車載系統開發-猶豫區間警示演算法之研究

Real-Time Onboard Warning Algorithms for Dilemma Zone Prevention

游上民(Shang-Min Yu)

指導教授 ： 張堂賢

國立臺灣大學/工學院/土木工程學研究所/博士(2011年)

https://doi.org/10.6342/NTU.2011.00748

摘要

號誌時制之設計乃為提供用路人安全與效率之交通環境，然而綠燈轉換時間之不當設計，卻可能產生猶豫區間因而提高路口肇事風險。為避免駕駛者於接近號誌化路口時落入猶豫區間，自1960年代開始，已有多位交通學者投入號誌轉換時間之研究，其中Gazis, Herman及Maradudin所提出之轉換時間設計方法被ITE手冊採用並廣泛應用於號誌時制設計。但由於實際交通環境相當複雜，此種方法只能保證在特定道路幾何線型條件與特定駕駛速率下，駕駛者接近號誌化路口時不會進入猶豫區間，而當駕駛環境超出理想狀況時，駕駛者仍然有陷入猶豫區間之風險。
為了降低駕駛者落入猶豫區間之風險，傳統做法乃是增加黃燈時間長度，以使駕駛者有足夠反應與緩衝時間安全通過路口。然而增加黃燈時間代表增加損失時間，將降低號誌化路口容量，造成號誌運行效率降低，伴隨著更多車輛延滯、車輛停等、廢氣汙染與能源消耗等負面效應。反之若減少黃燈時間雖可提高號誌化路口運行效率，但卻可能增加駕駛者落入猶豫區間風險，犧牲用路人安全。因此交通工程師設計黃燈時間時，經常必須於安全與效率間進行取捨，往往難以同時兼顧效率與安全。有鑑於此，實有必要在現有轉換時間設計情況下，針對如何避免駕駛者落入猶豫區間進行研究與分析，以不犧牲現有號誌運行效率為前提，盡可能提高路口安全性。
自車路整合(Vehicle Infrastructure Integration, VII)之概念被提出後，車路整合相關技術已趨於成熟，而在智慧駕駛環境下，行駛車輛不但可取得自身資訊(位置、速率、加速率)，亦可獲得環境資訊(如：道路坡度、號誌時制資訊等)，於此環境下應可建立更即時而準確之猶豫區間警示方法。本研究即以此為目標，利用結合最佳化方法之卡曼濾波器預測車輛運動狀態，並整合猶豫區間計算模式，建立一套可即時運算之演算法，藉此及時提供駕駛者適當警示資訊。
為瞭解警示演算法是否可有效即時執行，並檢驗演算法提供之警示訊息是否符合實際情況，因此本研究設計可執行演算法之程式架構，利用Java程式語言加以實作，根據所設定之模擬情境與實驗設計進行模擬實驗，證實只要取得相關參數，演算法可即時預測與判斷黃燈始亮時，車輛是否可能落入猶豫區間或清道區間，結果亦顯示演算法之判斷邏輯可正確而可靠地提供駕駛者警示資訊。此外使用者可根據適用環境分析結果，針對所需警示正確率，以及車輛所處道路之速限，選擇適當設計參數(觸發距離)。
本研究除了自行設計模擬實驗外，為求謹慎與更具說服力的實驗結果，並利用微觀車流模擬軟體VISSIM進行實驗與測試。結果顯示相較於以等速方法推算猶豫區間，研究中設計之警示演算法確實具有較好的預測與警示能力。

關鍵字

智慧駕駛 ； 車輛安全 ； 猶豫區間 ； 基因演算法 ； 卡曼濾波器

並列摘要

Due to inappropriate intergreen interval, the dilemma zone (DZ) has been identified as a critical issue in vehicle safety, because it might lead drivers to make incorrect decisions and causes potential risks of rear-end or right-angle accidents.
In practice, the Gazis, Herman and Maradudin (GHM) model is commonly used by traffic engineers to design intergreen to prevent the formation of the DZ. According to the yellow change interval formula proposed in the ITE handbook, the designed yellow change interval is supposed to allow an approaching vehicle moving at a constant speed to either safely stop or clear the intersection. Thus, the DZ is not supposed to happen. In reality, the DZ is difficult to be eliminated due to its dynamic features of location and length, resulting from a variety of drivers’ behavior and characteristics. Hence, current implementation of yellow change intervals still has a potential to form a DZ if a vehicle approaches an intersection at a speed higher than that identified in the ITE formulation. As a result, the static ITE approach might be less helpful for removing DZs.
The traditional concept for inter-green interval design would force traffic engineers to face the trade-off between the vehicle safety and operational efficiency of traffic signals at signalized intersections. Besides, the dynamic feature of dilemma zones cannot be effectively captured by the traditional approaches. A new approach that can improve the vehicle safety without diminishing existing efficiency is desired. Therefore, based on the concept of VII (Vehicle Infrastructure Integration)/connected vehicle, this study aims to develop a series of warning algorithms (WAs) for onboard advanced dilemma zone warning system to handle the dilemma zone problem in real-time. These algorithms are designed for the connected (VII-ready) vehicle to dynamically determine dilemma zones and provide drivers with proper warnings. To increase detection accuracy for dilemma zone, inputs from roadways, drivers and vehicles are considered. Besides, in order to capture the dynamical feature of DZ, a genetic systematic rule improving the prediction capacity of the Kalman filter is integrated into the warning algorithms.
The algorithms are tested by simulation with a variety of scenarios to demonstrate system reliability and performance. The results show the reliability and operating practicability of the proposed algorithms. Furthermore, the warning accuracy contour plot designed in this study also provides an effective way to assist users or system designers in determining the critical parameters of the algorithms for future implementations.

並列關鍵字

Connected Vehicle ； Vehicle Safety ； Dilemma Zone ； Genetic Algorithms ； Kalman Filter

參考文獻

59. 張堂賢，黃宏仁(2008)，車輛偵測器資料漏失之在線差補技術研究，運輸學刊，第二十卷，第四期，第300-320頁。

3. Gazis, D., Herman, R., and Maradudin, A. (1960). The problem of the amber signal light in traffic flow. Operations Research, 8(1), p. 112-132.

7. Williams, W. L. (1977). Driver behavior during the yellow interval (abridgment). Transportation Research Record(644), p. 75-78.

11. Lin, F. B., and Vijaykumar, S. (1988). Timing design of signal change interval. Traffic Engineering & Control, 29(10), p. 531-536.

16. 許書耕、藍武王(2007)，不同車輛到達型態之黃燈需時研究，運輸計劃季刊，第三十六卷，第二期，第209-230頁。