T-PickSeer:出租车上客点选择行为的可视化分析

IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Shuxian Gu, Yemo Dai, Zezheng Feng, Yong Wang, Haipeng Zeng
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引用次数: 0

摘要

摘要出租车司机经常需要花费大量时间在街道上寻找乘客,这导致了高空置率和资源浪费。出租车空车巡游仍然是出租车公司非常担心的问题。分析出租车司机的上客点选择行为可以有效解决这一问题,为出租车管理和调度提供建议。许多研究都致力于分析和推荐上客点的热点区域,从而方便司机上客。然而,上客点的选择非常复杂,受到多种因素的影响,如便利性和交通管理。由于出行需求不断变化且缺乏可解释性,大多数现有方法在实际应用中无法取得令人满意的结果。在本文中,我们介绍了一种可视化分析系统 T-PickSeer,供出租车公司分析人员更好地探索和理解乘客的上车点选择行为。我们探索了大量的出租车 GPS 数据,并采用了一种从概览到细节的方法来有效分析乘客的上车点选择。我们的系统提供了协调视图,可比较不同地区的不同规律和特征。此外,我们的系统还能帮助识别潜在的上客点,并检查每个上客点的性能。基于真实世界数据集和专家访谈的三个案例研究证明了我们系统的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

T-PickSeer: visual analysis of taxi pick-up point selection behavior

T-PickSeer: visual analysis of taxi pick-up point selection behavior

Abstract

Taxi drivers often take much time to navigate the streets to look for passengers, which leads to high vacancy rates and wasted resources. Empty taxi cruising remains a big concern for taxi companies. Analyzing the pick-up point selection behavior can solve this problem effectively, providing suggestions for taxi management and dispatch. Many studies have been devoted to analyzing and recommending hotspot regions of pick-up points, which can make it easier for drivers to pick-up passengers. However, the selection of pick-up points is complex and affected by multiple factors, such as convenience and traffic management. Most existing approaches cannot produce satisfactory results in real-world applications because of the changing travel demands and the lack of interpretability. In this paper, we introduce a visual analytics system, T-PickSeer, for taxi company analysts to better explore and understand the pick-up point selection behavior of passengers. We explore massive taxi GPS data and employ an overview-to-detail approach to enable effective analysis of pick-up point selection. Our system provides coordinated views to compare different regularities and characteristics in different regions. Also, our system assists in identifying potential pick-up points and checking the performance of each pick-up point. Three case studies based on a real-world dataset and interviews with experts have demonstrated the effectiveness of our system.

Graphic abstract

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来源期刊
Journal of Visualization
Journal of Visualization COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY
CiteScore
3.40
自引率
5.90%
发文量
79
审稿时长
>12 weeks
期刊介绍: Visualization is an interdisciplinary imaging science devoted to making the invisible visible through the techniques of experimental visualization and computer-aided visualization. The scope of the Journal is to provide a place to exchange information on the latest visualization technology and its application by the presentation of latest papers of both researchers and technicians.
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