329
Views
4
CrossRef citations to date
0
Altmetric
Research Article

DLW-Net model for traffic flow prediction under adverse weather

ORCID Icon, ORCID Icon &
Pages 499-524 | Received 09 Jun 2021, Accepted 11 Nov 2021, Published online: 02 Dec 2021

References

  • Angayarkanni, S. A., R. Sivakumar, and Y. V. R. Rao. 2021. “Hybrid Grey Wolf: Bald Eagle Search Optimized Support Vector Regression for Traffic Flow Forecasting.” Journal of Ambient Intelligence and Humanized Computing 12 (1): 1293–1304.
  • Cheng, J., G. Li, and X. H. Chen. 2019. “Developing a Travel Time Estimation Method of Freeway Based on Floating Car Using Random Forests.” Journal of Advanced Transportation, Article ID: 8582761.
  • Cheng, X. L., L. H. Quan, F. Hu, and B. L., Wang. 2007. “The Fractal and Chaotic Characteristic of Gustwind.” Climatic and Environmental Research 12 (3): 256–266.
  • Dai, X. Y., R. Fu, E. M. Zhao, Z. Zhang, Y. l. Lin, F. Y. Wang, and L. Li. 2019. “DeepTrend 2.0: A Light-Weighted Multi-Scale Traffic Prediction Model Using Detrending.” Transportation Research Part C: Emerging Technologies 103: 142–157.
  • Dunne, S., and B. Ghosh. 2013. “Weather Adaptive Traffic Prediction Using Neurowavelet Models.” IEEE Transactions on Intelligent Transportation Systems 14 (1): 370–379.
  • Grade of Precipitation. 2012. GB/T 28592-2012 (in Chinese).
  • Gu, Y. l., W. Q. Lu, L. Q. Qin, M. Li, and Z. Z. Shao. 2019. “Short-Term Prediction of Lane-Level Traffic Speeds: A Fusion Deep Learning Model.” Transportation Research Part C: Emerging Technologies 106: 1–16.
  • Guo, S. N., Y. F. Lin, N. Feng, C. Song, and H. Y. Wan.  2019. “Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting.” In Proceedings of 33rd AAAI Conference on Artificial Intelligence/31st Innovative Applications of Artificial Intelligence Conference/9th AAAI Symposium on Educational Advances in Artificial Intelligence, 922–929, Honolulu.
  • Hochreiter, S., and J. Schmidhuber. 1997. “Long Short-Term Memory.” Neural Computation 9 (8): 1735–1780.
  • Hu, R., Y. Chiu, and C. Hsieh. 2020. “Crowding Prediction on Mass Rapid Transit Systems Using a Weighted Bidirectional Recurrent Neural Network.” IET Intelligent Transport Systems 14 (3): 196–203.
  • Huang, M. L. 2015. “Intersection Traffic Flow Forecasting Based on v-GSVR with a New Hybrid Evolutionary Algorithm.” Neurocomputing 147: 343–349.
  • Huang, W. H., G. J. Song, H. K. Hong, and K. Q. Xie. 2014. “Deep Architecture for Traffic Flow Prediction: Deep Belief Networks with Multitask Learning.” IEEE Transactions on Intelligent Transportation Systems 15 (5): 2191–2201.
  • Jia, Y. H., J. P. Wu, M. Ben-Akiva, R. Seshadri, and Y. M. Du. 2017. “Rainfall-Integrated Traffic Speed Prediction Using Deep Learning Method.” IET Intelligent Transport Systems 11 (9): 531–536.
  • Jia, Y. H., J. P. Wu, and M. Xu. 2017. “Traffic Flow Prediction with Rainfall Impact Using a Deep Learning Method.” Journal of Advanced Transportation, Article Number: UNSP 6575947.
  • Jiang, X. C., B. Wang, and Y. S. Zeng. 2014. “Influence of Inclement Weather and Poor Road Condition on Traffic Signal Timing Scheme.” Journal of Highway and Transportation Research and Development (Chinese Edition) 31 (7): 135–142+158.
  • Kamarianakis, Y., and P. Prastacos. 2003. “Forecasting Traffic Flow Conditions in an Urban Network: Comparison of Multivariate and Univariate Approaches.” Transportation Research Record 1857: 74–84.
  • Koesdwiady, A., R. Soua, and F. Karray. 2016. “Improving Traffic Flow Prediction with Weather Information in Connected Cars: A Deep Learning Approach.” IEEE Transactions on Vehicular Technology 65 (12): 9508–9517.
  • Lana, I., J. L. Lobo, E. Capecci, J. D. Ser, and N. Kasabov. 2019. “Adaptive Long-Term Traffic State Estimation with Evolving Spiking Neural Networks.” Transportation Research Part C 101: 126–144.
  • Li, L. C., L. Q. Qin, X. Qu, J. Zhang, Y. G. Wang, and B. Ran. 2019. “Day-Ahead Traffic Flow Forecasting Based on a Deep Belief Network Optimized by the Multi-Objective Particle Swarm Algorithm.” Knowledge-Based Systems 172: 1–14.
  • Liu, L. J., and R. C. Chen. 2017. “A Novel Passenger Flow Prediction Model Using Deep Learning Methods.” Transportation Research Part C: Emerging Technologies 84: 74–91.
  • Liu, Y. P., H. F. Zheng, X. X. Feng, and Z. H. Chen. 2017. “Short-Term Traffic Flow Prediction with Conv-LSTM.” In Proceedings of 9th International Conference on Wireless Communications and Signal Processing (WCSP), 1–6, Nanjing.
  • Lv, Y. S., Y. J. Duan, W. W. Kang, Z. X. Li, and F. Y. Wang. 2015. “Traffic Flow Prediction with Big Data: A Deep Learning Approach.” IEEE Transactions on Intelligent Transportation Systems 16 (2): 865–873.
  • Ma, X. L., Z. Dai, Z. B. He, J. H. Ma, Y. Wang, and Y. P. Wang. 2017. “Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction.” Sensors 17 (4): Article Number: 818.
  • Ma, D. F., B. W. Sheng, S. Jin, X. L. Ma, and P. Gao. 2018. “Short-Term Traffic Flow Forecasting by Selecting Appropriate Predictions Based on Pattern Matching.” IEEE Access 6: 75629–75638.
  • Ma, X. L., Z. M. Tao, Y. H. Wang, H. Y. Yu, and Y. P. Wang. 2015. “Long Short-Term Memory Neural Network for Traffic Speed Prediction Using Remote Microwave Sensor Data.” Transportation Research Part C: Emerging Technologies 54: 187–197.
  • McMichael, A. J., R. E. Woodruff, and S. Hales. 2006. “Climate Change and Human Health: Present and Future Risks.” Lancet 367 (9513): 859–869.
  • Okutani, I., and Y. J. Stephanedes. 1984. “Dynamic Prediction of Traffic Volume Through Kalman Filtering Theory.” Transportation Research Part B: Methodological 18 (1): 1–11.
  • Pan, Y. Y., Z. Y. Zhu, P. Y. Shen, T. T. Gu, and W. W. Zhang. 2013. “Highway Traffic Accident Features and Analysis of Effect and Adverse Weather Conditions in Zhejiang Province.” Highway 58 (12): 157–160.
  • Polson, N. G., and V. O. Sokolov. 2017. “Deep Learning for Short-Term Traffic Flow Prediction.” Transportation Research Part C: Emerging Technologies 79: 1–17.
  • Qiao, W. X., A. Haghani, and M. Hamedi. 2012. “Short-Term Travel Time Prediction Considering the Effects of Weather.” Transportation Research Record 2308: 61–72.
  • Qiao, W. X., A. Haghani, C. Shao, and J. Liu. 2016. “Freeway Path Travel Time Prediction Based on Heterogeneous Traffic Data Through Nonparametric Model.” Journal of Intelligent Transportation Systems 20 (5): 438–448.
  • Shabarek, A., S. Chien, and S. Hadri. 2020. “Deep Learning Framework for Freeway Speed Prediction in Adverse Weather.” Transportation Research Record 2674 (10): 28–41.
  • Soua, R., A. Koesdwiady, and F. Karray. 2016. “Big-Data-Generated Traffic Flow Prediction Using Deep Learning and Dempster-Shafer Theory.” In Proceedings of International Joint Conference on Neural Networks (IJCNN), Vancouver.
  • Sun, H. Y., H. X. Liu, H. Xiao, R. R. He, and B. Ran. 2003. “Use of Local Linear Regression Model for Short-Term Traffic Forecasting.” Transportation Research Record 1836: 143–150.
  • Sun, Y., and D. B. Work. 2018. “Scaling the Kalman Filter for Large-Scale Traffic Estimation.” IEEE Transactions on Control of Network Systems 5 (3): 968–980.
  • Sun, T., C. W. Yang, K. Han, W. J. Ma, and F. Zhang. 2020. “Bidirectional Spatial-Temporal Network for Traffic Prediction with Multisource Data.” Transportation Research Record 2674 (8): 78–89.
  • Sun, H. Y., J. S. Yang, L. B. Li, and B. Wu. 2016. “Fuzzy Neural Network System for Urban Expressway Speed Prediction on Rainy day.” Journal of Tongji University (Natural Science) 44 (11): 1695–1701.
  • Sun, S. L., G. Q. Yu, and C. S. Zhang. 2004. “Short-Term Traffic Flow Forecasting Using Sampling Markov Chain Method with Incomplete Data.” In Proceedings of 2004 IEEE Intelligent Vehicles Symposium, 437–441, Parma.
  • Tanimura, R., A. Hiromori, H. Yamaguchi, T. Higashino, and T. Umedu.  2015. “Prediction of Deceleration Amount of Vehicle Speed in Snowy Urban Roads Using Weather Information and Traffic Data.” In Proceedings of 18th IEEE International Conference on Intelligent Transportation Systems, Spain.
  • Vlahogianni, E. I., M. G. Karlaftis, and J. C. Golias. 2005. “Optimized and Meta-Optimized Neural Networks for Short-Term Traffic Flow Prediction: A Genetic Approach.” Transportation Research Part C 13 (3): 211–234.
  • Vlahogianni, E. I., M. G. Karlaftis, and J. C. Golias. 2014. “Short-Term Traffic Forecasting: Where We Are and Where We’re Going.” Transportation Research Part C 43 (SI): 3–19.
  • Wang, H. Z., L. Liu, S. J. Dong, Z. Qian, and H. Wei. 2016. “A Novel Work Zone Short-Term Vehicle-Type Specific Traffic Speed Prediction Model Through the Hybrid EMD-ARIMA Framework.” Transportmetrica B-Transport Dynamics 4 (3): 159–186.
  • Wang, K., C. X. Ma, Y. H. Qiao, X. J. Lu, W. N. Hao, and S. Dong. 2021. “A Hybrid Deep Learning Model with 1DCNN-LSTM-Attention Networks for Short-Term Traffic Flow Prediction.” Physica A: Statistical Mechanics and its Applications 583: Article number: 126293.
  • Wang, X. X., and L. H. Xu. 2018. “Short-Term Traffic Flow Prediction Based on Deep Learning.” Journal of Transportation Systems Engineering and Information Technology 18 (1): 81–88.
  • Wang, J. Y., X. F. Xu, F. S. Wang, C. Chen, and K. Ren. 2018. “A Deep Prediction Architecture for Traffic Flow with Precipitation Information.” In Proceedings of Advances in Swarm Intelligence. 9th International Conference, ICSI 2018, Shanghai.
  • Wind Scale. 2012. GB/T 28591-2012 (in Chinese).
  • Wu, Y. K., H. C. Tan, L. Q. Qin, B. Ran, and Z. X. Jiang. 2018. “A Hybrid Deep Learning Based Traffic Flow Prediction Method and Its Understanding.” Transportation Research Part C: Emerging Technologies 90: 166–180.
  • Xu, Y. Y., H. Chen, Q. J. Kong, X. Zhai, and Y. C. Liu. 2016. “Urban Traffic Flow Prediction: A Spatio-Temporal Variable Selection-Based Approach.” Journal of Advanced Transportation 50 (4): 489–506.
  • Yang, D., S. J. Li, Z. Peng, P. Wang, J. H. Wang, and H. M. Yang. 2019. “MF-CNN: Traffic Flow Prediction Using Convolutional Neural Network and Multi-Features Fusion.” IEICE Transactions on Information and Systems E102D (8): 1526–1536.
  • Yao, R. H., W. S. Zhang, and D. Zhang. 2020. “Period Division-Based Markov Models for Short-Term Traffic Flow Prediction.” IEEE Access 8: 178345–178359.
  • Yu, G. Q., J. M. Hu, C. S. Zhang, L. K. Zhuang, and J. Y. Song. 2003. “Short-Term Traffic Flow Forecasting Based on Markov Chain Model.” In Proceedings of IEEE IV2003: Intelligent Vehicles Symposium, 208–212, Columbus, OH.
  • Zhang, K., and W. Gao. 1997. Probability Theory and Mathematical Statistics. Changchun: Northeast Normal University Press.
  • Zhang, D., and M. R. Kabuka. 2018. “Combining Weather Condition Data to Predict Traffic Flow: A GRU-Based Deep Learning Approach.” IET Intelligent Transport Systems 12 (7): 578–585.
  • Zhang, Z. C., M. Li, X. Lin, Y. H. Wang, and F. He. 2019. “Multistep Speed Prediction on Traffic Networks: A Deep Learning Approach Considering Spatio-Temporal Dependencies.” Transportation Research Part C: Emerging Technologies 105: 297–322.
  • Zhang, L., J. Q. Wu, J. Shen, M. Chen, R. Wang, X. L. Zhou, C. K. Xu, Q. K. Yao, and Q. Wu. 2021. “SATP-GAN: Self-Attention Based Generative Adversarial Network for Traffic Flow Prediction.” Transportmetrica B-Transport Dynamics 9 (1): 552–568.
  • Zhao, Z., W. H. Chen, X. M. Wu, P. Chen, and J. M. Liu. 2017. “LSTM Network: A Deep Learning Approach for Short-Term Traffic Forecast.” IET Intelligent Transport Systems 11 (2): 68–75.
  • Zhao, Z. H., H. G. Kang, M. W. Li, P. F. Zhou, and R. J. Mo. 2011. “Prediction of Freeway Short-Term Traffic Flow Based on Gaussian-SVR.” Journal of Wuhan University of Technology (Transportation Science & Engineering) 35 (6): 1187–1191.
  • Zhao, X. H., G. C. Ren, C. Chen, and J. Rong. 2017. “A Review on Driving Behavior Under Adverse Weather Conditions.” Journal of Transport Information and Safety 35 (5): 70–75 + 98.
  • Zheng, Z. B., Y. T. Yang, J. H. Liu, H. N. Dai, and Y. Zhang. 2019. “Deep and Embedded Learning Approach for Traffic Flow Prediction in Urban Informatics.” IEEE Transactions on Intelligent Transportation Systems 20 (10): 3927–3939.
  • Zhu, Z., B. Peng, C. F. Xiong, and L. Zhang. 2016. “Short-Term Traffic Flow Prediction with Linear Conditional Gaussian Bayesian Network.” Journal of Advanced Transportation 50 (6): 1111–1123.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.