簡易檢索 / 詳目顯示

回結果列表
研究生： 黃欣庭
Huang, Hsin-Ting
論文名稱： 無號誌路口機車駕駛者行為與風險感知分析
Analysis of Scooter Driver Behavior and Risk Perception at Unsignalized Intersections
指導教授： 魏健宏
Wei, Chien-Hung
學位類別： 碩士
Master
系所名稱： 管理學院 - 交通管理科學系
Department of Transportation and Communication Management Science
論文出版年： 2023
畢業學年度： 111
語文別： 中文
論文頁數： 123
中文關鍵詞： 無號誌路口 、駕駛行為 、路口停讓行為 、情境知覺量測技術 、情境知覺全面評估技術
外文關鍵詞： Unsignalized Intersections, Driving Behavior, Stop and Wait at Intersections, Situation Awareness Rating Technique, Situation Awareness Global Assessment Technique
相關次數： 點閱：145  下載：43 
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

    • 當車輛行經未設有交通號誌之交叉路口時，由於無號誌管制的狀況下，駕駛人對路口車流匯集處產生不確定性因素，容易造成交通衝突與混亂延滯情況，連帶輕易發生交通事故並成為肇事熱點。為解決無號誌管制路口之交通衝突問題，我國積極宣導車輛臨近路口之停讓運動，其為減少交通風險之關鍵駕駛行為，且各地交通局持續於無號誌路口中，推動設置標誌標線工程，以協助用路人建立路口停讓行為之正確觀念。警政署 111 年交通事故資料統計，無號誌路口總事故案數以機車最多，肇事占比高達五成一。本研究為瞭解機車駕駛者行駛於無號誌路口之駕駛行為，駕駛者是否執行停等或減速等動作，故必須進一步探討駕駛者於某一時間與空間內，對環境中各種相關元素之感知、對其意義理解以及不久後之狀態預測。
    本研究依據情境知覺（Situation Awareness, SA）架構進行問卷設計，利用三個級別之 SA 理論「個人對外在正在進行狀態之動態意識─感知、理解以及預測」，以具有系統性地研析出個人對環境資訊處理之認知與方法。實驗設計係透過情境知覺量測技術（Situation Awareness Rating Technique, SART）與情境知覺全面評估技術（Situation Awareness Global Assessment Technique, SAGAT）作情境建模，前者對駕駛者對於環境之不穩定性、複雜性以及變化性等，測量狀態下之主觀認知程度；後者以畫面凍結（Freeze Frame）作為實驗測驗方式，情境畫面暫停來詢問駕駛者對於狀態之客觀認知程度。兼採兩項技術以整體地評估駕駛者內心之感知、判斷與決策，將理論上正確之認知行為與實驗收集之問卷數據進行比較，了解並預測駕駛者對不同路口岔路形式、天候光線（日夜間）、混合車流組成與標誌標線完整性之因子條件下無號誌路口之決策行為，進一步分析各因子對駕駛者感知能力之重要程度。
    最後結果建議積極推動依每條道路路權來繪設標誌標線工程，提高駕駛者路口風險意識，俾使駕駛者行為、機動車輛與道路環境之間關係達到平衡協調之狀態。期望具顯著之風險因子能供作交通單位或管理機構改善措施之參考，最終達到無號誌路口交通安全短期目標─路口停讓行為，與長期目標─達到道路交通安全。

    The driver has uncertainties at intersection which is convergence of traffic flow due to the absence of signal control, and it is highly possible to lead to traffic conflicts and delays, which is likely to cause traffic accidents. To solve the problem of traffic conflicts, Taiwan advocates the driving behavior of stop and wait for approaching intersections, which is a key point for reducing traffic risks. According to the traffic accident data of the National Police Agency in 2022, scooters account for the largest number of accidents at unsignalized intersections (51%). To understand the scooter driving behavior at unsignalized intersections and whether drivers stopped or decelerated, it is necessary to explore the driver's perception of the elements in the environment, understanding of their meanings, and their future state predictions in a certain time and space.
    The questionnaire was designed by the framework of Situation Awareness (SA), and used the three-level SA "perception, understanding, and prediction" to systematically analyze personal perceptions to environmental information processing. The experimental design uses Situation Awareness Rating Technique (SART) and Situation Awareness Global Assessment Technique (SAGAT) for situational modeling. The former to measure the subjective perception of the environment state; the latter uses the Freeze Frame as an experimental test method to measure the objective perception. The technologies compare the theoretically correct cognitive behavior with the questionnaire data, and understand and predict the driver's decision-making for intersection configuration, time of day (day/night), composition of vehicle type, and completeness of road markings, and further analyzes the importance of each factor.
    The result suggests to actively promote setting up signs and markings in accordance with the road rights, to improve the driver's awareness of intersection, so that the relationship between driver's behavior, vehicle and environment can reach a coordinated state. Hoped that it can be used as a reference for the improvement measures of traffic management organization, and achieve the short-term goal of improving traffic safety - execution of stop and wait at unsignalized intersections, and the long-term goal - to achieve road traffic safety.

    第一章 緒論 1 1.1 研究背景與動機 1 1.2 研究目的 5 1.3 研究流程 7 第二章 文獻回顧 9 2.1 無號誌路口交通分析 9 2.1.1 無號誌路口定義與設置規定 9 2.1.2 無號誌路口基本交通特性 9 2.1.3 無號誌路口潛在交通風險 12 2.2 安全駕駛行為 14 2.2.1 防禦駕駛行為與觀念 15 2.2.2 路口停讓行為 16 2.3 風險感知 19 2.3.1 風險感知定義 19 2.3.2 風險感知測試 20 2.4 情境知覺 21 2.4.1 情境知覺三級模型 22 2.4.2 情境知覺量測技術（SART） 24 2.4.3 情境知覺全面評估技術（SAGAT） 27 2.4.4 SART與SAGAT之比較 29 2.5 道路安全之交通影像應用 30 2.5.1 我國交通影像教材案例 30 2.5.2 國外風險感知教材案例 32 2.6 小結 33 第三章 研究方法 34 3.1 情境知覺主要架構 34 3.1.1 SART問卷 35 3.1.2 SAGAT問卷 36 3.2 實驗設計 37 3.2.1 實驗目的與流程 37 3.2.2 實驗假設 39 3.2.3 模擬情境設計 40 3.2.4 影片素材蒐集 42 3.2.5 受測者背景與樣本數 43 3.3 資料分析方法 45 3.3.1 SART, SAGAT評估感知分數 47 3.3.2 變異數分析 47 3.3.3 獨立樣本 t 檢定 48 3.3.4 相關分析 49 3.3.5 多元線性迴歸分析 49 3.3.6 多重比較法 49 3.3.7 極值正規化 49 3.3.8 數值內插法 50 第四章 資料整理與分析 51 4.1 問卷測驗流程 51 4.2 樣本結構分析 53 4.2.1 問卷回收統計 53 4.2.2 受測者樣本結構 53 4.3 情境知覺感知分數基本分析 55 4.3.1 情境知覺感知分數敘述性統計 56 4.3.2 情境知覺感知分數差異檢定分析 57 4.3.3 駕駛行為感知值特性分析 58 4.3.4 主客觀感知值差異分析 62 4.4 無號誌路口風險因子評估 64 4.4.1 風險因子相關分析 64 4.4.2 風險因子影響駕駛感知分析 66 4.4.3 風險因子影響路口停讓行為分析 74 4.4.4 小結 79 4.5 無號誌路口情境推估模型 80 4.5.1 情境感知分數推估 80 4.5.2 全因子情境組合排名 81 4.6 無號誌路口主觀感知研析 84 4.6.1 標字標線組合分析 85 4.6.2 風險因子組合分析 87 4.7 建構駕駛感知分級模式 89 4.7.1 固定級距分級 89 4.7.2 固定比例分級 93 第五章 結論與建議 98 5.1 結論 98 5.2 建議 101 參考文獻 103 附錄一 情境知覺全面評估技術問卷 (SAGAT) 107 附錄二 情境知覺量測技術問卷 (SART) 116 附錄三 實驗模擬情境影片 119

    1. 內政部警政署警政統計查詢網，擷取時間：2023年04月10日，網址：https://ba.npa.gov.tw/npa/stmain.jsp?sys=100。
    2. 公路總局機車危險感知教育平台，擷取時間：2022年10月18日，網址：https://hpt.thb.gov.tw/。
    3. 交通部運輸研究所（2011），2011 年臺灣公路容量手冊。
    4. 交通部運輸研究所（2021），探討非號誌化路口之道路交通標線繪設方式
    5. 交通部統計查詢網站，擷取時間：2022年10月08日，網址：https://stat.motc.gov.tw/mocdb/stmain.jsp?sys=100&funid=a3301。
    6. 芳賀繁（2006），安全運転に必要なスキルは何か，交通事故防止の心理学(1)~(6)，交通サミット北海道。
    7. 美國汽車協會 How to Drive 訓練課程，擷取時間：2022年10月25日，網址：https://drivertraining.aaa.biz/。
    8. 財團法人車輛研究測試中心（2006），防禦駕駛教戰手冊。
    9. 財團法人車輛研究測試中心（2018），汽車防禦駕駛手冊。
    10. 道路交通標誌標線號誌設置規則（1968）。
    11. 道路交通安全規則（1968）。
    12. Advani, M., Gupta, N. J., Velmurugan, S., Madhu, E., & Chandra, S. (2020). Defining and analyzing forceful gap behavior at unsignalized intersections. Transportation research record, 2674(8), 420-428.
    13. Ashalatha, R., & Chandra, S. (2011). Service delay analysis at TWSC intersections through simulation. KSCE Journal of Civil Engineering, 15(2), 413-425.
    14. Beanland, V., Goode, N., Salmon, P. M., & Lenné, M. G. (2013). Is there a case for driver training? A review of the efficacy of pre-and post-licence driver training. Safety science, 51(1), 127-137.
    15. Bell, H. H., & Lyon, D. R. (2000). Using observer ratings to assess situation awareness. Situation awareness analysis and measurement, 129-146.
    16. Benda, H. V., & Hoyos, C. G. (1983). Estimating hazards in traffic situations. Accident Analysis & Prevention, 15(1), 1-9.
    17. Borowsky, A., Shinar, D., & Oron-Gilad, T. (2010). Age, skill, and hazard perception in driving. Accident Analysis & Prevention, 42(4), 1240-1249.
    18. Castro, C., Ventsislavova, P., Peña-Suarez, E., Gugliotta, A., Garcia-Fernandez, P., Eisman, E., & Crundall, D. (2016). Proactive listening to a training commentary improves hazard prediction. Safety science, 82, 144-154.
    19. Cheng, A. S., Ng, T. C., & Lee, H. C. (2011). A comparison of the hazard perception ability of accident-involved and accident-free motorcycle riders. Accident Analysis & Prevention, 43(4), 1464-1471.
    20. Crundall, D., Andrews, B., Van Loon, E., & Chapman, P. (2010). Commentary training improves responsiveness to hazards in a driving simulator. Accident Analysis & Prevention, 42(6), 2117-2124.
    21. Crundall, D. (2016). Hazard prediction discriminates between novice and experienced drivers. Accident Analysis & Prevention, 86, 47-58.
    22. Elander, J., West, R., & French, D. (1993). Behavioral correlates of individual differences in road-traffic crash risk: An examination of methods and findings. Psychological bulletin, 113(2), 279.
    23. Endsley, M. R. (1993). A survey of situation awareness requirements in air-to-air combat fighters. The International Journal of Aviation Psychology, 3(2), 157-168.
    24. Endsley, M. R., & Bolstad, C. A. (1994). Individual differences in pilot situation awareness. The International Journal of Aviation Psychology, 4(3), 241-264.
    25. Endsley, M. R. (1995a). Toward a theory of situation awareness in dynamic-systems. Human Factors, 37(1), 32-64
    26. Endsley, M. R. (1995b). A taxonomy of situation awareness errors. Human factors in aviation operations, 3(2), 287-292.
    27. Endsley, M. R., & Garland, D. J. (Eds.). (2000). Situation awareness analysis and measurement. CRC Press.
    28. Endsley, M. R. (2021). A systematic review and meta-analysis of direct objective measures of situation awareness: a comparison of SAGAT and SPAM. Human factors, 63(1), 124-150.
    29. Feng, J., Choi, H., Craik, F. I., Levine, B., Moreno, S., Naglie, G., & Zhu, M. (2018). Adaptive response criteria in road hazard detection among older drivers. Traffic injury prevention, 19(2), 141-146.
    30. Fisher, D. L., Laurie, N. E., Glaser, R., Connerney, K., Pollatsek, A., Duffy, S. A., & Brock, J. (2002). Use of a fixed-base driving simulator to evaluate the effects of experience and PC-based risk awareness training on drivers' decisions. Human factors, 44(2), 287-302.
    31. Grayson, G. B., Maycock, G., Groeger, J. A., Hammond, S. M., & Field, D. T. (2003). Risk, hazard perception and perceived control. Crowthorne, Berkshire: TRL Limited
    32. Horswill, M. S., & Helman, S. (2003). A behavioral comparison between motorcyclists and a matched group of non-motorcycling car drivers: factors influencing accident risk. Accident Analysis & Prevention, 35(4), 589-597.
    33. Horswill, M. S., Waylen, A. E., & Tofield, M. I. (2004). Drivers' Ratings of Different Components of Their Own Driving Skill: A Greater Illusion of Superiority for Skills that Relate to Accident Involvement. Journal of Applied Social Psychology, 34(1), 177-195.
    34. Horswill, M. S., Hill, A., & Wetton, M. (2015). Can a video-based hazard perception test used for driver licensing predict crash involvement?. Accident Analysis & Prevention, 82, 213-219.
    35. Horswill, M. S. (2016). Improving fitness to drive: The case for hazard perception training. Australian Psychologist, 51(3), 173-181.
    36. Jackson, L., Chapman, P., & Crundall, D. (2009). What happens next? Predicting other road users' behaviour as a function of driving experience and processing time. Ergonomics, 52(2), 154-164.
    37. Jones, D. G., & Endsley, M. R. (1996). Sources of situation awareness errors in aviation. Aviation, space, and environmental medicine, 67(6), 507-512.
    38. Laberge, J. C., Creaser, J. I., Rakauskas, M. E., & Ward, N. J. (2006). Design of an intersection decision support (IDS) interface to reduce crashes at rural stop-controlled intersections. Transportation Research Part C: Emerging Technologies, 14(1), 39-56.
    39. Lee, S. E., Klauer, S. G., Olsen, E. C., Simons-Morton, B. G., Dingus, T. A., Ramsey, D. J., & Ouimet, M. C. (2008). Detection of road hazards by novice teen and experienced adult drivers. Transportation research record, 2078(1), 26-32.
    40. Liu, C. C., Hosking, S. G., & Lenné, M. G. (2009). Hazard perception abilities of experienced and novice motorcyclists: An interactive simulator experiment. Transportation research part F: traffic psychology and behaviour, 12(4), 325-334.
    41. Mckenna, F. P., & Crick, J. L. (1994). Hazard perception in drivers: A methodology for testing and training. TRL contractor report, (313).
    42. Mckenna, F. P., & Crick, J. L. (1997). Developments in hazard perception. Crowthorne, UK: Transport Research Laboratory.
    43. McKnight, A. J., & McKnight, A. S. (2003). Young novice drivers: careless or clueless?. Accident Analysis & Prevention, 35(6), 921-925.
    44. Moran, C., Bennett, J. M., & Prabhakharan, P. (2019). Road user hazard perception tests: A systematic review of current methodologies. Accident Analysis & Prevention, 129, 309-333.
    45. Naito, A., Miyajima, C., Nishino, T., Kitaoka, N., & Takeda, K. (2009). Driver evaluation based on classification of rapid decelerating patterns. In 2009 IEEE International Conference on Vehicular Electronics and Safety (ICVES), 108-112.
    46. Patil, G. R., & Pawar, D. S. (2014). Temporal and spatial gap acceptance for minor road at uncontrolled intersections in India. Transportation Research Record, 2461(1), 129-136.
    47. Paul, M., & Ghosh, I. (2018). Speed-based proximal indicator for right-turn crashes at unsignalized intersections in India. Journal of Transportation Engineering, Part A: Systems, 144(6), 04018024.
    48. Salmon, P. M., Stanton, N. A., Walker, G. H., Jenkins, D., Ladva, D., Rafferty, L., & Young, M. (2009). Measuring Situation Awareness in complex systems: Comparison of measures study. International Journal of Industrial Ergonomics, 39(3), 490-500.
    49. Salmon, P. M., Lenne, M. G., Walker, G. H., Stanton, N. A., & Filtness, A. (2014). Exploring schema-driven differences in situation awareness between road users: an on-road study of driver, cyclist and motorcyclist situation awareness. Ergonomics, 57(2), 191-209.
    50. Schulz, C. M., Endsley, M. R., Kochs, E. F., Gelb, A. W., & Wagner, K. J. (2013). Situation awareness in anesthesia: concept and research. The Journal of the American Society of Anesthesiologists, 118(3), 729-742.
    51. Scialfa, C. T., Borkenhagen, D., Lyon, J., Deschênes, M., Horswill, M., & Wetton, M. (2012). The effects of driving experience on responses to a static hazard perception test. Accident Analysis & Prevention, 45, 547-553.
    52. Smith, K., & Hancock, P. A. (1995). Situation awareness is adaptive, externally directed consciousness. Human factors, 37(1), 137-148.
    53. Taylor, R. M. (1990). Situational Awareness Rating Technique (SART): The development of a tool for aircrew systems design. AGARD, Situational Awareness in Aerospace Operations 17p(SEE N 90-28972 23-53)
    54. Underwood, G., Phelps, N., Wright, C., Van Loon, E., & Galpin, A. (2005). Eye fixation scanpaths of younger and older drivers in a hazard perception task. Ophthalmic and Physiological Optics, 25(4), 346-356.
    55. Vlakveld, W. P. (2014). A comparative study of two desktop hazard perception tasks suitable for mass testing in which scores are not based on response latencies. Transportation research part F: traffic psychology and behaviour, 22, 218-231.
    56. Wang, X., & Abdel-Aty, M. (2008). Modeling left-turn crash occurrence at signalized intersections by conflicting patterns. Accident Analysis & Prevention, 40(1), 76-88.
    57. Wetton, M. A., Hill, A., & Horswill, M. S. (2013). Are what happens next exercises and self-generated commentaries useful additions to hazard perception training for novice drivers?. Accident Analysis & Prevention, 54, 57-66.
    58. Wong, S. C., Sze, N. N., & Li, Y. C. (2007). Contributory factors to traffic crashes at signalized intersections in Hong Kong. Accident Analysis & Prevention, 39(6), 1107-1113.
    59. Yan, X., Radwan, E., & Abdel-Aty, M. (2005). Characteristics of rear-end accidents at signalized intersections using multiple logistic regression model. Accident Analysis & Prevention, 37(6), 983-995.

    下載圖示 校內：立即公開
    校外：立即公開
    QR CODE