個人化路徑導引資訊 : 動態路徑選擇行為模式之應用

淡江大學機構典藏 > 商管學院 > 運輸管理學系暨研究所 > 學位論文 > Item 987654321/33791

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题名:	個人化路徑導引資訊 : 動態路徑選擇行為模式之應用
其它题名:	A study of personalized in-vehicle route guidance : application of dynamic route switch model
作者:	蘇秋如;Su, Chiu-ju
贡献者:	淡江大學運輸管理學系碩士班董啟崇;Tong, Chee-chung
关键词:	逐點動態路徑選擇行為模式;個人化資訊;控制實驗法;車內導引資訊;Personalized In-Vehicle Route Choice Guidance;Dynamic Route Switch Model;Indifference Band;Laboratory Simulation
日期:	2006
上传时间:	2010-01-11 04:33:00 (UTC+8)
摘要:	本研究認為導引資訊系統所提供之路網和導引訊息，駕駛者並非完全遵循其資訊，此外從相關文獻回顧可知相同資訊對旅運者影響不同以及不同旅運者對於資訊需求亦不同，因此提供交通導引資訊，除了基本即時道路狀況外，必須將駕駛者個體路徑選擇行為的差異性及個人特性納入導引資訊提供方式之背景因素考量，因此本研究應用動態路徑選擇行為模式所預測之轉換行為，其目的在於採用個人化路徑導引資訊方式進行實驗，透過對實驗之反應資料蒐集進行分析與模式參數校估等方法，進一步探討其個人化資訊對於動態路徑選擇行為之影響與個人化資訊之適用性。本研究欲達成目的之工作項目歸納如下：（1）設計結構化問卷，獲得駕駛者社經特性、路徑特性、使用資訊行為等基本資料，並利用車內導引模擬器畫面圖示單一決策點上個人化資訊導引方式，使受測者可以透過靜態方式初步瞭解其導引方式與決策過程，並請受測者勾選本身所設定速配度之門檻值（2）以動態模擬實驗方式，藉由一般導引方式與個人化資訊導引方式，觀測每個受測者在行車導引資訊下之路徑選擇行為差異（3）經由實驗所取得決策資料，進行決策點與模式分析。本研究內容主要可分為控制實驗和動態選擇行為模式校估與分析，其中控制實驗過程分為兩部分，第一部分目的為利用問卷蒐集基本特性資料與靜態情境模擬反應，並使受測者充分了解其代表意涵以減少第二部分之動態實驗誤差；第二部份分為兩階段動態模擬實驗，第一階段主要目的為觀察與蒐集駕駛者逐點動態行為紀錄並校估參數，第二階段利用其模式結果進行計算機率，以兩種個人化資訊導引方式進行實驗和蒐集決策資料。第三部分目的為分析其決策點遵循率變化和模式差異。最後，不論從決策點或模式分析其結果均為個人化資訊導引對駕駛者路徑決策變換行為會產生影響，且會使建議路徑之遵循率變高，即表示提供符合駕駛者本身行為之路徑導引資訊方式，會使駕駛者在路徑行進中對資訊之遵循率提高，也代表此個人化資訊方式之適用性高。 The node-to-node dynamic route choice behavior is of the most interest to study the individual driver’s route choices under the influence of the route guidance information where individual driver makes consecutive route switch decisions along with the traveling route. This particular issue has been successfully modeled with various forms and extensions under the notion of the “Indifference Bands” applied with Probit model specifications by Tong and his students at Tamkang University in recent years. The probability of “switching” or “route choice” at each decision node along the route can therefore be estimated under these model specifications. A concept of fitness of personalized in-vehicle route guidance can be derived from previously stated dynamic route switch model where the goodness-of-fit of the recommended route can be treated as the probability of compliance at each decision node along the trip. In this thesis, a two-stage comprehensive controlled experiment has been conducted where selected subjects will be examined in two comparative laboratory simulation scenarios and the results of compliance behavior will be investigated. The first scenario is to provide and update the driver the best (shortest) possible route at each decision node along entire route. From this stage, the node-to-node switching behavior model of each driver can be calibrated with the notion of the indifference band, and the compliance outcomes will be recorded. In the second stage, each individual experiment subject will be supplied with either the usual routing strategy or with personalized information defined by this study as best-fitted behavior routing guidance. The so-called best-fitted behavior routing advises comes from comparing the probability level of accepting the new route against a threshold set by each individual. Finally compliance record will be compared between these two contrasted scenarios to investigate the effect of different routing strategies. The results have demonstrated statistically significant improvement of compliance rate over conventional routing strategy for two variations of best-fitted advises provided respectively.
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