Highway Traffic Monitoring and Data Quality by Michael Dalgleish and Neil Hoose is one of a series of books published by Artech House on Intelligent Transport Systems. Among other things, it aims to ‘enable data technicians and managers to confidently estimate the uncertainty in their data and to quantify these using well-developed statistical techniques’. It meets this aim, providing a comprehensive introductory guideline on road vehicle data collection, analysis and interpretation for data technicians, students and data managers.
Dalgleish and Hoose correctly point to the enormous increase in vehicle data collected automatically and the need for analysts to understand the limitations of this data in order to interpret it correctly. Many traffic authorities are collecting and storing megabytes' worth of road vehicle data each day. The wealth of information in this data needs to be released and this book provides valuable assistance in this task.
The book contains 18 chapters that are contained in 207 pages. They take the reader through an introduction to some of the applications for traffic data, fundamental classical statistics, errors in road vehicle data, collection of data, measurement of fundamental vehicle parameters and data storage and conclude with some useful tips for people collecting and using data. The chapters on systematic and random errors, the verification and validation of data and the treatment of lost or missing data are particularly relevant to the main aim of this book.
Each chapter is concise and to the point. They do not cover all aspects associated with each area but introduce the main points in an interesting and readable fashion.
In such a short book there are clearly areas that are not covered in great detail. Some of these include: basic traffic flow theory, the interpretation of data using techniques such as exploratory data analysis, consideration of data other than interval parametric data, the testing of distributions other than normal, data-mining techniques as well as some areas of data collection such as weigh-in-motion, the measurement of pollutants and pedestrian traffic. The authors recognise this and focus each chapter on the key dimensions of the book.
Dalgleish and Hoose provide a bibliography of texts that will allow interested readers to follow up on particular areas of interest. Use of references in the book to the texts in the bibliography and further useful texts may be of assistance to readers should they wish to follow up particular areas of interest in more depth.
The book also includes appendices related to: Student's t distribution, glossary and abbreviations, information on the authors and a concise index. These are useful but could have been supplemented by a list of independent variables used in the statistical equations.
Highway Traffic Monitoring and Data Quality focuses mainly on the more common automatic measurement parameters of vehicles. These include vehicle flow, speed, length, type and weight. Many of the concerns and techniques outlined could equally well be applied to the rapidly developing area of monitoring people movement using global positioning systems, personal movement monitors and wireless communication systems.
In concluding this review, this book should be seen as a useful contribution to the growing need accurately to collect, understand and interpret the enormous data resources that are becoming available through developments in automated traffic data collection equipment.
