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Use of Main Roads WA Corporate Data for Road Safety Risk Data Sets

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Use of Main Roads WA Corporate Data for Road Safety Risk Data Sets Use of Main Roads WA Corporate Data for Road Safety Risk Data Sets Exploring the use of Corporate Data for AusRAP/ANRAM Data Sets ABN 68 004 620 651 Victoria 80A Turner St Port Melbourne VIC 3207 Australia Use of Main Roads WA Corporate Data for P: +61 3 9881 1555 F: +61 3 9887 8104 Road Safety Risk Data Sets [email protected] 2017-011 Western Australia 191 Carr Place Leederville WA 6007 Australia P: +61 8 9227 3000 F: +61 8 9227 3030 [email protected] New South Wales 2-14 Mountain St Ultimo NSW 2007 Australia P: +61 2 9282 4444 F: +61 2 9280 4430 [email protected] for Mark Parr (Main Roads WA) Queensland 21 McLachlan St Fortitude Valley QLD 4006 Australia P: +61 7 3260 3500 F: +61 7 3862 4699 [email protected] South Australia Level 11, 101 Grenfell Street Adelaide SA 5000 Australia P: +61 8 7200 2659 F: +61 8 8223 7406 [email protected] Reviewed Project Leader Anna Brett Quality Manager Lisa Steinmetz PSS17081-1 September 2018 Commercial in confidence September 2018 SUMMARY This project explored the suitability and applicability of using corporate data extracted from the Main Roads WA corporate database to supplement and ultimately replace the traditional (manually coded data) approach for developing AusRAP and ANRAM data sets. Data collected during the WARRIP TSD trial was used in the comparison of Main Roads corporate data against the traditional approach. An analysis of the differences between the data sets found similarities in the coding of results of some attributes but substantial differences in many others. It is suggested that corporate data could be used for some, although not currently all, attributes for producing AusRAP / ANRAM data sets. With further investigation and fine tuning, additional attributes could potentially be extracted from the corporate database. It is noted that additional work would need to be undertaken to improve alignment and to ensure confidence in the corporate data. It is recommended that for attributes that require review and refinement, traditional (manual) rating continue in parallel to the (evolving) corporate extraction to facilitate ongoing comparison, analysis and refinement of these until there is confidence that the corporate data can be consistently and accurately extracted. While use of corporate data is anticipated to deliver relatively small cost savings over the short-term, further cost saving opportunities would arise over time. A number of key challenges, observations and lessons were noted during this project, including: ▪ There are challenges in aligning data from different sources. ▪ Differences in terminology and understanding / familiarity with different data within ARRB and Main Roads WA can lead to miscommunication and errors. ▪ For some attributes, corporate data may provide more accurate information than the AusRAP traditional (manual) rating approach. ▪ Assumptions relating to the accuracy and / or currency of information in the corporate database, and / or interpretation of these attributes may be erroneous. Although the Report is believ ed to be correct at the time of publication, ▪ Use of corporate data will require consideration of new issues such Australian Road Research Board, to the as deterioration of assets over time. extent lawf ul, excludes all liability f or loss ▪ Differences in interpretation or categorisation of attributes (between (whether arising under contract, tort, corporate and traditional approach) need to be understood statute or otherwise) arising f rom the (particularly if these lead to differences in star rating outcomes). contents of the Report or f rom its use. Where such liability cannot be excluded, ▪ Recognising that some attributes are (currently) difficult to it is reduced to the f ull extent lawf ul. systematically or automatically extract from the corporate database. Without limiting the f oregoing, people However, new and evolving techniques and technologies will help should apply their own skill and improve accuracy of data attributes and will ultimately lead to judgement when using the inf ormation automatic classification of these. contained in the Report. Commercial in confidence - i - September 2018 ACKNOWLEDGEMENTS The authors would like to acknowledge the large contributions to this project by key data management staff from both Main Roads WA and ARRB. Commercial in confidence - ii - September 2018 CONTENTS 1 INTRODUCTION ........................................................................................................................ 1 1.1 Background................................................................................................................................. 1 1.2 Purpose for Project..................................................................................................................... 1 1.3 Method Overview........................................................................................................................ 2 1.4 Comment on Other Similar Projects .......................................................................................... 2 2 METHOD .................................................................................................................................... 3 2.1 AusRAP Data Sets ..................................................................................................................... 3 2.1.1 Traditional Coded Data Set (Based on TSD Data)...................................................... 3 2.1.2 Corporate Data Set (Extracted from Main Roads WA Corporate Asset Database) ... 3 2.2 ANRAM Data Sets...................................................................................................................... 4 2.3 Analysis ...................................................................................................................................... 5 2.3.1 Data Set Comparison ................................................................................................... 5 2.3.2 AusRAP Results Comparison .................................................................................... 15 2.3.3 ANRAM Results Comparison..................................................................................... 21 3 FINDINGS AND DISCUSSION ................................................................................................ 23 3.1 Differences in Coding and Risk Assessment Results.............................................................. 23 3.2 Key Challenges, Observations and Lessons Learnt................................................................ 24 3.3 Comment on Efficiencies and Value for Money....................................................................... 26 3.4 Next Steps and Future Technology ......................................................................................... 27 REFERENCES................................................................................................................................... 29 APPENDIX A DERIVING IRAP AND ANRAM ATTRIBUTES FROM IRIS ...................... 30 APPENDIX B EXAMPLE ROAD SEGMENT LENGTH APPROACH ............................... 60 APPENDIX C CODING COMPARISON BETWEEN DATA SETS.................................... 63 APPENDIX D CODING COMPARISON BY J KARPINSKI............................................... 80 APPENDIX E GLOSSARY ................................................................................................. 81 Commercial in confidence - iii - September 2018 TABLES Table 2.1: Calibration factors ...................................................................................................... 4 Table 2.2: Data set comparison (length & rows) ........................................................................ 6 Table 2.3: Data set comparison overview .................................................................................. 8 Table 2.4: Critical attributes in crash risk estimation of different crash types .......................... 14 Table 2.5: AusRAP star rating results....................................................................................... 16 Table 2.6: AusRAP star rating comparison .............................................................................. 18 Table 2.7: AusRAP star rating detailed comparison................................................................. 18 Table 2.8: ANRAM results summary (traditional vs corporate) ................................................ 22 FIGURES Figure 2.1: Corporate data: frequency of segment lengths ......................................................... 6 Figure 2.2: AusRAP star rating map .......................................................................................... 17 Figure 2.3: SRS correlation results ............................................................................................ 20 Commercial in confidence - iv - September 2018 Use of Main Roads WA Corporate Data for Road Safety Risk Data Sets PSS17081-1 1 INTRODUCTION 1.1 Background The Safe System approach establishes an ethical position that no one should die or be seriously injured on the road. To fulfil this vision there is a requirement to identify parts or segments of the road network that require treatment. The traditional approach to identify crash risk is through crash history (reactive approach). Given that human error may occur at any time on the road network, and that the human tolerance to impact forces may be exceeded on many sections of the network, a proactive approach is valuable. A proactive approach enables Main Roads
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