自主駕駛車輛的佔有比對都會混流交通的影響

A Study on the Effect of Autonomous Vehicle Penetration Rate in Urban Mix-fleet Traffic

林峻廷(Chun-Ting Lin)

指導教授 ： 詹魁元

國立臺灣大學/工學院/機械工程學研究所/碩士(2018年)

https://doi.org/10.6342/NTU201803922

摘要

自主駕駛車輛很可能在未來的道路上逐漸增加，然而在台灣的都會交通中，機車位機動車輛比率約65%，是不可忽視的部份，而自主駕駛車輛對汽機混流環境的影響，缺乏足夠的評估。因此本研究以微觀交通模擬為基礎，分別對一般駕駛汽車、機車、自主駕駛車輛及車隊自主駕駛車輛建立模型，並撰寫電腦程式進行模擬。其中一般駕駛汽車使用行為門檻模型，機車使用力場模型，自主駕駛車輛使用智慧駕駛模型，車隊自主駕駛車輛則以智慧駕駛模型並加上能跟隨前車加速度的模型。並且以實地空拍的資料對一般駕駛汽車及機車模型進行驗證。模擬的結果為無車隊功能的自主駕駛車輛對車流幾乎沒有影響，而有車隊功能的自主車輛在純汽車環境下隨著自駕車增加有越來越顯著的上升。車隊自主車輛在汽機車混流環境下，則對依機車的比例有不同的影響，在無機車情況下最大流量可以增加95.4%，但在75%的機車環境下最大流量僅增加5.8%，機車的存在會降低車隊自主駕駛車對車流表現提升的幅度。

關鍵字

自主駕駛車 ； 汽機車混流 ； 微觀車流模擬 ； 流量基本圖 ； 車隊

並列摘要

Autonomous car has a high possibility to become the mainstream in the future road. However, motorcycle plays a non-negligible part role in Taiwanese urban traffic. About 65% of motor vehicles are motorcycle.The effect of autonomous on mix-fleet traffic is not yet well evaluated. This research is based on microscopic traffic simulation. And models of normal driver car, motorcycle, autonomous car, autonomous car with platooning function are built respectively. The simulation is done by program application. The model of normal driver using action point model, motorcycle using force field model, and autonomous car using intelligent driver model, autonomous car with platooning function using model that follow the acceleration of car in front.We verified the models of normal driver car and motorcycle by aerial video. The result indicates that autonomous car has no influence on traffic flow. On the other hand, autonomous with platooning function has a significant growth with the increasing number of autonomous cars in pure car traffic. Autonomous with platooning function has different influence in mix-fleet traffic with respect to different percentage of motorcycles. Traffic flow increase 95.4% with no motorcycle, but only increase 5.8% with 75%motorcycles. The exist of motorcycle will decrease the advantage of autonomous with platooning function on traffic flow.

並列關鍵字

Autonomous car ； Mix-fleet ； Microscopic traffic simulation ； Fundamental diagram of traffic flow ； Platooning

參考文獻

[1] T. Hummel, M. Kühn, J. Bende, and A. Lang, “Advanced driver assistance systems,”German Insurance Association Insurers Accident Research. Available on www. udv.de, accessed at, vol. 6, no. 01, p. 2015, 2011.

[2] National Highway Traffic Safety Administration, “Automated Vehicles for Safety.”https://www.nhtsa.gov/technology-innovation/automated-vehiclessafety.Accessed: 2018-07-15.

[3] M. Bertoncello and D. Wee, “Ten ways autonomous driving could redefine the automotive world,” McKinsey & Company, vol. 6, 2015.

[4] 中華民國交通部, “機動車輛登記數.” https://stat.motc.gov.tw/mocdb/stmain.jsp?sys=100&funid=a3301. Accessed: 2018-07-15.

[5] T. Litman, Autonomous vehicle implementation predictions. Victoria Transport Policy Institute Victoria, Canada, 2017.