| 研究生: |
黃昱嘉 Huang, Yu-Chia |
|---|---|
| 論文名稱: |
都市幹道連鎖號誌設計分析-深度強化學習與Synchro之比較分析 Analysis of Deep Reinforcement Learning and Synchro For Urban Arterial Signal Coordinations |
| 指導教授: |
胡大瀛
Hu, Ta-Yin |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 交通管理科學系碩士在職專班 Department of Transportation and Communication Management Science(on-the-job training program) |
| 論文出版年: | 2022 |
| 畢業學年度: | 111 |
| 語文別: | 中文 |
| 論文頁數: | 64 |
| 中文關鍵詞: | 人工智慧 、深度強化學習 、幹道連鎖最佳化 |
| 外文關鍵詞: | Artificial Intelligence, Deep Reinforcement Learning, Optimization of Arterial Signal Coordination |
| 相關次數: | 點閱:114 下載:0 |
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1、Arsava, T., Xie, Y., Gartner, N. H., & Mwakalonge, J. (2014). Arterial traffic signal coordination utilizlar traffic origin-destination information. 17th International IEEE Conference on Intelligent Transportation Systems (ITSC),
2、Christofa, E., Ampountolas, K., & Skabardonis, A. (2016). Arterial traffic signal optimization: A person-based approach. Transportation Research Part C: Emerging Technologies, 66, 27-47.
3、Genders, W., & Razavi, S. (2016). Using a deep reinforcement learning agent for traffic signal control. arXiv preprint arXiv:1611.01142.
4、Hao, W., Lin, Y., Cheng, Y., & Yang, X. (2018). Signal progression model for long arterial: intersection grouping and coordination. IEEE Access, 6, 30128-30136.
5、Jing, B., Lin, Y., Shou, Y., Lu, K., & Xu, J. (2020). Pband: A General Signal Progression Model With Phase Optimization Along Urban Arterial. IEEE Transactions on Intelligent Transportation Systems.
6、Lan, C.-L., & Chang, G.-L. (2016). Optimizing signals for arterials experiencing heavy mixed scooter-vehicle flows. Transportation Research Part C: Emerging Technologies, 72, 182-201.
7、Li, L., Lv, Y., & Wang, F.-Y. (2016). Traffic signal timing via deep reinforcement learning. IEEE/CAA Journal of Automatica Sinica, 3(3), 247-254.
8、Li, Z., Yu, H., Zhang, G., Dong, S., & Xu, C.-Z. (2021). Network-wide traffic signal control optimization using a multi-agent deep reinforcement learning. Transportation Research Part C: Emerging Technologies, 125, 103059.
9、Liang, X., Du, X., Wang, G., & Han, Z. (2019). A deep reinforcement learning network for traffic light cycle control. IEEE Transactions on Vehicular Technology, 68(2), 1243-1253.
10、 Liu, M., Deng, J., Xu, M., Zhang, X., & Wang, W. (2017). Cooperative deep reinforcement learning for tra ic signal control. Proc. 23rd ACM SIGKDD Conf. Knowl. Discovery Data Mining (KDD),
11、Rasheed, F., Yau, K.-L. A., Noor, R. M., Wu, C., & Low, Y.-C. (2020). Deep Reinforcement Learning for Traffic Signal Control: A Review. IEEE Access.
12、Stevanovic, A., Martin, P. T., & Stevanovic, J. (2007). VisSim-based genetic algorithm optimization of signal timings. Transportation Research Record, 2035(1), 59-68.
13、Sutton, R. S., & Barto, A. G. (2018). Reinforcement learning: An introduction. MIT press.
14、Van der Pol, E., & Oliehoek, F. A. (2016). Coordinated deep reinforcement learners for traffic light control. Proceedings of Learning, Inference and Control of Multi-Agent Systems (at NIPS 2016).
15、Watkins, C. J., & Dayan, P. (1992). Q-learning. Machine learning, 8(3-4), 279-292.
16、Wei, H., Chen, C., Zheng, G., Wu, K., Gayah, V., Xu, K., & Li, Z. (2019). Presslight: Learning max pressure control to coordinate traffic signals in arterial network. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining,
17、Wu, X., Tian, Z., Hu, P., & Yuan, Z. (2012). Bandwidth optimization of coordinated arterials based on group partition method. Procedia-Social and Behavioral Sciences, 43, 232-244.
18、Zhang, L., Song, Z., Tang, X., & Wang, D. (2016). Signal coordination models for long arterials and grid networks. Transportation Research Part C: Emerging Technologies, 71, 215-230.
19、石家豪. (2001). 幹道號誌續進式時制設計模式之開發研究,碩士論文,國立成功大學.
20、何志宏. (2003). 交通工程人才培訓計畫 (2). 交通部運輸研究所.
21、吳沛儒. (2020). 應用AI技術進行交通數據蒐集暨號誌控制之研究. 交通部運輸研究所.
22、吳悅慈. (2011). 幹道群組適應性號誌控制模式之開發研究,碩士論文,國立成功大學.
23、卓訓榮、曾明德、周幼琳. (2018). 台灣號誌控制軟體(PaSO)示範驗證與推廣計畫. 國立交通大學.
24、林良泰、黃華宇、黃啟倡. (2012). 幹道系統延滯最小下續進路口數最大化模式之研究. 運輸學刊, 24(4), 529-554.
25、林良泰、謝長明、古新全. (2010). 高飽和下幹道號誌系統續進路口數最大化模式. 中國土木水利工程學刊, 22(3), 319-331.
26、胡大瀛、林婉婷、梁力元. (2014). 幹道號誌連鎖之減碳效益比較與分析:以小東路為例. 中華民國運輸學會103年,P.1587-1604.
27、陳一昌、張開國、張仲杰、黃惠隆、黃文鑑、張景平、翁忠川. (2007). 交通號誌時制重整計畫(1)-標準作業程序建立. 交通部運輸研究所.
28、陳麗雯, & 胡大瀛. (2020). 都市幹道連鎖時制設計之研究與實例分析. 土木水利, 47(4), 40-50.
29、黃秀雲. (2007). 都市路網號誌連鎖最佳化之研究,碩士論文,國立成功大學.
30、李卓育(2022). 深度強化學習法於交通號誌連鎖之應用,碩士論文,國立成功大學.
校內:2026-01-30公開