Bingjie Lu

Ms. Bingjie Lu

orcid

Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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5 January 2024 in Construction and Building Materials
Verified
Journal Article
Closed access
HDHan-Cheng Dan
Han-Cheng Dan
BLBingjie Lu
Bingjie Lu
MLMengyu Li
Mengyu Li

9 November 2024 in Construction and Building Materials
Verified
Journal Article
Closed access
HDHan-Cheng Dan
Han-Cheng Dan
ZHZhetao Huang
Zhetao Huang
BLBingjie Lu
Bingjie Lu
MLMengyu Li
Mengyu Li

22 May 2025 in Neurocomputing
Verified
Journal Article
Closed access
Zhengyang LuZhengyang Lu
Zhengyang Lu
BLBingjie Lu
Bingjie Lu
FWFeng Wang
Feng Wang

31 July 2025 in Lubricants
Verified
Journal Article
Open access
PDF file
BLBingjie Lu
Bingjie Lu
Zhengyang LuZhengyang Lu
Zhengyang Lu
YQYIJIASHUN QI
YIJIASHUN QI
HGHanzhe Guo
Hanzhe Guo
TSTianyao Sun
Tianyao Sun
ZZZunduo Zhao
Zunduo Zhao
Pavement skid resistance is of vital importance for road safety. The objective of this study is to propose and validate a texture-based image indicator to predict pavement friction. This index enables pavement friction to be predicted easily and inexpensively using digital images, with predictions correlated to Dynamic Friction Tester (DFT) measurements. Three different types of asphalt surfaces (Dense-Grade Asphalt Concrete, Open-Grade Friction Course, and Chip Seal) were evaluated subject to various tire polishing cycles. Images were taken with corresponding friction coefficients obtained using DFT in the laboratory. The aggregate protrusion area is proposed as the indicator. Statistical models are established for each asphalt surface type to correlate the proposed indicator with friction coefficients. The results show that the adjusted R-squared values of all relationships are above 0.90. Compared to other image-based indicators in the literature, the proposed image indicator more accurately reflects the changes in pavement friction with the number of polishing cycles, proving its cost-effective use for considering pavement friction in the mix design stage.
1

4 July 2025 in arXiv
Verified
Preprint
Open access
PDF file
BLBingjie Lu
Bingjie Lu
Zhengyang LuZhengyang Lu
Zhengyang Lu
YQYIJIASHUN QI
YIJIASHUN QI
HGHanzhe Guo
Hanzhe Guo
TSTianyao Sun
Tianyao Sun
ZZZunduo Zhao
Zunduo Zhao
Pavement skid resistance is of vital importance for road safety. The objective of this study is to propose and validate a texture-based image indicator to predict pavement friction. This index enables pavement friction to be measured easily and inexpensively using digital images. Three different types of asphalt surfaces (dense-graded asphalt mix, open-grade friction course, and chip seal) were evaluated subject to various tire polishing cycles. Images were taken with corresponding friction measured using Dynamic Friction Tester (DFT) in the laboratory. The aggregate protrusion area is proposed as the indicator. Statistical models are established for each asphalt surface type to correlate the proposed indicator with friction coefficients. The results show that the adjusted R-square values of all relationships are above 0.90. Compared to other image-based indicators in the literature, the proposed image indicator more accurately reflects the changes in pavement friction with the number of polishing cycles, proving its cost-effective use for considering pavement friction in mix design stage.