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研究生: 羊以傑
Yang, Yi-Jie
論文名稱: 結合自動駕駛車與醫院接駁服務的財務可行性評估
Assessing the Financial Feasibility of Integrating Autonomous Vehicle in Hospital Access Service
指導教授: 胡守任
Hu, Shou-Ren
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: 2019
畢業學年度: 107
語文別: 英文
論文頁數: 73
中文關鍵詞: 自動駕駛車代理人模式個人快速運輸系統成本效益分析
外文關鍵詞: Autonomous vehicles, Agent-based model, Personal rapid transit, Cost-benefit analysis
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  • 臺灣已於2018年正式宣告邁入「高齡社會」,許多的問題也隨著人口結構的改變而逐漸成為重要的議題,其中長者運輸是一項非常重要且具挑戰性的議題。針對目前人口老化的問題,政府於2007年及2016年分別頒布長照1.0及2.0的政策,其中包括長者的運輸服務,但相關議題限制重重,無法有效提供有需求的長者有效率且值得信任的運輸服務。關於長者運輸服務的部分,其中有關醫院接駁的部分,尤其重要且迫在眉睫,目前長照計畫針對此部分多是透過與外部基金會合作以復康巴士提供接駁服務,但是使用復康巴士的限制多且有車輛、預算不足等問題。在未來幾年內,隨著長者的比例及數量將持續攀高,長者運輸需求也將隨之提升。伴隨著科技進展,近年來無人自駕車發展快速,且有著無人駕駛的特性,若將目前復康巴士轉而採用無人自駕車來提供服務,可望降低人力相關的成本,如此可以將預算轉至其他需要的部分,使得長者運輸服務更加完善。
    近年來有關無人自駕車的文獻多將其視為傳統私有車的升級版,而這樣的看法無法完全展現無人自駕車的優勢,若將其特性加以應用,可望在運輸領域的應用上,將有更大的突破。本研究主要針對無人自駕車應用於提供個人的醫院接駁服務進行財務可行性的評估,預期透過該系統提供個人快速運輸服務,可以提供可及性更高與效率更好的醫院接駁服務。最後本研究透過財務可行性分析與營運績效的分析,評估以無人自駕車提供醫療接駁服務應用的整體績效及可行性。
    本研究在研究方法的應用上,主要透過基於Agent的模型,進行營運績效的模擬,再將模擬結果作為成本效益分析的輸入,以資料進行後續的財務可行性分析。根據模擬實驗結果顯示,相關結論可總結為以下兩點:1) 以目前自駕車的能源效率表現而言,對於整體成本效益的影響並不明顯;2) 期初投入的資本成本,對於整體財務影響顯著。

    With the increasing attention of population aging, the transportation of the elderly has been one of the concerns in recent years. Taiwan had already become an Aged Society. For this reason, the elderly care policy was proposed which is called Long-term Care 1.0 in 2007 and Long-term Care 2.0 in 2016, including elderly transportation service. A large increasing in the travel of the elderly would result in many current transportation systems facing challenges in providing efficient and reliable services to users, especially hospital access service. Hospital access service providers face a suffering; the demand exceeds the supply. The elderly transportation demanders are expected to raise sharply, hence, thde Long-term Care scheme cannot afford it. In order to increase the service area and sustainability of transportation services from Long-term Care 2.0, replacing rehabilitation buses to autonomous vehicles (AVs) might be an option to reduce the operation cost. With the advent of automation, the use of AVs in public health transportation service may provide a new type of door-to-door service.
    Recent literature on the potential of AVs primarily look on them as an upgraded version to conventional personal vehicles. Therefore, if we merely deploy AVs as an upgraded version of human-driven vehicles, we may underestimate the benefits of the new technology. This study aims at integrating AV in demand responsive transport (DRT) system for hospital access service, which is expected to be an accessible and reliable service because the flexible routing policy. We will access the financial feasibility and operational achievement of the new option of using AVs for the hospital access service problem.
    For the methods used, we simulated a simplified gridded network using agent-based model to evaluate the operational performance and collected the output as inputs in the cost-benefit analysis to evaluate the financial feasibility conditions. The conclusions of the simulation results are summarized as follows: 1) power efficiency of EVs is negligible for an AV transportation system; and 2) the initial cost of this AV transportation system has a great influence on the financial sustainability of an AV-based model for hospital access service.

    TABLE OF CONTENT CHAPTER 1 INTRODUCTION 1 1.1. Background 1 1.2. Motivation 4 1.3. Research Methods 7 1.4. Research Objective 7 1.5. Research Content with Flow Chart 7 CHAPTER 2 LITERATURE REVIEW 9 2.1. Integrating AV in Public Transportation 9 2.2. Public Health 11 2.2.1. Definition of Disability and Long-term Care 2.0 eligibility 12 2.2.2. Mobility of the elderly 13 2.3. DRT 14 2.3.1. Definition of DRT 15 2.3.2. Case study of DRT 16 2.3.3. Studies of DRT 18 2.4. Cost-benefit analysis: Selected infrastructure projects 19 2.5. Summary of the Literature Review 22 CHAPTER 3 RESEARCH METHODS 31 3.1. Problem Statement 31 3.2. Modeling and decision-making issues 32 3.3. Research framework 34 3.4. Cost-benefit analysis 36 3.4.1. Net present value (NPV) 37 3.4.2. Internal rate of return (IRR) 38 3.4.3. Self-liquidation ratio (SLR) 38 3.4.4. Benefit-cost ratio (BCR) 39 3.4.5. Payback period (PBP) 40 3.4.6. Capital cost calculation concept 41 3.4.7. Operating cost calculation concept 41 3.5. Agent-based model 42 3.6. Simulation tool and environment 44 3.6.1. Basic elements 45 3.6.2. Implementation 45 3.7. Summary of research methods 46 CHAPTER 4 NUMERICAL ANALYSIS 47 4.1. Experimental setup 47 4.2. Results of the Tainan rail station network 55 4.2.1. Operating results 55 4.2.2. Financial results 57 4.2.3. Sensitivity analysis 58 4.3. Summary 62 CHAPTER 5 CONCLUSION AND RECOMMEDATION 63 REFERENCES 65 APPENDICES 71 Appendix A - Sensitivity analysis results 71 Appendix B - Sensitivity analysis results (parking space) 73

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