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A data-driven operational integrated driving behavioral model on highways

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Abstract

Car-following (CF) and lane-changing (LC) behavior models have been widely studied separately as the core models of traffic simulation. However, in practice, CF and LC are inseparable and thus integrated driving (ID) models containing CF and LC behaviors emerge. Here, we proposed a new work to introduce the social force (SF) model to the operational ID behavioral model on the highway. First, a data-driven-based operational ID behavioral model is proposed in the hierarchical social force behavioral model framework. Then, the inputs/output of the SF-ID behavioral model is determined. SF-ID model is built by the feed-forward neural networks (FNN), and the network structure and other parameters are calibrated and verified by field data. Results of the test on CF and LC situations show that our proposed FNN SF-ID model has a good capability in reproducing/predicting the operational ID behaviors on the highway. In addition, we also analyzed the structural features of the FNN SF-ID models, and refine the original models by removing insignificant inputs. The comparison results showed that the refined model—FNN SF-ID (R)—performed better than the original models.

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Acknowledgements

This work was partially supported by National Natural Science Foundation of China (Grant Nos. 51408237, 51775565 and U1811463), Science and Technology Planning Project of Guangdong Province (Grant No. 2017A040405021), Fundamental Research Funds for the Central Universities (Grant No. 18lgpy83), and the Engineering and Physical Sciences Research Council of U.K. under the EPSRC Innovation Fellow scheme (Grant No. EP/S001956/1).

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Authors and Affiliations

  1. School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, 510640, People’s Republic of China

    Ling Huang & Hengcong Guo

  2. Guangdong Key Laboratory of Intelligent Transportation System, School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, 510275, People’s Republic of China

    Ronghui Zhang

  3. Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough, LE11 3TU, UK

    Dezong Zhao

  4. Department of Civil Engineering, Tsinghua University, Beijing, 100084, People’s Republic of China

    Jianping Wu

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  1. Ling Huang
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Correspondence to Ronghui Zhang.

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Huang, L., Guo, H., Zhang, R. et al. A data-driven operational integrated driving behavioral model on highways. Neural Comput & Applic 32, 13017–13033 (2020). https://doi.org/10.1007/s00521-020-04746-5

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