References
- Adams, J.J., et al., 2019. Diagnostic techniques for various asphalt refining and modification methods. Energy & Fuels, 33 (4), 2680–2698.
- Apeagyei, A., et al., 2019. Design and rehabilitation of asphalt pavements: history and future. AFD 60 Standing Committee – Centennial Paper. Washington, D.C.: Transportation Research Board.
- Bijlsma, T., and Hendriks, T., 2020. A fail-operational truck platooning architecture. In: 2017 IEEE Intelligent Vehicles Symposium (IV) IEEE, 1819–1826.
- Castro, M., and Sánchez, J.A., 2006. Fatigue and healing of asphalt mixtures: discriminate analysis of fatigue curves. Journal of Transportation Engineering, 132 (2), 168–174.
- Chen, F., et al., 2019. Assess the impacts of different autonomous trucks’ lateral control modes on asphalt pavement performance. Transportation Research Part C: Emerging Technologies, 103, 17–29.
- Demuth, H., and Beale, M., 1993. Neural network toolbox for use with Matlab – user’s guide. Version 3.0.
- El Bouchihati, M., 2020. The impact of Truck Platooning on the pavement structure of Dutch Motorways: The link between truck platooning and road surface wear. Master’s Thesis. The Delft University of Technology.
- Elwardany, M.D., et al., 2019. Correlation analysis coupled with artificial neural networks to investigate asphalt binder chemo-mechanical relations. In: 56th Petersen Asphalt Research Conference (PARC) Annual Meeting, Laramie, WY.
- Elwardany, M., Planche, J-P., and King, G., 2020. Universal and practical approach to evaluate asphalt binder resistance to thermally-induced surface damage. Construction & Building Materials, 255, 119331.
- Gungor, O.E., et al., 2019. Optimization of lateral position of autonomous trucks. Washington, D.C.: 98th Transportation Research Board.
- Gungor, O.E., and Al-Qadi, I.L., 2020. Wander 2D: a flexible pavement design framework for autonomous and connected trucks. International Journal of Pavement Engineering, 1–16. doi:10.1080/10298436.2020.1735636.
- Hagan, M.T., and Menhaj, M.B, 1994. Training feedforward networks with the Marquardt algorithm. IEEE Transactions on Neural Networks, 5 (6), 989–993.
- Hanna, B.N., et al., 2020. Coarse-grid computational fluid dynamic (CG-CFD) error prediction using machine learning. Progress in Nuclear Energy, 118, 103140.
- Harvey, J., and Tsai, Bor-Wen, 1996. Effect of asphalt content and air void content on mix fatigue and stiffness. Transportation Research Record, 1543, 38–45.
- Isied, M., and Souliman, M., 2019a. Fatigue endurance limit model utilizing artificial neural network for asphalt concrete pavements. In: I. Al-Qadi, et al., eds. Airfield and highway pavements 2019: innovation and sustainability in highway and airfield pavement technology. Reston, VA: American Society of Civil Engineers, 42–50.
- Isied, M., and Souliman, M., 2019b. Integrated predictive artificial neural network fatigue endurance limit model for asphalt concrete pavements. Canadian Journal of Civil Engineering, 46 (2), 114–123.
- Janssen, G.R., et al., 2015. Truck platooning: driving the future of transportation. Report: TNO Innovation for Life.
- Kang, S., Ozer, H., and Al-Qadi, I.L, 2019. Benefit cost analysis (BCA) of autonomous and connected truck (ACT) technology and platooning. In: I. Al-Qadi, et al., ed. Airfield and highway pavements 2019: innovation and sustainability in highway and airfield pavement technology. Reston, VA: American Society of Civil Engineers, 174–182.
- Kircher, J, 2001. Data analysis toolkit# 5: uncertainty analysis and error propagation. University of California Berkeley Seismological Laboratory. Available from: http://seismo.berkeley.edu/~kirchner/eps_120/Toolkits/Toolkit_05.pdf.
- Marquardt, D.W., 1963. An algorithm for least-squares estimation of nonlinear parameters. Journal of the Society for Industrial and Applied Mathematics, 11 (2), 431–441.
- Satani, S., et al., 2020. Preliminary evaluation of using intelligent compaction for life cycle assessment and life cycle cost analysis of pavement structures. Sacramento, CA: Pavement, Roadway, and Bridge Life Cycle Assessment.
- Souliman, M., 2012. Integrated predictive model for healing and fatigue endurance limit for asphalt concrete. Ph.D. Dissertation, Arizona State University.
- Souliman, M.I., et al., 2013. Fatigue endurance limit for HMA based on healing. In: Association of asphalt paving technologists annual meeting, AAPT 2013. Association of Asphalt Paving Technologist, 503–531.
- Strategic Highway Research Program (SHRP), A-404, 1994. Fatigue response of asphalt-aggregate mixes. Strategic Highway Research Program. National Research Council.
- Tayebali, A. A., Rowe, G.M., and Sousa, J.B., 1994. Fatigue response of asphalt aggregate mixtures. Journal of the Association of Asphalt Paving Technologists, 61, 333–360.
- Verstraeten, J., Romain, J. E., and Veverka, V., 1977. The Belgian road research center’s overall approach structural design. In: Fourth International Conference on The Structural Design of Asphalt Pavements, Ann Arbor, MI.
- Witczak, M., et al., 2013. NCHRP Report 762: Laboratory Validation of an Endurance Limit for Asphalt Pavements. Washington, D.C.: Transportation Research Board of the National Academies
- Yin, F., et al., 2020. Performance evaluation and chemical characterization of asphalt binders and mixtures containing recycled polyethylene. Final Report, Plastics Industry Association.