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Household use of autonomous vehicles with ride sourcing

机译:家庭使用自动车辆乘坐采购

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The prospect of autonomous vehicles (AVs) offers the possibility that a household could reduce household owned vehicles to a single vehicle. At the same time, with AVs, a Shared Autonomous Vehicle (SAV) system will rise as a primary mode of serving travel demands. This study aims to model households? activity/travel decisions using both household owned AVs as well as readily available SAVs to perform daily activities. We formulate the Household Activity Pattern Problem with Autonomous Vehicles and Ride Sourcing (HAPPAV-RS), as a mixed integer linear program. The model generates an optimal activity/travel patterns for household members under spatial and temporal constraints. The model can capture driverless operations such as AV pick-up and dropoff, parking availability, empty trips and ridesharing among household members, as well as the use of SAVs with the request waiting time. A decomposition method is used to solve the NP-hard problem HAPPAV-RS. scenarios on using AVs and SAVs with different travel mode availability, AV/SAV cost and SAV waiting time are designed to enable sensitivity analysis. Various travel metrics such as activity pattern feasibility, household?s total travel disutility, travel mode VMT and AV-SAV trip coverage are reported.
机译:自治车辆(AVS)的前景提供了家庭可以将家庭拥有车辆减少到单一车辆的可能性。与此同时,通过AVS,共享自主车辆(SAV)系统将作为服务旅行需求的主要模式上升。这项研究旨在模拟家庭?使用家庭拥有的AVS以及随时可获得的活动/旅行决策以进行日常活动。我们用自动车辆制定家庭活动模式问题并乘坐源(Happav-Rs),作为混合整数线性程序。该模型在空间和时间限制下为家庭成员提供最佳活动/旅行模式。该模型可以捕获无驱动的操作,如AV接送和下降,家庭成员之间的停车可用性,空的旅行和骑士,以及使用SED与请求等待时间。分解方法用于解决NP-Coll问题Happav-Rs。使用具有不同旅行模式可用性的AVS和SEVS的场景,AV / SAV成本和SAV等待时间旨在实现灵敏度分析。报告了各种旅行指标,如活动模式可行性,家庭的总旅行宿舍,旅行模式VMT和AV-SAV跳闸覆盖率。

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