2023-08-14 ノースカロライナ州立大学(NCState)
Image credit: Nabeel Syed.
◆研究では、計算モデルを使用して交通状況をシミュレートし、自動運転車、接続車両などを考慮。結果として、接続された車両の割合が高いほど交差点の通過能力が向上し、通行時間が短縮されることが分かったが、接続されていない自動運転車の割合が高いと通行時間が遅くなることが明らかになった。この研究は、将来の交通制御システムや車両設計に接続性を組み込む重要性を示唆している。
＜関連情報＞
- https://news.ncsu.edu/2023/08/self-driving-cars-can-make-traffic-slower/
- https://journals.sagepub.com/doi/10.1177/03611981231187386
信号交差点の飽和ヘッドウェイと容量に対する接続性と自動化の効果 Effects of Connectivity and Automation on Saturation Headway and Capacity at Signalized Intersections
Ali Hajbabaie, Mehrdad Tajalli, and Eleni Bardaka
Transportation Research Record Published:August 11, 2023
DOI:https://doi.org/10.1177/03611981231187386
Abstract
This paper analyzes the potential effects of connected and automated vehicles on saturation headway and capacity at signalized intersections. A signalized intersection is created in Vissim as a testbed, where four vehicle types are modeled and tested: (I) human-driven vehicles (HVs), (II) connected vehicles (CVs), (III) automated vehicles (AVs), and (IV) connected automated vehicles (CAVs). Various scenarios are defined based on different market-penetration rates of these four vehicle types. AVs are assumed to move more cautiously than HVs. CVs and CAVs are supposed to receive information about the future state of traffic lights and adjust their speeds to avoid stopping at the intersection. As a result, their movements are expected to be smoother with a lower number of stops. The effects of these vehicle types in mixed traffic are investigated in relation to saturation headway, capacity, travel time, delay, and queue length in different lane groups of an intersection. A Python script code developed by Vissim is used to provide the communication between the signal controller and CVs and CAVs to adjust their speeds accordingly. The results show that increasing CV and CAV market-penetration rate reduces saturation headway and consequently increases capacity at signalized intersections. On the other hand, increasing the AV market-penetration rate deteriorates traffic operations. Results also indicate that the highest increase (80%) and decrease (20%) in lane-group capacity are observed respectively in a traffic stream of 100% CAVs and 100% AVs.
