AP-G84/04 Best practice in road use data collection, analysis ... - WIM

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Accessed by AR - ARRB TRANSPORT RESEARCH on 04 Feb 2005 2 BEST PRACTICE PRINCIPLES Austroads 2004 — 2 — Best Practices in Road Use Data Collection, Analysis and Reporting This section provides a brief discussion on the principles of best practice. The aim is to provide a broad context in making recommendations in this report. These principles also relate to data integrity issues, which will be addressed in more detail in Section 6. They are as follows: Accuracy – This is a measure of how well the data collected represent true values. In traffic data, perfect accuracy is unnecessary and it is actually impossible to achieve. Consequently, it is good practice to quote a percentage error and the associated confidence level. A trade-off between accuracy with other quality criteria is also necessary – higher accuracy often implies higher cost. Effectiveness – This is the likelihood that a work program achieves desired objectives. It measures how closely outcomes match predefined targets. Efficiency – This is the ratio of output to input. A lot of output data with minimal input resources is an efficient data collection program. However, collecting the wrong data is an ineffective program irrespective of the amount of input resources involved. Reliability – This is related to accuracy. A counting program needs to produce consistent and repeatable results. Reliability is therefore an outcome of how well a road network is sampled or covered to produce statistically consistent data. Accessibility – Road use data should be easily accessible within a jurisdiction and to the public due to the Freedom of Information (FOI) Act, possibly not in the raw data form but in aggregated form. The data structure and formats should be amenable to data accessibility. Transparency – A clear enunciation of the procedures for collection, analysis and reporting should help reducing differences amongst RAs and other users in the use and interpretation of road use data. Timeliness – This relates to the frequency of data collection, its reporting and updates. A yearly update and reporting should be the minimal update period. With more and better database technologies, it is expected that road use data would become more timely in the near future. Relevance – The data collected should meet the needs of a user, i.e. should fulfil the principle of fitness of purpose. There is always a great need for traffic counts and weigh-inmotion (WIM) data. A current issue is what other types of data should be included in a comprehensive road use database. The above list is certainly not exhaustive but does cover most of the important elements in identifying best practices. These principles will be applied in the following sections to identify and recommend practices in the final road use data report. Further, a glossary of terms is included in Appendix A. The glossary is intended to be a ‘national glossary’ to promote consistency. It is recognised that individual jurisdictions would adopt slight variations in definitions and therefore practices due to constraints specific to a jurisdiction. Over time, the national glossary also requires updates and is a reference towards which jurisdictional practices would migrate.
Accessed by AR - ARRB TRANSPORT RESEARCH on 04 Feb 2005 3 VEHICLE DETECTION AND CLASSIFICATION Austroads 2004 — 3 — Best Practices in Road Use Data Collection, Analysis and Reporting The Austroads (1988a and 2004) Guide to Traffic Engineering Practice (GTEP) Part 3 on Traffic Studies provides a broad background to vehicle detection and classification and other traffic studies. Discussions on technologies such as image processing and Global Positioning System (GPS) will only be mentioned in passing in this report. The focus of this section is on getting the most out of currently used technologies, which are axle and inductive loop sensors. 3.1 Axle Sensor and Axle Counts The most common type of axle sensor is the pneumatic tube with an air switch. It is suitable in both urban and rural environments for temporary axle counts. Two tubes are usually needed for speed measurement and vehicle classification. A two-tube installation for vehicle classification on a local road is shown in Figure 1. The photograph shows the set-up for the monitoring of two lanes of vehicular traffic and a bicycle path on the near side of the photograph. Figure 1 – A pair of pneumatic tubes and a vehicle classifier on a local road monitoring two lanes of vehicle traffic and a bicycle path on the nearside of the photograph A single axle sensor has been found useful in a wide range of road traffic conditions. For single lane traffic, one axle sensor usually presents no problems in obtaining axle counts. At remote sites, single axle sensors are sometimes used in permanent count stations because they are reasonably reliable and repair costs at remote sites are expensive. For multi-lane traffic (in one or two directions), axle counts are missed when the wheels of two different vehicles arrive at an axle sensor at the same time. Installing two axle sensors could improve accuracy but the installation of two axle sensors also increase the Occupational Health and Safety (OH&S) risk.
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AP-G84/04 Best practice in road use data collection, analysis ... - WIM

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