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Scientific notes

Effect of cumulative traffic and statistical predictive modelling of field skid resistance

, , , , & ORCID Icon
Pages 426-439 | Received 11 Jan 2017, Accepted 05 Sep 2017, Published online: 11 Oct 2017
 

Abstract

Skid resistance value (SRV) is a significant parameter representing the road safety condition. The measurement of SRV at different times after the construction is time-consuming and costly. To accurately predict the reduction of SRV, the SRV reduction model has been developed based on the aggregate and asphalt concrete mixture characteristics and field cumulative traffic volumes. In this study, three main types of aggregates typically used in pavements in Thailand, being limestone, granite and basalt were used to make asphalt concrete. The standard dense-grade asphalt concrete mixtures of 9.5 and 12.5 mm maximum aggregate sizes were designed and constructed at the studied sites (12 project sites located in 6 provinces). The SRVs were measured at every 50,000 passenger car unit (pcu) by the British pendulum tester for 3–4 years after the end of construction. Based on the statistical analysis of the test results, the SRV at various cumulative traffic volumes can be predicted using asphalt concrete mixture characteristics and initial SRV (after the end of construction) as prime parameters. The model will be recommended for inclusion in the Department of Rural Roads, Thailand preventive scheme for road safety management protocols.

Acknowledgements

This research paper was made possible with the help and support from Department of Rural Roads, Thailand.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The authors acknowledge the financial support from the Thailand Research Fund under the TRF Senior Research Scholar program [grant no. RTA5980005], Suranaree University of Technology, and Department of Rural Roads, Thailand.

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