自動駕駛巴士運行路線之研究-以台北市爲例

Operation Routes of Autonomous Buses- A Case Study of Taipei City

徐浩荃(Hao-Quan Xu)

指導教授 ： 張學孔

國立臺灣大學/工學院/土木工程學研究所/碩士(2021年)

https://doi.org/10.6342/NTU202103940

摘要

傳統的公車運營存在尖峰時段車厢擁擠、離峰時段出行等待時間長、而偏遠地區數量少致使乘客出行不方便等諸多問題。「自駕定制公車」（Autonomous Customized Bus）則是借助自動駕駛技術開展定制公車服務的一種新的運營模式。爲了緩解傳統公車存在的不足，本研究提出以自駕公車提供定制服務的模式，並以台北市公車系統為例針對自駕定制公車的路線選擇之規劃層次以及運行管理優化等兩個面向進行研究。
首先，本研究構建自駕定制公車路線選擇評價指標體系和評價模型。所建立的評價指標體系包括客流適宜性和路線適宜性兩個維度指標，涉及客流結構、客流規模、出行時段、站點數量、路線位置以及路權情况等六個子維度指標。根據評價指標體系，本文進一步提出基於熵權法的灰色關聯度分析模型用於自駕定制公車方案的評選。該模型基於案例數據和熵權法計算各個子維度指標，進而使用灰色關聯度分析法獲取各個方案與理想方案之間的接近程度。
此外，建立了基於乘客感知成本最小化目標的自駕定制公車運行管理優化模型。設計了非綫性整數規劃的動態規劃模型，幷採用Python對模型進行求解。研究成果可以最大程度降低乘客出行過程中的感知成本，增加乘客出行過程中對於服務的信賴。研究模型應用在台北市的應用分析顯示，研究成果可以爲公車業者在自駕定制公車運行管理優化方案提供理論依據及技術支撑，並可據以推動自駕定制公車系統的發展。

關鍵字

自駕公車 ； 定制公車 ； 路線選擇 ； 感知成本 ； 優化模型

並列摘要

The traditional bus operation has many problems, which makes it inconvenient for passengers to travel and so on. The autonomous customized bus is an operation mode of customized bus service with the help of automated technologies. In order to alleviate the shortcomings of traditional buses, this paper proposes the operation model of applying autonomous bus to provide customized services. The developed models are applied to Taipei City in two aspects, namely bus route selection in the planning stage and operation optimization in management aspect.
Firstly, the evaluation framework for selection of customized bus route is developed and applied for the candidate routes in Central Taipei. According to the evaluation index system, this paper further proposes a Grey correlation analysis model based on entropy weight method for the evaluation, comparison and selection of autonomous customized buses schemes. The model calculates based on case data and entropy weight method, and then uses Grey correlation analysis method to obtain the proximity between each scheme and the ideal scheme.
In the aspect of operation, an optimization model of autonomous customized bus system is developed based on the objective of minimum passengers perceived cost while the model is solved by algorithm of Python. With the minimized perceived cost, the autonomous customized bus operation would be able to bring confidence to passengers. The results and findings of this study can provide theoretical basis and technical support for development of autonomous customized bus system.

並列關鍵字

Autonomous bus ； Customized bus ； Route selection ； Perceived cost ； Optimization model

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