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首页> 外文期刊>Transport policy >Guiding vacant taxi drivers to demand locations by taxi-calling signals: A sequential binary logistic regression modeling approach and policy implications
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Guiding vacant taxi drivers to demand locations by taxi-calling signals: A sequential binary logistic regression modeling approach and policy implications

机译：指导空置出租车司机通过出租车呼叫信号要求位置：顺序二进制物流回归建模方法和政策含义

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摘要

Taxi-calling signals (TCSs) have appeared in many cities to reveal passenger demand at locations away from the roadside to cruising vacant taxis to reduce search times for both vacant taxi drivers and customers. This study aims to find out the factors influencing vacant taxi drivers' customer-search decisions on whether to enter or bypass recommended areas while the drivers are cruising along a road with a series of TCSs. Observational survey data were collected and analyzed to understand the travel behavior of vacant taxi drivers. A sequential binary logistic regression (SBLR) model is first proposed to examine the dynamic decision-making process of vacant taxi drivers. A simulation model and a solution procedure are then developed by adopting the intervening opportunity modeling concept to validate the SBLR model. A sensitivity analysis is consequently conducted to show that the installation of TCSs can effectively increase the number of vacant taxis entering off-road locations for picking up customers. Potential policy implications are discussed.
机译：出租车呼叫信号（TCSS）出现在许多城市中，以揭示远离路边的乘客需求，以减少空置出租车，以减少空置出租车司机和客户的搜索时间。本研究旨在了解影响空置出租车司机的客户搜索决策的因素，而驾驶员沿着带有一系列TCS的道路巡航。收集并分析了观察调查数据，以了解空置出租车司机的旅行行为。首先提出顺序二进制物流回归（SBLR）模型来检查空闲出租车司机的动态决策过程。然后通过采用介入机会建模概念来开发模拟模型和解决方案过程以验证SBLR模型。因此，进行了敏感性分析，表明TCS的安装可以有效地增加进入越野地点的空乘出租车的数量来拾取客户。讨论了潜在的政策影响。

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