sample Data -- 3.10.2 Confidence Interval of the Mean Error Using Categorical Analysis -- 3.10.3 Continuous Sampling Method -- 3.10.4 Poisson Distribution Method -- 3.10.5 Binomial Distribution Method -- 3.10.6 Summary of Categorical Analysis -- 3.11 Confidence Interval of the Mean Using the Total Count Assuming a K Ratio -- 3.11.1 Theoretical Basis -- 3.11.2 Example Calculation -- 3.12 Confidence Interval of the Mean Using the Total Count Assuming P or M to Be Zero -- 3.12.1 Derivation of the Formula When P or M Is Zero -- 3.12.2 Example Calculation -- 3.13 Discussion of Confidence Interval of the Mean Methods -- 3.13.1 Multiple-Sample (Attribute-Based) Method -- 3.13.2 Total Count Using P and M Counts -- 3.13.3 Total Count Assuming P/M Ratio Method -- 3.13.4 Total Count Assuming P or M Zero Method -- 3.14 Sample Size for a Given Confidence Interval of the Mean -- 3.14.1 Minimum Sample Size Using Multiple-Sample (Attribute) Approach -- 3.14.2 Minimum Sample Size Using P and M and the Binomial Distribution -- 3.14.3 Minimum Sample Size Using the P/M Ratio Method -- 3.14.4 Minimum Sample Size Assuming Either P or M Is Equal to Zero -- 3.15 Comparison of the Four Minimum Sample Size Results -- 3.16 Sources of Error -- 3.16.1 Manual Enumeration -- 3.16.2 Typical Blunders -- 3.16.3 Equipment Parameter Settings -- 3.16.4 Loop Detector Error Sources -- 3.16.5 Errors in Length Measurement Using Loops -- 3.16.6 Tube Detector Error Sources -- 3.16.7 Microwave Sensor Error Sources -- 3.16.8 Number Plate Reader Error Sources
3.16.9 Bias in Number Plate Readers -- 3.17 Meaning of Capability -- 3.18 Relevance of Quality Assurance -- 3.19 Summary -- 4 Accuracy Assessments -- 4.1 Introduction -- 4.2 Interval Counting Variance -- 4.3 Confidence Interval for Individual Counts -- 4.4 Calculating the Confidence Interval for Different Periods -- 4.5 Some Words about Systematic Error -- 4.6 Even-Probability Accuracy Test -- 4.7 Two-Sigma Probability Accuracy Test -- 4.8 Three-Sigma Probability Accuracy Test -- 4.9 Discussion of the Tests -- 4.10 Additional Conditions to the Basic Tests -- 4.11 Restricted Mean -- 4.12 Zero Included in Range -- 4.13 Sample Size Trap -- 4.14 Random Error Trap -- 4.15 Test Failure Options -- 4.16 One-Sided Accuracy Requirements -- 4.17 Minimizing Sample Size by Combining Mean and CIM Data -- 4.17.1 Minimum Multiple Sample for Determining Accuracy within Specification -- 4.17.2 Minimum P and M Sample for Determining Accuracy within Specification -- 4.17.3 K Ratio and P or M Equal to Zero Minimum Sample Size -- 4.18 Semiautomated Minimum Sample Sizing -- 4.19 Accuracy Test Failures -- 4.20 Calibration -- 4.20.1 An Example of Calibration for Vehicle Length -- 5 Collecting Data in Groups -- 5.1 Introduction -- 5.2 Binning Error Basics -- 5.3 Direct Observation Method -- 5.3.1 Methodology Using Length Bins -- 5.3.2 Pros and Cons -- 5.4 Distributions Analysis Method -- 5.4.1 Measurement Error Distribution -- 5.4.2 Parameter Distribution -- 5.4.3 Combining Measurement Error Distribution and Parameter Distribution -- 5.4.4 Example Using Measurement SD of 6 kph and 100 kph Bin Bound -- 5.4.5 Repeated Example Using Measurement SD of 3 kph Instead of 6 kph -- 5.4.6 Bin Proportions -- 5.4.7 Pros and Cons -- References -- 6 Availability and Reliability -- 6.1 Introduction -- 6.2 Defining Availability -- 6.3 Specified Performance Level -- 6.4 Equipment Failure
6.5 Availability Blunders and Intermittent Faults -- 6.6 Typical Equipment Failure Rates -- 6.7 Monitoring MTBF -- 6.8 Annual Actions with Respect to Availability -- 7 Sampling -- 7.1 Introduction -- 7.2 Simple Random Sampling -- 7.3 Stratified Random Sampling -- 7.3.1 Time -- 7.3.2 Flow, Speed, and Density -- 7.3.3 Environment -- 7.4 1-in-k Systematic Random Sampling -- 7.5 Popular Sampling Plans -- 7.6 Environmental Aspects for Vision-Based Systems -- 7.7 Deliberately Biased Sampling -- 7.8 Sample Size Considerations -- 8 Validation and Verification -- 8.1 Introduction -- 8.2 Online Validation -- 8.3 Verification -- 8.4 Assessment Output -- 8.5 Manual Verification -- 8.5.1 Verification for Audit -- 8.5.2 Process -- 8.5.3 Enumeration -- 8.5.4 Enumerator Decisions -- 8.5.5 Multiple Enumerations -- 8.5.6 Vehicle Length -- 8.5.7 Conditions of Work -- 8.6 Historic Data Validation and Patching -- 8.6.1 Data Validation -- 8.6.2 Manual Data Validation -- 8.6.3 Automatic Data Validation -- 8.6.4 Data Value Window -- 8.6.5 Data Patching -- 8.6.6 Patching of Count-and-Classify Data -- 8.6.7 Patching of Loop-Based Speed Measurement Data -- 8.6.8 Patching of ANPR-Based Speed Measurement Data -- Reference -- 9 Traffic Monitoring Technologies -- 9.1 Introduction -- 9.2 Traffic Monitoring Stations, Sites, and Equipment -- 9.3 Measurement Types -- 9.3.1 Traffic Data Types -- 9.4 Typical Traffic Monitoring Sensing Devices -- 9.4.1 Axle Detectors -- 9.4.2 Inductive Loops -- 9.4.3 Above Ground Detectors -- 9.4.4 Image Processing -- 10 Detector Occupancy -- 10.1 Introduction -- 10.2 Occupancy Rate Error Assessment Methods -- 10.3 Occupancy Error Rate -- 10.4 Video Frame Count Method -- 10.5 Confidence Interval for Individual Sample Period Intervals -- 10.6 Confi dence Limits for the Mean Occupancy -- 10.7 Other Occupancy Time Periods -- 11 Speed
11.1 Definition of Speed -- 11.2 Measurement Methods -- 11.3 Calibration and Rounding -- 11.4 Determining the Accepted Reference Values for Speed -- 11.5 Key ARV Methods for Portable/Temporary Use -- 11.6 Speed Gun Technology -- 11.6.1 Speed Gun Measurement Rounding Down -- 11.6.2 Cosine Effect -- 11.6.3 Speed Gun Manufacturers -- 11.6.4 Assessment Using a Speed Gun -- 11.6.5 An Example of the Speed Gun Method -- 11.7 Deducting Speed Gun Error from a System under Test Data -- 11.8 Confidence Interval for the Mean Speed Error -- 11.9 Confidence Interval for Individual Vehicle Speed Reports -- 11.10 Calibrated Vehicle Method of Speed Assessment -- 11.11 Redundant Station Method of Speed Assessment -- 11.12 Using an Axle Switch for a Speed Reference -- 11.13 Minimum Sample Size for a Given Uncertainty in the Mean Error -- 11.14 Minimum Sample Size to Show Accuracy Compliance -- 11.15 Linearity of Speed Measurement -- 12 Length -- 12.1 Definition of Length -- 12.2 Using Loops to Measure Length -- 12.3 Determining the Accepted Reference Values for Length -- 12.4 Maker's Information Method -- 12.4.1 Example of the Maker's Information Method -- 12.5 Confidence Interval for Individual Vehicle Length Errors -- 12.6 Confidence Interval for the Population Mean Length -- 12.7 Other Matters -- 13 Vehicle Classification -- 13.1 Introduction -- 13.2 Theory of Operation -- 13.3 Causes of Vehicle Type Classification Error -- 13.4 Vehicle Type Error Assessment Methods -- 13.5 Video Overlay Methodology -- 13.6 Confidence Interval for Individual Class Counts (Class 1 Example) -- 13.7 Confidence Interval for All Class Counts (Class 1 Example) -- 13.8 Systematic Error in Vehicle Type Classifiers -- 13.9 Aggregate Classification Error Rate Calculation -- 14 Vehicle Weight -- 14.1 Introduction -- 14.2 Assessment Methods -- 14.3 Effect of Speed Calibration-Important
14.4 Weighing the Assessment Vehicles
This unique resource gives you a hands-on understanding of the latest sensors, processors, and communication links for everything from vehicle counts to urban congestion measurement. Moreover, you learn statistical techniques for quantifying data accuracy and reducing uncertainty in both current system state assessments and future system state forecasts
Description based on publisher supplied metadata and other sources
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2020. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
Link Print version: Dalgleish, Michael Highway Traffic Monitoring and Data Quality Norwood : Artech House,c2008 9781580537155
Subject Traffic monitoring -- Data processing -- Evaluation.;Traffic monitoring -- Data processing.;Vehicle detectors -- Evaluation.;Vehicle detectors
Electronic books
Alt Author Hoose, Neil
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