Data-Driven Prediction for Red-Light-Running at a TJunction
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-7976-9_52
Reference6 articles.
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2. Franklin, R.J.: Traffic signal violation detection using artificial intelligence and deep learning. In: 2020 5th International Conference on Communication and Electronics Systems (ICCES). pp. 839–844. IEEE (2020).
3. Chen, X., Zhou, L., Li, L.: Bayesian network for red-light-running prediction at signalized intersections. Journal of Intelligent Transportation Systems. 23, 120–132 (2019). https://doi.org/10.1080/15472450.2018.1486192.
4. Kalman, R.E.: A new approach to linear filtering and prediction problems. (1960). https://doi.org/10.1115/1.3662552.
5. Qin, H., Wei, Y., Zhang, Q., Ma, L.: An observational study on the risk behaviors of electric bicycle riders performing meal delivery at urban intersections in China. Transportation research part F: traffic psychology and behaviour. 79, 107–117 (2021). https://doi.org/10.1016/j.trf.2021.04.010.
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