造成交通事故的因素大致可區分為人為、設備、天氣、路況等，根據臺灣國道高速公路局的統計，「不當駕駛」－包括「變換車道不當」及「未注意車前狀態」－是造成交通事故的最主要原因，意即「人」（駕駛）終究是車禍事件的最關鍵因素。為了彌補駕駛的能力限制，近年來先進駕駛輔助系統（Advanced Driver Assistance System, ADAS）廣為各車廠積極發展，出發點是為了幫助駕駛能更快速地得到資訊、做出更正確的決策，但大量的資訊可能會超出人類訊息處理的極限，導致處理時間增長、判斷錯誤。因此，本研究旨在探討駕駛輔助系統的警示時間點對於駕駛績效與安全性的影響，並分析性別差異與駕駛決策間的關係，期能透過相應的改善，達到有效提醒駕駛、避免事故發生之目的。
本研究利用Unity 3D模擬行駛於高速公路、左側旁車欲切換至目前所在車道前方之路況，探討不同的警示時間點是否造成駕駛行為之差異。共招募20位（男、女各10位）介於20至26歲、具有兩年以上駕駛經驗、且行駛於高速公路的頻率為一週至少一次或一個月內至少有一次連續三至四天駕駛行為的本國國民，為了排除過於保守及冒險之駕駛，其駕駛憤怒量表（Driving Anger Scale）填答分數需介於41至53分。研究參與者先進行一組沒有任何輔助的任務做為個人的基準參考值，接著進行有輔助系統的三組任務，其警示時間點分別為碰撞發生前2.5秒、3.0秒、3.5秒，順序為隨機安排。每位研究參與者全程共要完成四組駕駛任務，每組任務中皆會透過C#撰寫之程式蒐集剎車與油門踏板的幅度以及兩車的絕對座標，以用於定義及計算出駕駛之執行任務正確率、碰撞次數、反應時間、緩衝時間（在可能碰撞的前幾秒做出反應）等客觀反應參數；另要求研究參與者在每組任務結束後立即填寫NASA工作負荷指標（Task Load Index）量表，隨後再稍做休息。最後進行二因子變異數分析（Two-Way ANOVA）以瞭解性別與警示時間點對於任務執行正確率、碰撞次數、反應時間、以及心智負荷等績效指標有無顯著影響，並觀察兩因子之間的交互作用，亦即男性與女性駕駛是否有各自的最佳警示時間點。
結果顯示：不同提醒時間點之下的任務執行正確率並無顯著差異，駕駛的個別差異可能才是影響駕駛穩定度之關鍵；但提醒時間點的早晚會影響駕駛對系統的信任程度，進而反映在駕駛行為上，造成緩衝時間與工作負荷之差異。其中當駕駛面對在碰撞前3.5秒即出現的警示可獲得最長的緩衝時間以及最低的工作負荷；此外，男性駕駛之任務執行正確率較女性高，具有較高之穩定性，女性則有較長之緩衝時間，亦即能更早在碰撞前就達到安全之狀態，並有較多時間為下個狀況做準備，但男、女性駕駛之工作負荷並沒有顯著差異。
整體而言，駕駛對於車內輔助系統的信任程度為影響此系統是否能有效輔助駕駛之關鍵因素，因此，輔助系統之設計宜以「提醒出現時間點是否符合駕駛本身預期且不與其認知衝突」為首要重點，當駕駛對系統之自覺信任程度愈高，其愈能有效地協助駕駛縮短判斷路況所需的時間，提升決策品質與駕駛安全。此外，由於女性較為信任且依賴車內輔助系統，其績效也較男性來得好，因此未來設計應以如何強化男性對於系統之信賴程度為改善方向，以便更廣泛地協助提昇駕駛績效。

The common causes of traffic accidents include humans, equipment, weather, and road conditions. According to the statistics of Taiwan National Freeway Bureau, improper driving, including "improper lane changing" and "ignoring the state of front vehicle," is the main cause of traffic accidents. In other words, human (driver) is the most critical factor of traffic accidents. In order to compensate for the limitations of driver's abilities, the Advanced Driver Assistance System (ADAS) has been developed rapidly. The purpose of such a system is to help the driver receive information more rapidly and make decisions more accurately. However, a larger amount of information may be beyond the limit of human information processing, resulting in increased processing time and incorrect judgments. Thus, the purpose of this study is to investigate the effect of warning timing of driving assistance system on driving performance and safety, as well as analyzing the relationship between driver’s gender and decisions made. Through the corresponding improvements that help clearly remind the drivers, traffic accidents can be reduced effectively.
In this study, Unity 3D was used to simulate vehicle operations on a highway in which the vehicle on the left-side lane plans to change lane and drive in front of the participant, so as to analyze how the warning timing of driving assistance system may influence the driving behavior. Twenty participants (10 males and 10 females) ranging from 20 to 26 years old who drive on the highway at least once a week or drive for 3 to 4 days continuously for at least one time in a month and with the driving experience of more than two years were recruited. Besides, their scores of Driving Anger Sale have to be between 41 and 53 (out of 70) for excluding those who are too conservative and too risky. Each participant was asked to perform a series of tasks without warning system as his/her baseline, and then perform three sessions of tasks with the warning system in which the warning timing is set at 2.5 seconds, 3.0 seconds, and 3.5 seconds prior to the potential collision respectively. The three sessions were arranged randomly to reduce the effect of learning and fatigue. Each participant needs to complete four sessions of tasks in total, with the NASA-TLX survey conducted after each session and followed by a 5-minute rest. The experimenter will define and calculate the success rate of task execution, error counts, and reaction time through using C# program to collect the range of brake, accelerator pedal range, and the absolute coordinates of the two cars during the experiment. After that, the effects of warning timing and driver’s gender on the correct rate of task execution, error counts, reaction time, buffer time (the duration from the moment that drivers take the reaction to the potential collision), and workload were evaluated by Two-Way ANOVA (Analysis of Variance).In other words, it was observed whether male and female drivers have each’s recommended warning timing.
The results showed that there is no significant difference between the drivers' success rate of task execution at different timing of warning. The difference among drivers could be the main factor to affect the drivers' stability. The timing of warning will affect the driver’s degree of trust toward the system, and hence affect the driving behavior. More specifically, the drivers had the longest buffer time and the lowest workload at the warning timing which is set at 3.5 seconds prior to the potential collision. Male participants' success rate of task execution is higher than that of female participants, which indicates that males tend to have better stability while driving. However, females had longer buffer time, which allows them to reach the safe status more quickly before the potential collision. This hence given them more time to prepare for other unexpected situations. Further, there is no difference in workload between males and females: So, the driver’s gender could not be a main factor affecting the drivers' workload.
Overall, the driver’s perceived trust toward the driving assistance system is a key factor for judging whether the system can assist drivers effectively. Hence, while designing a driving assistance system, it is necessary to focus on whether the timing of warning matches the drivers' expectation without conflict. In this way, a higher degree of trust in the driving assistance system can effectively help drivers reduce the time required for dealing with unexpected traffic conditions, resulting in enhanced quality of decision making and safety. In addition, females tend to trust and depend on the system more than males do, which contributes to the better performance. Future improvement of the design should be focused on how to increase the males' degree of trust toward the system, so as to enhance the males' driving performance as well.

中文
1. 中華民國交通部（民104年）。自用小客車駕駛人男女比率。
2. 中華民國內政部警政署（民105年03月01日）。道路交通事故(A1類)死亡人數－按性別及年齡別分。取自https://www.npa.gov.tw/NPAGip/wSite/lp?ct
Node=12873&nowPage=4&pagesize=15
3. 台灣國道高速公路局（民96年）。高速公路噪音潛勢分析與防制措施之研究。
4. 台中市政府警察局（民99年10月27日）。交通安全宣導－行人安全守則。取自http://www.police.taichung.gov.tw/TCPBWeb/wSite/ct?xItem=10647&
ctNode=479&mp=pda
5. 台灣國道高速公路局（民103年07月24日）。交通安全資訊－交通事故分析。取自http://www.freeway.gov.tw/Publish.aspx?cnid=516&p=128
6. 交通部運輸研究所（民103年08月22日）。一年車禍損失約4,750億!。取自http://www.motc.gov.tw/ch/index.jsp
7. 台灣國道高速公路局（民104）。103年國道事故檢討分析報告。
8. 邱士軒（民96年）。性別及年齡差異對汽車駕駛的情境知覺之影響。碩士論文。
9. 吳欣潔、林清同、簡廷諺、羅羽辰（民99年）。車內導航顯示格式對駕駛績效及安全性之影響。第17屆中華民國人因工程學會年會暨研討會。
10. 中華民國交通部（民100年4月13日）。國內公路路線設計規範。取自
http://www.motc.gov.tw/ch/home.jsp?id=740&parentpath
=0,2,738&mcustomize=divpubreg_view.jsp&dataserno=362&aplistdn
=ou=data,ou=divpubreg,ou=ap_root,o=motc,c=tw&toolsflag=Y&imgfolder=img/standard
11. 黃俊仁（民97年）。車輛前方防撞警示系統及其對於駕駛績效影響之研究。
12. 曾平毅、黃益三、姜心怡（民90年9月）。不同年齡層汽車駕駛人事故風險分析。年國際道路交通安全與執法研討會（民90年9月）。
13. 廖哲聖（2009）。憤怒駕駛傾向之量測與人格特質及性別角色之影響。國立交通大學運輸科技與管理學系碩士論文。
14. 謝孟真（2014）。美國國家航空暨太空總署工作心智負荷指標之中文化與信效度初探。長庚大學護理學系碩士論文。

英文
1. American Association of State Highway and Transportation Officials (1984). A Policy on Geometric Design of Highways and Streets. Washington, D.C.: AASHTO.
2. Abe, Genya and Richardson, John (2004). The effect of alarm timing on driver behaviour: an investigation of differences in driver trust and response to alarms according to alarm timing. Transportation Research Part F: Traffic Psychology and Behaviour, 7(4), 307–322.
3. Abe, Genya and Richardson, John (2006). Alarm timing, trust and driver expectation for forward collision warning systems. Applied ergonomics, 37(5), 577–586.
4. Bertollini, Gary P., Johnston, Charles M., Kuiper, James W., Kukula, James C., Kulczycka, Malgorzata A., and Thomas, William E. (1994). The general motors driving simulator (No. 940179). SAE Technical Paper.
5. Baldock, Matthew R.J. and McLean, Jack (2005). Older Drivers: Crash Involvement Rates and Causes. Centre for Automotive Safety Research, The University of Adelaide, South Australia
6. Burke, Jennifer L., Prewett, Matthew S., Gray, Ashley A., Yang, Liuquin, Stilson, Frederick R.B., Redden, Elizabeth, Coovert, Michael D., and Elliot, Linda R. (2006). Comparing the effects of visual-auditory and visual-tactile feedback on user performance: A meta-analysis. In Proceedings of the ACM 8th International Conference on Multimodal Interfaces, Banff, Canada.
7. Chang, Myung S., Messer, Carroll J., and Santiago, Alberto J. (1985). Timing traffic signal change intervals based on driver behavior (HS-040 068).
8. Campbell, John L., Richard, Christian M., Brown, James L., and McCallum, Marvin (2007). Crash warning system interfaces: human factors insights and lessons learned. NHTSA report (HS-810 697).
9. DeJoy, David M. (1992). An examination of gender differences in traffic accident risk perception. Accident Analysis & Prevention, 24(3), 237–246.
10. Deffenbacher, Jerry L., Oetting, Eugene R., and Lynch, Rebekah S. (1994). Development of a driving anger scale. Psychological reports, 74(1), 83–91.
11. D’Addario, Pamela M., Donmez, Birsen, and Ising, Kurt W. (2014). EMG provides an earlier glimpse into the effects of cognitive distraction on brake motor response. In Proceedings of the Human Factors and Ergonomics Society 58th Annual Meeting. DOI 10.1177/1541931214581462.
12. Do, Quoc H., Tehrani, Hossein, Mita, Seiichi, Egawa, Masumi, Muto, Kenji and Yoneda, Keisuke (2017). Human Drivers Based Active-Passive Model for Automated Lane Change. IEEE Intelligent Transportation Systems Magazine, 9(1), 42－56.
13. Fillmore, Mark T., Blackburn, Jaime S., and Harrison, Emily L.R. (2008). Acute disinhibiting effects of alcohol as a factor in risky driving behavior. Drug and alcohol dependence, 95(1), 97–106.
14. Gao, Zhenhai, Li, Chuzhao, Hu, Hongyu, Zhao, Hui, Chen, Chaoyang, and Yu, Huili (2015). Experimal study of young male drivers’ responses to vehicle collision using EMG of lower extremity. Bio-medical Materials and Engineering, 26(s1), S563-S573.
15. Hancock, P.A. and Verwey, Willem B. (1997). Fatigue, workload and adaptive driver systems. Accident Analysis & Prevention, 29(4), 495–506.
16. Hansen, Ellen B. and Breivik, Gunnar (2001). Sensation seeking as a predictor of positive and negative risk behaviour among adolescents. Personality and individual differences, 30(4), 627–640.
17. Jonsson, Ing-Marie, Harris, Helen, and Nass, Clifford (2008). How accurate must an in-car information system be?: consequences of accurate and inaccurate information in cars. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1665–1674). ACM.
18. Knipling, R.R., Mironer, M., Hendriks, D.L., Tijerina, L., Everson, J., Allen, J.C., and Wilson, C. (1993). Assessment of IVHS countermeasures for collision avoidance: Rear-end crashes (DOT HS 807 995). National Highway Traffic Safety Administration.
19. Kaptein, Nico, Theeuwes, Jan, and Van Der Horst, Richard (1996). Driving simulator validity: Some considerations. Transportation Research Record: Journal of the Transportation Research Board, (1550), 30–36
20. Kiefer, R., LeBlanc, D., Palmer, M., Salinger, J., Deering, R., and Shulman, M. (1999). Development and validation of functional definitions and evaluation procedures for collision warning/avoidance systems (DTNH22-95-H-07301). Washington DC: National Highway Traffic Safety Administration.
21. Kantowitz, B. H., and Simsek, O. (2001). Secondary-task measures of driver workload. Stress, workload and fatigue.
22. Kim, Hyeonggeun Munand Gyoungeun and Kim, Byeongwoo (2016). Study on V2V communication based Lateral Collision Risk. International Journal of Applied Engineering Research, 11(2), 1094－1098.
23. Lee, Allan Y. (1996). Performance of driver-vehicle in aborted lane change maneuvers (No. 960516). SAE Technical Paper.
24. Lajunen, Timo and Parker, Dianne (2001). Are aggressive people aggressive drivers? A study of the relationship between self-reported general aggressiveness, driver anger and aggressive driving. Accident Analysis & Prevention, 33(2), 243–255.
25. Lee, John D. and Caven, Brent (2001). Speech-Based Interaction with In-Vehicle Computers: The Effect of Speech-Based E-Mail on Drivers’ Attention to the Roadway. Human Factors and Ergonomics Society, 43(4), 631–640.
26. Lee, John D., McGehee, Daniel V., Brown, Timothy L., and Reyes, M. L. (2002). Collision warning timing, driver distraction, and driver response to imminent rear-end collisions in a high-fidelity driving simulator. Human Factors and Ergonomics Society, 44(2), 314–334.
27. Lee, John D., Hoffman, Joshua D., and Hayes, Elizabeth. (2004). Collision warning design to mitigate driver distraction. In Proceedings of the SIGCHI Conference on Human factors in Computing Systems. 65–72.
28. Lerner, Neil, Robinson, Emanuel, Singer, Jeremiah, Jenness, James, Huey, Richard, Baldwin, Carryl, and Fitch, Gregory (2014). Human factors for connected vehicles: Effective warning interface research findings (DOT HS 812 068). National Highway Traffic Safety Administration.
29. McLean, John R., & Hoffmann, Errol R. (1975). Steering reversals as a measure of driver performance and steering task difficulty. Human Factors: The Journal of the Human Factors and Ergonomics Society, 17(3), 248–256.
30. McKnight, A.James, and McKnight, A.Scott (2003). Young novice drivers: careless or clueless? Accident Analysis & Prevention, 35(6), 921–925.
31. Misener, James A., Sengupta, Raja, and Krishnan, Hariharan (2005, November). Cooperative collision warning: Enabling crash avoidance with wireless technology. In 12th World Congress on ITS (Vol. 3).
32. Musselwhite, Charles (2006). Attitudes towards vehicle driving behaviour: Categorising and contextualising risk. Accident Analysis & Prevention, 38(2), 324–334.
33. Ma, Xiaoliang and Andréasson, Ingmar (2006). Estimation of driver reaction time from car-following data: application in evaluation of general motor-type model.
34. NASA Human Performance Research Group (1987). Task Load Index (NASA-TLX) v1. 0. NASA Ames Research Centre.
35. Petzoldt, Tibor, Bär, Nina, and Krems, Josef F. (2009). Gender effects on lane change test (LCT) performance. In Proceedings of the 5th international driving symposium on human factors in driver assessment, training, and vehicle design. 90–96.
36. Roberts, K.M. (1980). The FHWA highway driving simulator. Public Roads 44(3).
37. Rumar, K. (1990). The basic driver error: late detection. Ergonomics, 33(10-11), 1281–1290.
38. Reason, James, Manstead, Antony, Stradling, Stephen, Baxter, James, and Campbell, Karen (1990). Errors and violations on the roads: a real distinction? Ergonomics, 33(10-11), 1315–1332.
39. Rydstedt, Leif W., Johansson, Gunn, and Evans, Gary W. (1998). A longitudinal study of workload, health and well‐being among male and female urban bus drivers. Journal of occupational and organizational psychology, 71(1), 35–45.
40. Reed, Matthew P. and Green, Pual A. (1999). Comparison of driving performance on-road and in a low-cost simulator using a concurrent telephone dialling task. Ergonomics, 42(8), 1015–1037.
41. Reymond, Gilles, Kemeny, Andras, Droulez, Jacques, and Berthoz, Alain (2001). Role of lateral acceleration in curve driving: Driver model and experiments on a real vehicle and a driving simulator. Human Factors: The Journal of the Human Factors and Ergonomics Society, 43(3), 483–495.
42. Rhodes, Nancy and Pivik, Kelly (2011). Age and gender differences in risky driving: The roles of positive affect and risk perception. Accident Analysis & Prevention, 43(3), 923–931.
43. Selcon, S. J., Taylor, R. M., and McKenna, F. P. (1995). Integrating multiple information sources: Using redundancy in the design of warnings. Ergonomics, 38(11), 2362–2370.
44. Sarno, Kenneth J. and Wickens, Christopher D. (1995). Role of multiple resources in predicting time-sharing efficiency: Evaluation of three workload models in a multiple-task setting. The International Journal of Aviation Psychology, 5(1), 107–130.
45. Suzuki, Keisuke and Jansson, Hakan (2003). An analysis of driver’s steering behavior during auditory or haptic warnings for the designing of lane departure warning system. Society of Automotive Engineers of Japan Review, 24(1), 65–70.
46. Sarkar, Sheila and Andreas, Marie (2004). Acceptance of and engagement in risky driving behaviors by teenagers. Adolescence, 39(156), 687.
47. Taoka, George T. (1989). Brake reaction times of unalerted drivers. Institute of Transportation Engineers, 59(3), 19–21.
48. Talmadge, S., Chu, R., Eberhard, C., Jordan, K., & Moffa, P. (2000). Development of performance specifications for collisions avoidance systems for lane change crashes (No. HS-809 414,).
49. Tanaka, J., Ishida, S., Kawagoe, H., & Kondo, S. (2000). Workload of using a driver assistance system. In Intelligent Transportation Systems, 2000. Proceedings. IEEE (pp. 382-386). IEEE.
50. Tan, Han-Shue and Huang, Jihua (2006). DGPS-based vehicle-to-vehicle cooperative collision warning: Engineering feasibility viewpoints. IEEE Transactions on Intelligent Transportation Systems, 7(4), 415–428.
51. Ting, Ping-Huang, Hwang, Jiun-Ren, Doong, Ji-Liang, and Jeng, Ming-Chang (2008). Driver fatigue and highway driving: A simulator study. Physiology & Behavior, 94(3), 448–453.
52. Wickens, Christopher. D. (1984) Engineering psychology & human performance. Columbus, OH: Merrill.
53. World Health Organization (2004). World report on road traffic injury prevention. Retrieved from http://apps.who.int/iris/bitstream/10665/42871/1/9241562609.pdf
54. Wickens, Christopher D., Hollands, Justin G., Banbury, Simon, and Parasuraman, Raja (2015). Engineering psychology & human performance. Psychology Press (Chapter 11).