Asset Management
- Publication no: AP-T161-10
- ISBN: 978-1-921709-38-8
- Published: 27 August 2010
- PDF (free) Download
This report looks at low-cost vehicle classifiers to provide some indication of pavement loading or gross vehicle mass (GVM). WIM equipment is relatively expensive to install and calibrate, and may not be easily installed anywhere in a road network. It is therefore desirable that a vehicle classifier located on the network can give an indication of the GVM at that location, based on the loading characteristics of the WIM equipment in that state.
The proposed methodology in this report aims to identify, from a list of candidate WIM sites (therefore with known GVM frequency distributions), the one that can give the best indication of the GVM distribution at a classifier site. The method was developed at Main Roads WA and initially investigated at VicRoads. It has been further refined at ARRB and requires the use of piezoelectric cables in the vehicle classifier to give some indication of the loading characteristics of a classifier site.
- 1. INTRODUCTION
- 2. METHOD FOR CORRELATING WIM DATA WITH CLASSIFIED COUNTS
- 2.1. An Intelligent Classifier
- 2.2. Correlation Methodology
- 2.2.1. Stage 1 – Assessment of Suitability
- 2.2.2. Stage 2 – Application of Method
- 2.3. WIM Sites with Similar Levels of Unladenness
- 3. RESULTS OF ANALYSING WA DATA
- 3.1. Suitability of WA WIM Data
- 3.2. Application to Main Roads WA Data
- 3.3. Analysing WA Data – Class 10 Vehicles
- 4. RESULTS OF ANALYSING QUEENSLAND DATA
- 4.1. Suitability of Queensland WIM Data
- 4.2. Application to Queensland TMR Data
- 5. RESULTS OF ANALYSING NSW DATA
- 5.1. Suitability of NSW WIM Data
- 5.2. Application to RTA NSW Data
- 6. CONCLUSIONS AND RECOMMENDATIONS
- REFERENCES
- APPENDIX A LIST OF ABBREVIATIONS
- APPENDIX B ELEVEN SITE PAIRS WITH NSW DATA FOR CLASS 10 VEHICLES