群體用路人路徑選擇決策之研究

Abstract

隨著智慧型運輸系統(Intelligent Transportation Systems, ITS)的發展，先進旅行者資訊系統(Advanced Traveler Information Systems, ATIS)與可變資訊標誌(VMS)可提供即時路況資訊供用路人進行相關旅運決策之參考，以減少用路人對於旅行時間的不確定性、以紓緩交通壅賽的情形。 傳統路徑選擇相關研究多探討路網特性與用路人行為特性對路徑選擇決策的影響，少有探討同車旅客對駕駛者路徑選擇決策的影響。本研究針對群體用路人透過ATIS獲得交通資訊之下，各個個體根據本身風險傾向，透過學習及相關經驗的累積進行群體決策時，旅行成本對於中長程旅次群體用路人路徑選擇的影響。 研究中利用情境分析模擬多種用路人路徑選擇情形，以多元羅吉特計算用路人選擇各路徑的比例。根據Cheu et al. (2008)所發展的Simpler Equivalent Link Disutility (Simpler ELD)計算時間成本，並以Aribarg (2010)與Harsanyi (1975)所提出的模式為群體效用函數，以”用路人認知負效用最小化”為決策準則，以反應同車旅客對群體用路人中長程旅次路徑選擇的影響。

With the development of the Intelligent Transportation Systems, Advanced Traveler Information Systems and Variable-Message Sign can provide instant traffic information as references of route choices for travelers in order to decrease the travel-time uncertainty and to reduce the amount of traffic. Most of the traditional route choice researches are focused on the effect of route choice decision that based on road characteristics and traveler behavior characteristics, but only a few studies have evaluated the influence of passengers in the same car on the driver’s route choice decision. This dissertation is focused on the effect of travel cost on group’s route choice decision-making for long travel with the condition that user group obtain traffic information from ATIS and make group decision through individuals’ risk-taking and momentary recollection of past experience.