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Award, U.V. Helava, ISPRS.
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0912
Ad hoc shared ride systems.
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1003
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Greenhouse Gas Emission Impacts of Carsharing in North America,
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1112
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1206
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1309
Autoregressive integrated moving average (ARIMA)
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A Car Pooling Model and Solution Method With Stochastic Vehicle
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1403
automobiles
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Dynamic Vehicle Redistribution and Online Price Incentives in Shared
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bicycles
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A Genetic-Algorithm-Based Approach to Solve Carpool Service Problems
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1502
Biological cells
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1511
genetic algorithms
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electric vehicles
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Comparing Optimal Relocation Operations With Simulated Relocation
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1410
mathematical programming
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Intelligent Carpool Routing for Urban Ridesharing by Mining GPS
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1410
Global Positioning System
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A Partition-Based Match Making Algorithm for Dynamic Ridesharing,
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1511
intelligent transportation systems
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A Discounted Trade Reduction Mechanism for Dynamic Ridesharing
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1606
Companies
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Analysis of Taxi Drivers' Behaviors Within a Battle Between Two Taxi
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1601
Cities and towns
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Big data
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1606
Global Positioning System
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Trace Data,
IJGI(6), No. 5, 2017, pp. xx-yy.
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Pan, G.,
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Wu, Z.,
Understanding Taxi Service Strategies From Taxi GPS Traces,
ITS(16), No. 1, February 2015, pp. 123-135.
IEEE DOI
1502
Cities and towns
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Chen, C.[Chao],
Li, S.J.[Shi-Jian],
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Vehicles equipped with GPS localizers are an important sensory device
for examining people's movements and activities. Taxis equipped with
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Wu, H.B.[Hang-Bin],
Fan, H.C.[Hong-Chao],
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Exploring Spatiotemporal Patterns of Long-Distance Taxi Rides in
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IJGI(6), No. 11, 2017, pp. xx-yy.
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1712
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Wang, J.[Jian],
Revealing Recurrent Urban Congestion Evolution Patterns with Taxi
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IJGI(7), No. 4, 2018, pp. xx-yy.
DOI Link
1805
BibRef
Wang, Y.D.[Yan-Dong],
Gu, Y.[Yanyan],
Dou, M.X.[Ming-Xuan],
Qiao, M.[Mengling],
Using Spatial Semantics and Interactions to Identify Urban Functional
Regions,
IJGI(7), No. 4, 2018, pp. xx-yy.
DOI Link
1805
Using taxi origin/destination (O/D) flows.
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Su, R.X.[Rong-Xiang],
Fang, Z.X.[Zhi-Xiang],
Xu, H.[Hong],
Huang, L.[Lian],
Uncovering Spatial Inequality in Taxi Services in the Context of a
Subsidy War among E-Hailing Apps,
IJGI(7), No. 6, 2018, pp. xx-yy.
DOI Link
1806
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Alfeo, A.L.,
Cimino, M.G.C.A.[M. G. C. A.],
Egidi, S.,
Lepri, B.,
Vaglini, G.,
A Stigmergy-Based Analysis of City Hotspots to Discover Trends and
Anomalies in Urban Transportation Usage,
ITS(19), No. 7, July 2018, pp. 2258-2267.
IEEE DOI
1807
Computational modeling, Global Positioning System, Pollution,
Pollution measurement, Public transportation, Urban areas,
taxi-GPS traces
BibRef
Xu, J.,
Rahmatizadeh, R.,
Bölöni, L.,
Turgut, D.,
Real-Time Prediction of Taxi Demand Using Recurrent Neural Networks,
ITS(19), No. 8, August 2018, pp. 2572-2581.
IEEE DOI
1808
Public transportation, Urban areas, Recurrent neural networks,
Predictive models, Global Positioning System,
mixture density networks
BibRef
He, Z.,
Chen, K.,
Chen, X.,
A Collaborative Method for Route Discovery Using Taxi Drivers'
Experience and Preferences,
ITS(19), No. 8, August 2018, pp. 2505-2514.
IEEE DOI
1808
Public transportation, Roads, Vehicles, Collaboration, Trajectory,
Routing, Intelligent transportation systems,
knowledge acquisition
BibRef
Chen, C.,
Jiao, S.,
Zhang, S.,
Liu, W.,
Feng, L.,
Wang, Y.,
TripImputor: Real-Time Imputing Taxi Trip Purpose Leveraging
Multi-Sourced Urban Data,
ITS(19), No. 10, October 2018, pp. 3292-3304.
IEEE DOI
1810
Public transportation, Real-time systems, Trajectory,
Global Positioning System, Semantics, Data mining, Urban areas,
trajectory data mining
BibRef
Amar, H.M.,
Basir, O.A.,
A Game Theoretic Solution for the Territory Sharing Problem in Social
Taxi Networks,
ITS(19), No. 7, July 2018, pp. 2114-2124.
IEEE DOI
1807
Automobiles, Game theory, Games, Public transportation,
Resource management, Cooperative trip planning,
social taxi networks
BibRef
He, B.[Biao],
Zhang, Y.[Yan],
Chen, Y.[Yu],
Gu, Z.H.[Zhi-Hui],
A Simple Line Clustering Method for Spatial Analysis with
Origin-Destination Data and Its Application to Bike-Sharing Movement
Data,
IJGI(7), No. 6, 2018, pp. xx-yy.
DOI Link
1806
BibRef
Jing, W.P.[Wei-Peng],
Kang, J.[Jian],
Liu, M.[Meiling],
Mining taxi trajectories for most suitable stations of sharing bikes to
ease traffic congestion,
IET-ITS(12), No. 7, September 2018, pp. 586-593.
DOI Link
1808
BibRef
Clemente, M.,
Fanti, M.P.,
Iacobellis, G.,
Nolich, M.,
Ukovich, W.,
A Decision Support System for User-Based Vehicle Relocation in Car
Sharing Systems,
SMCS(48), No. 8, August 2018, pp. 1283-1296.
IEEE DOI
1808
automobiles, closed loop systems, decision support systems,
discrete event simulation, particle swarm optimisation,
optimization
BibRef
Tang, G.,
Keshav, S.,
Golab, L.,
Wu, K.,
Bikeshare Pool Sizing for Bike-and-Ride Multimodal Transit,
ITS(19), No. 7, July 2018, pp. 2279-2289.
IEEE DOI
1807
Bicycles, Employment, Public transportation, Rail transportation,
Schedules, Sociology, Statistics, Bikeshare pool sizing, multimodal transit
BibRef
Genikomsakis, K.N.,
Gutierrez, I.A.[I. Angulo],
Thomas, D.,
Ioakimidis, C.S.,
Simulation and Design of Fast Charging Infrastructure for a
University-Based e-Carsharing System,
ITS(19), No. 9, September 2018, pp. 2923-2932.
IEEE DOI
1809
Batteries, Charging stations, Automobiles, State of charge,
Urban areas, MATLAB, Electric vehicles, battery chargers,
transportation
BibRef
Rigas, E.S.[Emmanouil S.],
Ramchurn, S.D.[Sarvapali D.],
Bassiliades, N.[Nick],
Algorithms for electric vehicle scheduling in large-scale
mobility-on-demand schemes,
AI(262), 2018, pp. 248-278.
Elsevier DOI
1809
Mixed integer programming, Heuristic search, Local search,
Max-flow, Electric vehicles, Shared vehicles, Mobility on demand
BibRef
Zhang, X.X.[Xin-Xin],
Huang, B.[Bo],
Zhu, S.Z.[Shun-Zhi],
Spatiotemporal Influence of Urban Environment on Taxi Ridership Using
Geographically and Temporally Weighted Regression,
IJGI(8), No. 1, 2019, pp. xx-yy.
DOI Link
1901
BibRef
Zong, F.,
Wu, T.,
Jia, H.,
Taxi Drivers' Cruising Patterns: Insights from Taxi GPS Traces,
ITS(20), No. 2, February 2019, pp. 571-582.
IEEE DOI
1902
Public transportation, Vehicles, Global Positioning System,
Urban areas, Roads, Taxi, GPS, cruising pattern, land use, pick-up points
BibRef
Yu, W.,
Discovering Frequent Movement Paths From Taxi Trajectory Data Using
Spatially Embedded Networks and Association Rules,
ITS(20), No. 3, March 2019, pp. 855-866.
IEEE DOI
1903
Trajectory, Public transportation, Data mining, Urban areas,
Space exploration, Clustering algorithms, Taxi trajectory,
spatial association rule
BibRef
Kuang, L.[Li],
Yan, X.J.[Xue-Jin],
Tan, X.H.[Xian-Han],
Li, S.[Shuqi],
Yang, X.X.[Xiao-Xian],
Predicting Taxi Demand Based on 3D Convolutional Neural Network and
Multi-task Learning,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link
1906
BibRef
Wang, H.[Huihui],
Huang, H.[Hong],
Ni, X.Y.[Xiao-Yong],
Zeng, W.H.[Wei-Hua],
Revealing Spatial-Temporal Characteristics and Patterns of Urban
Travel: A Large-Scale Analysis and Visualization Study with Taxi GPS
Data,
IJGI(8), No. 6, 2019, pp. xx-yy.
DOI Link
1908
BibRef
Hu, C.C.[Chun-Chun],
Thill, J.C.[Jean-Claude],
Predicting the Upcoming Services of Vacant Taxis near Fixed Locations
Using Taxi Trajectories,
IJGI(8), No. 7, 2019, pp. xx-yy.
DOI Link
1908
BibRef
Xu, Y.[Ying],
Li, D.S.[Dong-Sheng],
Incorporating Graph Attention and Recurrent Architectures for
City-Wide Taxi Demand Prediction,
IJGI(8), No. 9, 2019, pp. xx-yy.
DOI Link
1909
BibRef
Liu, L.,
Qiu, Z.,
Li, G.,
Wang, Q.,
Ouyang, W.,
Lin, L.,
Contextualized Spatial-Temporal Network for Taxi Origin-Destination
Demand Prediction,
ITS(20), No. 10, October 2019, pp. 3875-3887.
IEEE DOI
1910
Public transportation, Task analysis, Correlation, Neural networks,
Urban areas, Context modeling, Predictive models,
spatial-temporal modeling
BibRef
Yu, H.,
Chen, X.,
Li, Z.,
Zhang, G.,
Liu, P.,
Yang, J.,
Yang, Y.,
Taxi-Based Mobility Demand Formulation and Prediction Using
Conditional Generative Adversarial Network-Driven Learning Approaches,
ITS(20), No. 10, October 2019, pp. 3888-3899.
IEEE DOI
1910
Public transportation, Predictive models, Generators, Training,
Roads, Numerical models, Data models, Taxi system, machine learning,
big transportation data
BibRef
Kondor, D.,
Zhang, H.,
Tachet, R.,
Santi, P.,
Ratti, C.,
Estimating Savings in Parking Demand Using Shared Vehicles for
Home-Work Commuting,
ITS(20), No. 8, August 2019, pp. 2903-2912.
IEEE DOI
1908
Automobiles, Urban areas, Autonomous vehicles, Roads,
Public transportation, Sociology, Statistics, Shared vehicles,
agent-based model
BibRef
Cao, M.[Min],
Ma, S.[Shangjing],
Huang, M.[Mengxue],
Lü, G.[Guonian],
Chen, M.[Min],
Effects of Free-Floating Shared Bicycles on Urban Public
Transportation,
IJGI(8), No. 8, 2019, pp. xx-yy.
DOI Link
1909
BibRef
Zhao, X.F.[Xiao-Fei],
Hu, C.[Caiyi],
Liu, Z.[Zhao],
Meng, Y.Y.[Yang-Yang],
Weighted Dynamic Time Warping for Grid-Based Travel-Demand-Pattern
Clustering: Case Study of Beijing Bicycle-Sharing System,
IJGI(8), No. 6, 2019, pp. xx-yy.
DOI Link
1908
BibRef
Zhu, M.,
Liu, X.,
Wang, X.,
An Online Ride-Sharing Path-Planning Strategy for Public Vehicle
Systems,
ITS(20), No. 2, February 2019, pp. 616-627.
IEEE DOI
1902
Quality of service, Public transportation, Path planning,
Schedules, Pollution, Peer-to-peer computing,
online/dynamic peer-to-peer ride-sharing
BibRef
Zhai, Y.[Yong],
Liu, J.[Jin],
Du, J.[Juan],
Wu, H.[Hao],
Fleet Size and Rebalancing Analysis of Dockless Bike-Sharing Stations
Based on Markov Chain,
IJGI(8), No. 8, 2019, pp. xx-yy.
DOI Link
1909
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Dong, J.[Jian],
Chen, B.[Bin],
He, L.[Lingnan],
Ai, C.[Chuan],
Zhang, F.[Fang],
Guo, D.[Danhuai],
Qiu, X.G.[Xiao-Gang],
A Spatio-Temporal Flow Model of Urban Dockless Shared Bikes Based on
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IJGI(8), No. 8, 2019, pp. xx-yy.
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1909
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Fu, X.Y.[Xiao-Yi],
Zhang, C.[Ce],
Lu, H.[Hua],
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Efficient matching of offers and requests in social-aware ridesharing,
GeoInfo(23), No. 4, October 2019, pp. 559-589.
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1911
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Christian, K.[Kapuku],
Cho, S.H.[Shin-Hyung],
Kho, S.Y.[Seung-Young],
Kim, D.K.[Dong-Kyu],
Bayesian models with spatial autocorrelation for bike sharing ridership
variability based on revealed preference GPS trajectory data,
IET-ITS(13), No. 11, November 2019, pp. 1658-1667.
DOI Link
1911
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Panagiotopoulos, I.[Ilias],
Dimitrakopoulos, G.[George],
Cognitive intelligence of highly automated vehicles in a car-sharing
context,
IET-ITS(13), No. 11, November 2019, pp. 1604-1612.
DOI Link
1911
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Ke, J.,
Yang, H.,
Zheng, H.,
Chen, X.,
Jia, Y.,
Gong, P.,
Ye, J.,
Hexagon-Based Convolutional Neural Network for Supply-Demand
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ITS(20), No. 11, November 2019, pp. 4160-4173.
IEEE DOI
1911
Forecasting, Urban areas, Automobiles,
Convolutional neural networks, Pricing,
ride-sourcing service
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Chen, C.C.[Chian-Ching],
Tsang, S.S.[Seng-Su],
Predicting adoption of mobile payments from the perspective of taxi
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IET-ITS(13), No. 7, July 2019, pp. 1116-1124.
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1906
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Cao, M.[Min],
Cai, B.[Boqin],
Ma, S.J.[Shang-Jing],
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Analysis of the Cycling Flow Between Origin and Destination for
Dockless Shared Bicycles Based on Singular Value Decomposition,
IJGI(8), No. 12, 2019, pp. xx-yy.
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1912
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Mojtabaee, P.,
Molavi, M.,
Taleai, M.,
Exploring Driving Factors of Higher Paid Taxi Trips Using
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1912
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Coskun, I.B.,
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Anbaroglu, B.,
K-nearest Neighbour Query Performance Analyses On a Large Scale Taxi
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1912
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Wang, H.,
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Wang, Y.,
Shan, J.,
Local Maximum Density Approach for Small-scale Clustering of Urban Taxi
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1912
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Rangriz, S.,
Davoodi, M.,
Saberian, J.,
A Novel Approach to Optimize The Ridesharing Problem Using Genetic
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SMPR19(875-878).
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1912
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Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Transit Traffic Analysis, Public Transit, Bus .