| 研究生: |
周奕伶 Yi-Ling Chou |
|---|---|
| 論文名稱: |
自駕車通過號誌化路口之速率控制 Speed control of autonomous vehicle passing through the signalized intersections |
| 指導教授: | 吳健生 |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 土木工程學系 Department of Civil Engineering |
| 論文出版年: | 2021 |
| 畢業學年度: | 109 |
| 語文別: | 中文 |
| 論文頁數: | 111 |
| 中文關鍵詞: | 自動駕駛汽車 、車聯網 、速率控制 、交通號誌資訊 、紅燈秒數 、Red light seconds |
| 外文關鍵詞: | Vehicle-to-everything, Traffic signal information |
| 相關次數: | 點閱:17 下載:0 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
在這個互聯的時代,互聯的車輛或交通管理系統從其他車輛的感測器或周遭環境、固定基礎設施等去接收訊息,再做出相應的動作,而自駕車與智慧交通號誌的資訊傳遞上,當前為根據車輛系統偵測前方燈號,使駕駛能預判採放油門力道,並根據攝影機和感測器再做出續進或減速行為。現今通訊技術上傳遞範圍已經能夠於更遠的位置就可以接收到號誌資訊,即可以提早知道週期時間,判斷依目前速率是否可以通過路口,依此直接控制系統調整自駕車行駛速率,進而達到改善道路交通流量。
本研究以聯網自駕車於路口一段距離前,可以提早接收號誌資訊並依其調整行駛速率,使其最大程度通過路口而不停駛,建立速率模式及控制策略,界定速率與加速度減速度範圍,針對不同接收位置及紅燈秒數進行各項分析,並且以不同紅燈情況之情境下進行控制結果,以控制自駕車通過號誌化路口,減少因為紅燈造成的停駛時間,並且能夠增加路口通過機率。
The present society is the era of Internet, connected vehicles or traffic management systems receive information from the sensors of other vehicles or the surrounding environment, fixed infrastructure, etc., and then take corresponding actions. In the information transmission of autonomous vehicles and intelligent traffic signals, the current technology is to detect the front light signal according to the vehicle system, so that the driver can predetermine the force of the accelerator, and then progression or deceleration behavior according to the camera and sensor .
Nowadays, the transmission range of communication technology is able to receive the signal information at a farther position, and the cycle time can be known in advance, and it can be judged whether the intersection can be passed at the current rate, and the system can directly control the system to adjust the speed of the autonomous vehicle to improve road traffic flow.
In this study, a connected autonomous vehicle can receive signal information in advance and adjust the driving speed according to it to make it pass the intersection to the maximum extent without stopping, establish a speed model and control strategy, and define the speed and acceleration/deceleration range. Perform various analyses for different receiving positions and red light seconds, and control the results under different red light situations to control the autonomous vehicle to pass signalized intersections, reduce the stop time caused by red lights, and can Increase the probability of passing the intersection.
1.財團法人車輛研究測試中心,自駕車專區。檢自https://www.artc.org.tw/chinese/04_industry/01_01detail.aspx?pdid=22
2.Luo, C., Li, D., Ding, X., & Wu, W. (2020). Delivery Route Optimization with automated vehicle in smart urban environment. Theoretical Computer Science, 836, 42-52.
3.Gora, P., Katrakazas, C., Drabicki, A., Islam, F., & Ostaszewski, P. (2020). Microscopic traffic simulation models for connected and automated vehicles (CAVs)–state-of-the-art. Procedia Computer Science, 170, 474-481.
4.Lian, Y., Zhang, G., Lee, J., & Huang, H. (2020). Review on big data applications in safety research of intelligent transportation systems and connected/automated vehicles. Accident Analysis & Prevention, 146, 105711.
5.Barthauer, M., & Friedrich, B. (2019). Presorting and presignaling: A new intersection operation mode for autonomous and human-operated vehicles. Transportation research procedia, 37, 179-186.
6.Zhu, H. B., Zhou, Y. J., & Wu, W. J. (2020). Modeling traffic flow mixed with automated vehicles considering drivers’ character difference. Physica A: Statistical Mechanics and its Applications, 549, 124337.
7.Bhargava, K., Choy, K. W., Jennings, P. A., Birrell, S. A., & Higgins, M. D. (2020). Traffic Simulation of Connected and Autonomous Freight Vehicles (CAV-F) using a data-driven traffic model of a real-world road tunnel. Transportation Engineering, 2, 100011.
8.Jin, I. G., Avedisov, S. S., He, C. R., Qin, W. B., Sadeghpour, M., & Orosz, G. (2018). Experimental validation of connected automated vehicle design among human-driven vehicles. Transportation research part C: emerging technologies, 91, 335-352.
9.Chen, H., Rakha, H. A., Loulizi, A., El-Shawarby, I., & Almannaa, M. H. (2016). Development and preliminary field testing of an in-vehicle eco-speed control system in the vicinity of signalized intersections. IFAC-PapersOnLine, 49(3), 249-254.
10.Tang, T. Q., Yi, Z. Y., Zhang, J., Wang, T., & Leng, J. Q. (2018). A speed guidance strategy for multiple signalized intersections based on car-following model. Physica A: Statistical Mechanics and its Applications, 496, 399-409.
11.Stebbins, S., Hickman, M., Kim, J., & Vu, H. L. (2017). Characterising green light optimal speed advisory trajectories for platoon-based optimisation. Transportation Research Part C: Emerging Technologies, 82, 43-62.
12.Nguyen, V., Kim, O. T. T., Dang, T. N., Moon, S. I., & Hong, C. S. (2016, October). An efficient and reliable green light optimal speed advisory system for autonomous cars. In 2016 18th Asia-Pacific Network Operations and Management Symposium (APNOMS) (pp. 1-4). IEEE.
13.Zhu, W. X., & Zhang, L. D. (2014). A speed feedback control strategy for car-following model. Physica A: Statistical Mechanics and its Applications, 413, 343-351.
14.郭景華, 李克強, & 羅禹貢. (2016). 智慧車輛運動控制研究綜述. 汽車安全與節能學報, 7(02), 151.
15.Katsaros, K., Kernchen, R., Dianati, M., & Rieck, D. (2011, July). Performance study of a Green Light Optimized Speed Advisory (GLOSA) application using an integrated cooperative ITS simulation platform. In 2011 7th International Wireless Communications and Mobile Computing Conference (pp. 918-923). IEEE.
16.Colombaroni, C., Fusco, G., & Isaenko, N. (2020). A simulation-optimization method for signal synchronization with bus priority and driver speed advisory to connected vehicles. Transportation research procedia, 45, 890-897.
17.張博, 郭戈, 王麗媛, & 王瓊. (2018). 基於信號燈狀態的燃油最優車速規劃與控制. 自動化學報, 44(3), 461-470.
18.Tak, S., Kim, S., & Yeo, H. (2016). A study on the traffic predictive cruise control strategy with downstream traffic information. IEEE Transactions on Intelligent Transportation Systems, 17(7), 1932-1943.
19.Mahler, G., & Vahidi, A. (2014). An optimal velocity-planning scheme for vehicle energy efficiency through probabilistic prediction of traffic-signal timing. IEEE Transactions on Intelligent Transportation Systems, 15(6), 2516-2523.
20.Liang, X. J., Guler, S. I., & Gayah, V. V. (2020). An equitable traffic signal control scheme at isolated signalized intersections using Connected Vehicle technology. Transportation Research Part C: Emerging Technologies, 110, 81-97.
21.Xie, X. F., & Wang, Z. J. (2018). SIV-DSS: Smart in-vehicle decision support system for driving at signalized intersections with V2I communication. Transportation Research Part C: Emerging Technologies, 90, 181-197.
22.Zhao, X., Wu, X., Xin, Q., Sun, K., & Yu, S. (2020). Dynamic Eco-Driving on Signalized Arterial Corridors during the Green Phase for the Connected Vehicles. Journal of Advanced Transportation, 2020.
23.Sun, C., Guanetti, J., Borrelli, F., & Moura, S. J. (2020). Optimal eco-driving control of connected and autonomous vehicles through signalized intersections. IEEE Internet of Things Journal, 7(5), 3759-3773.
24.Ubiergo, G. A., & Jin, W. L. (2016). Mobility and environment improvement of signalized networks through Vehicle-to-Infrastructure (V2I) communications. Transportation Research Part C: Emerging Technologies, 68, 70-82.
25.Ci, Y., Wu, L., Zhao, J., Sun, Y., & Zhang, G. (2019). V2I-based car-following modeling and simulation of signalized intersection. Physica A: Statistical Mechanics and Its Applications, 525, 672-679.
26.Zha, L., Zhang, Y., Songchitruksa, P., & Middleton, D. R. (2015). An integrated dilemma zone protection system using connected vehicle technology. IEEE Transactions on Intelligent Transportation Systems, 17(6), 1714-1723.
27.Priemer, C., & Friedrich, B. (2009, October). A decentralized adaptive traffic signal control using V2I communication data. In 2009 12th International IEEE Conference on Intelligent Transportation Systems (pp. 1-6). IEEE.
28.Han, E., Lee, H. P., Park, S., So, J. J., & Yun, I. (2019). Optimal signal control algorithm for signalized intersections under a V2I communication environment. Journal of Advanced Transportation, 2019.
29.Guo, Q., Li, L., & Ban, X. J. (2019). Urban traffic signal control with connected and automated vehicles: A survey. Transportation research part C: emerging technologies, 101, 313-334.
30.Chandan, K., Seco, A. M., & Silva, A. B. (2017). Real-time traffic signal control for isolated intersection, using car-following logic under connected vehicle environment. Transportation research procedia, 25, 1610-1625.
31.Liang, X. J., Guler, S. I., & Gayah, V. V. (2020). A heuristic method to optimize generic signal phasing and timing plans at signalized intersections using Connected Vehicle technology. Transportation Research Part C: Emerging Technologies, 111, 156-170.
32.Matsumoto, Y., & Nishio, K. (2019). Reinforcement learning of driver receiving traffic signal information for passing through signalized intersection at arterial road. Transportation research procedia, 37, 449-456.
33.Asadi, B., & Vahidi, A. (2010). Predictive cruise control: Utilizing upcoming traffic signal information for improving fuel economy and reducing trip time. IEEE transactions on control systems technology, 19(3), 707-714.
34.Bosetti, P., Da Lio, M., & Saroldi, A. (2014). On the human control of vehicles: an experimental study of acceleration. European Transport Research Review, 6(2), 157-170.
35.Svensson, L., & Eriksson, J. (2015). Tuning for ride quality in autonomous vehicle: Application to linear quadratic path planning algorithm.
36.Moon, S., & Yi, K. (2008). Human driving data-based design of a vehicle adaptive cruise control algorithm. Vehicle System Dynamics, 46(8), 661-690.
37.Bae, I., Moon, J., & Seo, J. (2019). Toward a comfortable driving experience for a self-driving shuttle bus. Electronics, 8(9), 943.
38.Roess, R. P., Prassas, E. S., & McShane, W. R. (2011). Traffic Engineering–Fourth Edition. Pearson Prentice Hall.
39.朱致遠、邱裕鈞、陳惠國 (2017) 。交通工程。五南。
40.臺北市路口號誌時制計畫 (2020年12月31日)。檢自https://data.gov.tw/。