[论文解读] Dynamic Interaction between Shared Autonomous Vehicles and Public Transit: A Competitive Perspective.

Baichuan Mo, Zhejing Cao+3 more|arXiv (Cornell University)|Jan 9, 2020

Transportation and Mobility Innovations参考文献 28被引用 6

一句话总结

本文通過基於代理的模擬與啟發式動態供應更新算法（HDSUA），在利潤導向的設定下，研究了共享自動駕駛車輛（AV）與公共交通（PT）之間的競爭動態。研究結果顯示，AV與PT運營商透過在高峰時段調整供應，可提升利潤，減少出行時間但增加成本；然而，由於時間節省，綜合出行成本仍下降，且在政策干預下可實現雙贏結果。

ABSTRACT

The emergence of autonomous vehicles (AVs) is anticipated to influence the public transportation (PT) system. Many possible relationships between AV and PT are proposed depending on the policy and institution, where competition and cooperation are two main categories. This paper focuses on the former in a hypothetical scenario-if both AV and PT operators were only profit-oriented. We aim to quantitatively evaluate the system performance (e.g. level of service, operators' financial viability, transport efficiency) when AV and PT are profit-oriented competitors with dynamic adjustable supply strategies under certain policy constraints. We assume AV can adjust the fleetsize and PT can adjust the headway. Service fare and bus routes are fixed. The competition process is analyzed through an agent-based simulation platform, which incorporates a proposed heuristic dynamic supply updating algorithm (HDSUA). The first-mile scenario in Singapore Tampines area is selected as the case study, where only bus is considered for PT system. We found that when AV and bus operators are given the flexibility to adjust supply, both of them will re-distribute their supply spatially and temporally, leading to higher profits. In temporal dimension, both AV and bus will concentrate their supplies in morning and evening peak hours, and reduce the supplies in off-peak hours. The competition between AV and PT decreases passengers' travel time but increase their travel cost. The generalized travel cost is still reduced when counting the value of time. The bus supply adjustment can increase the bus average load and reduce total passenger car equivalent (PCE), which is good for transport efficiency and sustainability. But the AV supply adjustment shows the opposite effect. Overall, the competition does not necessarily bring out loss-gain results. A win-win outcome is also possible under certain policy interventions.

研究动机与目标

• 分析利潤導向的共享自動駕駛車輛（AV）與公共交通（PT）在動態供應調整下的競爭互動。
• 從服務品質、財務可行性與運輸效率等角度評估系統表現。
• 探討政策限制如何影響真實都市環境中AV-PT競爭的結果。
• 評估在不同供應調整策略下，競爭是否導致雙贏或零和結果。

提出的方法

• 建立基於代理的模擬平台，將AV與PT運營商視為具利潤最大化目標的獨立代理。
• 採用啟發式動態供應更新算法（HDSUA），使AV與巴士能根據需求與競爭狀況動態調整車隊規模與班距。
• 案例研究聚焦於新加坡榜額地區的首程出行場景，PT採用固定票價與路線。
• 供應調整基於即時需求模式，AV與巴士均以高峰時段集中供應為優化目標。
• 模擬評估包括出行時間、成本、載客率與總乘客當量（PCE）在內的績效指標。
• 嵌入政策限制，以反映現實中的制度與法規條件。

实验结果

研究问题

• RQ1 在共享出行環境中，AV與PT運營商如何動態調整供應以追求利潤？
• RQ2 動態供應調整對出行時間、成本與綜合出行成本的影響為何？
• RQ3 供應調整如何影響運輸效率（以平均載客率與PCE衡量）？
• RQ4 在何種條件下，競爭可導致雙贏結果而非損益相抵？
• RQ5 政策干預在促成AV與PT運營商互利結果中扮演何種角色？

主要发现

• AV與PT運營商均透過在早晨與傍晚高峰時段集中供應、非高峰時段減少供應，提升利潤。
• 競爭雖減少平均出行時間，但增加貨幣成本，然而綜合成本（含時間價值）整體仍下降。
• 巴士供應調整提升平均載客率，減少總乘客當量（PCE），進而提升運輸效率與永續性。
• AV供應調整產生相反效果，降低載客率並增加PCE，不利於效率提升。
• 競爭並非簡單的損益相抵動態；在適當政策干預下，雙贏結果仍可實現。
• 啟發式動態供應更新算法（HDSUA）有效支援適應性供應策略，在競爭環境下提升系統表現。