article

Prediction of urban human mobility using large-scale taxi traces and its applications

Authors:

Wangsheng Zhang,

Zonghui WangAuthors Info & Claims

Frontiers of Computer Science in China, Volume 6, Issue 1

Pages 111 - 121

Published: 01 February 2012 Publication History

Abstract

This paper investigates human mobility patterns in an urban taxi transportation system. This work focuses on predicting humanmobility fromdiscovering patterns of in the number of passenger pick-ups quantity (PUQ) from urban hotspots. This paper proposes an improved ARIMA based prediction method to forecast the spatial-temporal variation of passengers in a hotspot. Evaluation with a large-scale realworld data set of 4 000 taxis' GPS traces over one year shows a prediction error of only 5.8%. We also explore the application of the prediction approach to help drivers find their next passengers. The simulation results using historical real-world data demonstrate that, with our guidance, drivers can reduce the time taken and distance travelled, to find their next passenger, by 37.1% and 6.4%, respectively.

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Cited By

Mo ZXiang HDi X(2024)Cross- and Context-Aware Attention Based Spatial-Temporal Graph Convolutional Networks for Human Mobility PredictionACM Transactions on Spatial Algorithms and Systems10.1145/367322710:4(1-25)Online publication date: 9-Jul-2024
https://dl.acm.org/doi/10.1145/3673227
Zhang YYu ZDang MXu EGuo BLiang YYin YZimmermann R(2024)Predictability in Human Mobility: From Individual to Collective (Vision Paper)ACM Transactions on Spatial Algorithms and Systems10.1145/365664010:2(1-17)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3656640
Zhang CCai LChen MLi XCong G(2024)DeepMeshCity: A Deep Learning Model for Urban Grid PredictionACM Transactions on Knowledge Discovery from Data10.1145/365285918:6(1-26)Online publication date: 29-Apr-2024
https://dl.acm.org/doi/10.1145/3652859
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Prediction of urban human mobility using large-scale taxi traces and its applications
1. Information systems
  1. Information systems applications

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Published In

cover image Frontiers of Computer Science in China

Frontiers of Computer Science in China Volume 6, Issue 1

February 2012

130 pages

ISSN:1673-7350

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Copyright © Copyright © 2012 Higher Education Press and Springer-Verlag Berlin Heidelberg.

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 February 2012

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Cited By

Mo ZXiang HDi X(2024)Cross- and Context-Aware Attention Based Spatial-Temporal Graph Convolutional Networks for Human Mobility PredictionACM Transactions on Spatial Algorithms and Systems10.1145/367322710:4(1-25)Online publication date: 9-Jul-2024
https://dl.acm.org/doi/10.1145/3673227
Zhang YYu ZDang MXu EGuo BLiang YYin YZimmermann R(2024)Predictability in Human Mobility: From Individual to Collective (Vision Paper)ACM Transactions on Spatial Algorithms and Systems10.1145/365664010:2(1-17)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3656640
Zhang CCai LChen MLi XCong G(2024)DeepMeshCity: A Deep Learning Model for Urban Grid PredictionACM Transactions on Knowledge Discovery from Data10.1145/365285918:6(1-26)Online publication date: 29-Apr-2024
https://dl.acm.org/doi/10.1145/3652859
Jiang ZHuang ALuo QGuan W(2024)Local-Perception-Enhanced Spatial–Temporal Evolving Graph Transformer Network: Citywide Demand Prediction of Taxi and Ride-HailingIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2024.345084625:11(17105-17121)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TITS.2024.3450846
Yang HYan CChen ZWang P(2024)A K-Shape Clustering Based Transformer-Decoder Model for Predicting Multi-Step Potentials of Urban Mobility FieldIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2024.335521125:8(10298-10312)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1109/TITS.2024.3355211
Liu JTeng MChen WXiong H(2023)A Cost-Effective Sequential Route Recommender System for Taxi DriversINFORMS Journal on Computing10.1287/ijoc.2021.011235:5(1098-1119)Online publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1287/ijoc.2021.0112
Wang QGuo BCheng LYu Z(2023)sUrbanProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36108777:3(1-20)Online publication date: 27-Sep-2023
https://dl.acm.org/doi/10.1145/3610877
Shou TYe ZHong YWang ZZhu HJiang ZYang DZhou BWang CChen L(2023)CrowdQProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36108757:3(1-28)Online publication date: 27-Sep-2023
https://dl.acm.org/doi/10.1145/3610875
Yu ZDang MWu QChen LXie YWang YGuo B(2023)An Information Theory Based Method for Quantifying the Predictability of Human MobilityACM Transactions on Knowledge Discovery from Data10.1145/359750017:9(1-19)Online publication date: 18-Jul-2023
https://dl.acm.org/doi/10.1145/3597500
Wu YZhang XWang YFrommholz IHopfgartner FLee MOakes MLalmas MZhang MSantos R(2023)Adaptive Graph Neural Diffusion for Traffic Demand ForecastingProceedings of the 32nd ACM International Conference on Information and Knowledge Management10.1145/3583780.3615153(4350-4354)Online publication date: 21-Oct-2023
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