16.7.2.5.10 Shared Ride Systems, Car Sharing, Bike Sharing, Taxi, Analysis

Raubal, M.[Martin], Winter, S.[Stephan], Tessmann, S.[Sven], Gaisbauer, C.[Christian],
Time geography for ad-hoc shared-ride trip planning in mobile geosensor networks,
PandRS(58), No. 5-6, July 2004, pp. 289-300.
Elsevier DOI 1202
Award, U.V. Helava, ISPRS. BibRef

Braun, M., Winter, S.,
Ad Hoc Solution of the Multicommodity-Flow-Over-Time Problem,
ITS(10), No. 4, December 2009, pp. 658-667.
IEEE DOI 0912
Ad hoc shared ride systems. BibRef

Seow, K.T., Lee, D.H.,
Performance of Multiagent Taxi Dispatch on Extended-Runtime Taxi Availability: A Simulation Study,
ITS(11), No. 1, March 2010, pp. 231-236.
IEEE DOI 1003
BibRef

Yan, S., Chen, C.Y., Lin, Y.F.,
A Model With a Heuristic Algorithm for Solving the Long-Term Many-to-Many Car Pooling Problem,
ITS(12), No. 4, December 2011, pp. 1362-1373.
IEEE DOI 1112
BibRef

Jia, T.[Tao], Jiang, B.[Bin],
Exploring Human Activity Patterns Using Taxicab Static Points,
IJGI(1), No. 1, June 2012, pp. 89-107;.
DOI Link 1206
BibRef

Dimitrakopoulos, G., Demestichas, P., Koutra, V.,
Intelligent Management Functionality for Improving Transportation Efficiency by Means of the Car Pooling Concept,
ITS(13), No. 2, June 2012, pp. 424-436.
IEEE DOI 1206
BibRef

Moreira-Matias, L., Gama, J., Ferreira, M., Mendes-Moreira, J., Damas, L.,
Predicting Taxi-Passenger Demand Using Streaming Data,
ITS(14), No. 3, 2013, pp. 1393-1402.
IEEE DOI 1309
Sardis Award, Research. Autoregressive integrated moving average (ARIMA) BibRef

Yan, S.Y.[Shang-Yao], Chen, C.Y.[Chun-Ying], Chang, S.C.[Sheng-Chieh],
A Car Pooling Model and Solution Method With Stochastic Vehicle Travel Times,
ITS(15), No. 1, February 2014, pp. 47-61.
IEEE DOI 1403
automobiles BibRef

Pfrommer, J., Warrington, J., Schildbach, G., Morari, M.,
Dynamic Vehicle Redistribution and Online Price Incentives in Shared Mobility Systems,
ITS(15), No. 4, August 2014, pp. 1567-1578.
IEEE DOI 1410
bicycles BibRef

Huang, S.C.[Shih-Chia], Jiau, M.K.[Ming-Kai], Lin, C.,
A Genetic-Algorithm-Based Approach to Solve Carpool Service Problems in Cloud Computing,
ITS(16), No. 1, February 2015, pp. 352-364.
IEEE DOI 1502
Biological cells BibRef

Jiau, M.K.[Ming-Kai], Huang, S.C.[Shih-Chia],
Services-Oriented Computing Using the Compact Genetic Algorithm for Solving the Carpool Services Problem,
ITS(16), No. 5, October 2015, pp. 2711-2722.
IEEE DOI 1511
genetic algorithms BibRef

Arena, M., Azzone, G., Colorni, A., Conte, A., Lue`, A., Nocerino, R.,
Service design in electric vehicle sharing: evidence from Italy,
IET-ITS(9), No. 2, 2015, pp. 145-155.
DOI Link 1504
electric vehicles BibRef

Jorge, D., Correia, G.H.A., Barnhart, C.,
Comparing Optimal Relocation Operations With Simulated Relocation Policies in One-Way Carsharing Systems,
ITS(15), No. 4, August 2014, pp. 1667-1675.
IEEE DOI 1410
mathematical programming BibRef

He, W.[Wen], Hwang, K.[Kai], Li, D.[Deyi],
Intelligent Carpool Routing for Urban Ridesharing by Mining GPS Trajectories,
ITS(15), No. 5, October 2014, pp. 2286-2296.
IEEE DOI 1410
Global Positioning System BibRef

Pelzer, D., Xiao, J.[Jiajian], Zehe, D., Lees, M.H., Knoll, A.C., Aydt, H.,
A Partition-Based Match Making Algorithm for Dynamic Ridesharing,
ITS(16), No. 5, October 2015, pp. 2587-2598.
IEEE DOI 1511
intelligent transportation systems BibRef

Zhang, J., Wen, D., Zeng, S.,
A Discounted Trade Reduction Mechanism for Dynamic Ridesharing Pricing,
ITS(17), No. 6, June 2016, pp. 1586-1595.
IEEE DOI 1606
Companies BibRef

Leng, B., Du, H., Wang, J., Li, L., Xiong, Z.,
Analysis of Taxi Drivers' Behaviors Within a Battle Between Two Taxi Apps,
ITS(17), No. 1, January 2016, pp. 296-300.
IEEE DOI 1601
Cities and towns BibRef

Yuan, W., Deng, P., Taleb, T., Wan, J., Bi, C.,
An Unlicensed Taxi Identification Model Based on Big Data Analysis,
ITS(17), No. 6, June 2016, pp. 1703-1713.
IEEE DOI 1606
Big data BibRef

Yang, G.[Gege], Song, C.[Ci], Shu, H.[Hua], Zhang, J.[Jia], Pei, T.[Tao], Zhou, C.[Chenghu],
Assessing Patient bypass Behavior Using Taxi Trip Origin-Destination (OD) Data,
IJGI(5), No. 9, 2016, pp. 157.
DOI Link 1610
BibRef

Schweizer, J., Bernardi, S., Rupi, F.,
Map-matching algorithm applied to bicycle global positioning system traces in Bologna,
IET-ITS(10), No. 4, 2016, pp. 244-250.
DOI Link 1606
Global Positioning System BibRef

Tang, L.L.[Lu-Liang], Sun, F.[Fei], Kan, Z.[Zihan], Ren, C.[Chang], Cheng, L.L.[Lu-Ling],
Uncovering Distribution Patterns of High Performance Taxis from Big Trace Data,
IJGI(6), No. 5, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Schlote, A., Chen, B., Shorten, R.,
On Closed-Loop Bicycle Availability Prediction,
ITS(16), No. 3, June 2015, pp. 1449-1455.
IEEE DOI 1506
Availability BibRef

Zhang, D.Q., Sun, L., Li, B., Chen, C., Pan, G., Li, S.J., 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 BibRef

Castro, P.S.[Pablo Samuel], Zhang, D.Q.[Da-Qing], Chen, C.[Chao], Li, S.J.[Shi-Jian], Pan, G.[Gang],
From taxi GPS traces to social and community dynamics: A survey,
Surveys(46), No. 2, November 2013, pp. Article No 17.
DOI Link 1402
Vehicles equipped with GPS localizers are an important sensory device for examining people's movements and activities. Taxis equipped with GPS localizers serve the transportation needs of a large number of people driven by diverse needs; BibRef

Wu, H.B.[Hang-Bin], Fan, H.C.[Hong-Chao], Wu, S.Y.[Sheng-Yuan],
Exploring Spatiotemporal Patterns of Long-Distance Taxi Rides in Shanghai,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

An, S.[Shi], Yang, H.[Haiqiang], Wang, J.[Jian],
Revealing Recurrent Urban Congestion Evolution Patterns with Taxi Trajectories,
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. BibRef

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
BibRef

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.J.[Shang-Jing], Huang, M.X.[Meng-Xue], Lü, G.N.[Guo-Nian], 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
BibRef

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 Points of Interest Clustering,
IJGI(8), No. 8, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Fu, X.Y.[Xiao-Yi], Zhang, C.[Ce], Lu, H.[Hua], Xu, J.L.[Jian-Liang],
Efficient matching of offers and requests in social-aware ridesharing,
GeoInfo(23), No. 4, October 2019, pp. 559-589.
WWW Link. 1911
BibRef

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
BibRef

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
BibRef

Ke, J., Yang, H., Zheng, H., Chen, X., Jia, Y., Gong, P., Ye, J.,
Hexagon-Based Convolutional Neural Network for Supply-Demand Forecasting of Ride-Sourcing Services,
ITS(20), No. 11, November 2019, pp. 4160-4173.
IEEE DOI 1911
Forecasting, Urban areas, Automobiles, Convolutional neural networks, Pricing, ride-sourcing service BibRef

Chen, C.C.[Chian-Ching], Tsang, S.S.[Seng-Su],
Predicting adoption of mobile payments from the perspective of taxi drivers,
IET-ITS(13), No. 7, July 2019, pp. 1116-1124.
DOI Link 1906
BibRef

Cao, M.[Min], Cai, B.[Boqin], Ma, S.J.[Shang-Jing], Lü, G.[Guonian], Chen, M.[Min],
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.
DOI Link 1912
BibRef

Yang, Z., Chen, J., Hu, J., Shu, Y., Cheng, P.,
Mobility Modeling and Data-Driven Closed-Loop Prediction in Bike-Sharing Systems,
ITS(20), No. 12, December 2019, pp. 4488-4499.
IEEE DOI 2001
Predictive models, Bicycles, Urban areas, Optimization, Meteorology, Probabilistic logic, Bike-sharing, mobility modeling, Monte Carlo simulation BibRef

Babicheva, T.[Tatiana], Burghout, W.[Wilco], Andreasson, I.[Ingmar], Faul, N.[Nadege],
Empty vehicle redistribution and fleet size in autonomous taxi systems,
IET-ITS(13), No. 4, April 2019, pp. 677-682.
DOI Link 1903
BibRef

Al-Abbasi, A.O., Ghosh, A., Aggarwal, V.,
DeepPool: Distributed Model-Free Algorithm for Ride-Sharing Using Deep Reinforcement Learning,
ITS(20), No. 12, December 2019, pp. 4714-4727.
IEEE DOI 2001
Automobiles, Dispatching, Public transportation, Reinforcement learning, Vehicle dynamics, Real-time systems, distributed algorithm BibRef

Lasmar, E.L., de Paula, F.O., Rosa, R.L., Abrahão, J.I., Rodríguez, D.Z.,
RsRS: Ridesharing Recommendation System Based on Social Networks to Improve the User's QoE,
ITS(20), No. 12, December 2019, pp. 4728-4740.
IEEE DOI 2001
Quality of experience, Machine learning algorithms, Public transportation, Social networking (online), Vehicles, mobile applications BibRef

Zhang, X., Zhao, Z., Zheng, Y., Li, J.,
Prediction of Taxi Destinations Using a Novel Data Embedding Method and Ensemble Learning,
ITS(21), No. 1, January 2020, pp. 68-78.
IEEE DOI 2001
Public transportation, Trajectory, Hidden Markov models, Predictive models, Markov processes, Global Positioning System, ensemble learning BibRef

Qu, B., Yang, W., Cui, G., Wang, X.,
Profitable Taxi Travel Route Recommendation Based on Big Taxi Trajectory Data,
ITS(21), No. 2, February 2020, pp. 653-668.
IEEE DOI 2002
Public transportation, Trajectory, Global Positioning System, Vehicles, Probabilistic logic, Capacity planning, Kalman filters, MapReduce BibRef

Fanti, M.P., Mangini, A.M., Pedroncelli, G., Ukovich, W.,
Fleet Sizing for Electric Car Sharing Systems in Discrete Event System Frameworks,
SMCS(50), No. 3, March 2020, pp. 1161-1177.
IEEE DOI 2002
Optimization, Computational modeling, Automobiles, Cascading style sheets, Analytical models, Mathematical model, transportation BibRef

Li, Y.M.[Yi-Ming], Fang, J.Z.[Jing-Zhi], Zeng, Y.X.[Yu-Xiang], Maag, B.[Balz], Tong, Y.X.[Yong-Xin], Zhang, L.Y.[Ling-Yu],
Two-sided online bipartite matching in spatial data: Experiments and analysis,
GeoInfo(24), No. 1, January 2020, pp. 175-198.
Springer DOI 2002
Matching workers to tasks (sharing economy). BibRef

Huang, S., Lin, J., Jiau, M.,
Global and Local Pareto Optimality in Coevolution for Solving Carpool Service Problem With Time Windows,
ITS(21), No. 3, March 2020, pp. 934-946.
IEEE DOI 2003
Vehicles, Search problems, Sociology, Statistics, Optimization, Convergence, Genetic algorithms, Multi-objective optimization, carpool service problem with time windows BibRef

Jiao, J.F.[Jun-Feng], Bai, S.[Shunhua],
Understanding the Shared E-scooter Travels in Austin, TX,
IJGI(9), No. 2, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Guo, X.G.[Xiao-Gang], Xu, Z.J.[Zhi-Jie], Zhang, J.[Jianqin], Lu, J.[Jian], Zhang, H.[Hao],
An OD Flow Clustering Method Based on Vector Constraints: A Case Study for Beijing Taxi Origin-Destination Data,
IJGI(9), No. 2, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Tang, J., Wang, Y., Hao, W., Liu, F., Huang, H., Wang, Y.,
A Mixed Path Size Logit-Based Taxi Customer-Search Model Considering Spatio-Temporal Factors in Route Choice,
ITS(21), No. 4, April 2020, pp. 1347-1358.
IEEE DOI 2004
Path size logit model, taxi customer searching, route choice model, intersection delays, travel time BibRef

Sun, Y.[Yeran], Ren, Y.[Yinming], Sun, X.[Xuan],
Uber Movement Data: A Proxy for Average One-way Commuting Times by Car,
IJGI(9), No. 3, 2020, pp. xx-yy.
DOI Link 2004
BibRef

Cheng, L.[Luling], Yang, X.[Xue], Tang, L.[Luliang], Duan, Q.[Qian], Kan, Z.[Zihan], Zhang, X.[Xia], Ye, X.Y.[Xin-Yue],
Spatiotemporal Analysis of Taxi-Driver Shifts Using Big Trace Data,
IJGI(9), No. 4, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Chen, P.C.[Po-Chuan], Hsieh, H.Y.[He-Yen], Su, K.W.[Kuan-Wu], Sigalingging, X.K.[Xanno Kharis], Chen, Y.R.[Yan-Ru], Leu, J.S.[Jenq-Shiou],
Predicting station level demand in a bike-sharing system using recurrent neural networks,
IET-ITS(14), No. 6, June 2020, pp. 554-561.
DOI Link 2005
BibRef

Bayrak, A.E., Egilmez, M.M., Kuang, H., Li, X., Park, J.M., Umpfenbach, E., Anderson, E., Gorsich, D., Hu, J., Papalambros, P.Y., Epureanu, B.I.,
A System-of-Systems Approach to the Strategic Feasibility of Modular Vehicle Fleets,
SMCS(50), No. 7, July 2020, pp. 2716-2728.
IEEE DOI 2006
Land vehicles, Maintenance engineering, Manufacturing, US Department of Defense, Atmospheric modeling, Modular vehicle, vehicle fleet BibRef

Jia, R.[Ruo], Li, Z.[Zhekang], Xia, Y.[Yan], Zhu, J.Y.[Jia-Yan], Ma, N.[Nan], Chai, H.[Hua], Liu, Z.[Zhiyuan],
Urban road traffic condition forecasting based on sparse ride-hailing service data,
IET-ITS(14), No. 7, July 2020, pp. 668-674.
DOI Link 2006
BibRef

Wang, Y.L.[Yang-Lan], Zhang, Y.[Yi], Zhang, Y.[Yi], Ma, J.S.[Jiang-Shan],
Dynamic real-time high-capacity ride-sharing model with subsequent information,
IET-ITS(14), No. 7, July 2020, pp. 742-752.
DOI Link 2006
BibRef

Ye, M.[Mao], Zeng, S.[Simeng], Yang, G.X.[Gui-Xin], Chen, Y.J.[Ya-Jing],
Identification of contributing factors on travel mode choice among different resident types with bike-sharing as an alternative,
IET-ITS(14), No. 7, July 2020, pp. 639-646.
DOI Link 2006
BibRef

Wang, S.[Shuofeng], Li, Z.H.[Zhi-Heng], Gu, R.[Ruochen], Xie, N.[Na],
Placement optimisation for station-free bicycle-sharing under 1D distribution assumption,
IET-ITS(14), No. 9, September 2020, pp. 1079-1086.
DOI Link 2008
BibRef

Zhang, X.X.[Xin-Xin], Huang, B.[Bo], Zhu, S.Z.[Shun-Zhi],
Spatiotemporal Varying Effects of Built Environment on Taxi and Ride-Hailing Ridership in New York City,
IJGI(9), No. 8, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Kypriadis, D., Pantziou, G., Konstantopoulos, C., Gavalas, D.,
Optimizing Relocation Cost in Free-Floating Car-Sharing Systems,
ITS(21), No. 9, September 2020, pp. 4017-4030.
IEEE DOI 2008
Automobiles, Legged locomotion, Optimization, Dispatching, Vehicle dynamics, Vehicle sharing systems, electric cars, heuristics BibRef

Yu, X., Shen, S.,
An Integrated Decomposition and Approximate Dynamic Programming Approach for On-Demand Ride Pooling,
ITS(21), No. 9, September 2020, pp. 3811-3820.
IEEE DOI 2008
Vehicles, Delays, Computational modeling, Optimization, Vehicle dynamics, Stochastic processes, Dynamic programming, approximate dynamic programming BibRef

Ren, Y., Zhao, F., Jin, H., Jiao, Z., Meng, L., Zhang, C., Sutherland, J.W.,
Rebalancing Bike Sharing Systems for Minimizing Depot Inventory and Traveling Costs,
ITS(21), No. 9, September 2020, pp. 3871-3882.
IEEE DOI 2008
Bicycles, Routing, Mathematical model, Vehicle dynamics, Mathematical programming, Biological system modeling, mathematical programming BibRef

Salazar, M., Lanzetti, N., Rossi, F., Schiffer, M., Pavone, M.,
Intermodal Autonomous Mobility-on-Demand,
ITS(21), No. 9, September 2020, pp. 3946-3960.
IEEE DOI 2008
Roads, Pricing, Public transportation, Optimization, Urban areas, Legged locomotion, Autonomous vehicles, networks, optimization, public transportation BibRef

Wang, F., Zhu, Y., Wang, F., Liu, J., Ma, X., Fan, X.,
Car4Pac: Last Mile Parcel Delivery Through Intelligent Car Trip Sharing,
ITS(21), No. 10, October 2020, pp. 4410-4424.
IEEE DOI 2010
Automobiles, Task analysis, Logistics, Fuels, Planning, Roads, Intelligent transportation system, trajectory data mining, travel cost prediction BibRef

Zhang, R., Ghanem, R.,
Demand, Supply, and Performance of Street-Hail Taxi,
ITS(21), No. 10, October 2020, pp. 4123-4132.
IEEE DOI 2010
Public transportation, Queueing analysis, Urban areas, Global Positioning System, Analytical models, Supply and demand, congestion BibRef

Hsieh, F.S.[Fu-Shiung],
A Comparative Study of Several Metaheuristic Algorithms to Optimize Monetary Incentive in Ridesharing Systems,
IJGI(9), No. 10, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Liu, Y., Liu, Z., Lyu, C., Ye, J.,
Attention-Based Deep Ensemble Net for Large-Scale Online Taxi-Hailing Demand Prediction,
ITS(21), No. 11, November 2020, pp. 4798-4807.
IEEE DOI 2011
Predictive models, Public transportation, Task analysis, Deep learning, Forecasting, Neural networks, Ensemble learning, demand prediction BibRef

Hua, M.Z.[Ming-Zhuang], Chen, J.X.[Jing-Xu], Chen, X.[Xuewu], Gan, Z.X.[Zuo-Xian], Wang, P.F.[Peng-Fei], Zhao, D.[De],
Forecasting usage and bike distribution of dockless bike-sharing using journey data,
IET-ITS(14), No. 12, December 2020, pp. 1647-1656.
DOI Link 2011
BibRef

Liu, Y., Lyu, C., Khadka, A., Zhang, W., Liu, Z.,
Spatio-Temporal Ensemble Method for Car-Hailing Demand Prediction,
ITS(21), No. 12, December 2020, pp. 5328-5333.
IEEE DOI 2012
Predictive models, Public transportation, Urban areas, Time series analysis, Demand forecasting, Data models, Correlation, fully convolutional networks BibRef

Jin, X.T.[Xue-Ting], Tong, D.Q.[Dao-Qin],
Station-Free Bike Rebalancing Analysis: Scale, Modeling, and Computational Challenges,
IJGI(9), No. 11, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Shen, B.[Boxi], Xu, X.[Xiang], Li, J.[Jun], Plaza, A.[Antonio], Huang, Q.[Qunying],
Unfolding Spatial-Temporal Patterns of Taxi Trip based on an Improved Network Kernel Density Estimation,
IJGI(9), No. 11, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Bistaffa, F., Blum, C., Cerquides, J., Farinelli, A., Rodríguez-Aguilar, J.A.,
A Computational Approach to Quantify the Benefits of Ridesharing for Policy Makers and Travellers,
ITS(22), No. 1, January 2021, pp. 119-130.
IEEE DOI 2012
Automobiles, Quality of service, Peer-to-peer computing, Pollution, Real-time systems, Ridesharing, collective intelligence, integer linear programming BibRef

Zhang, W.B.[Wen-Bo], Xi, Y.F.[Yin-Fei], Ukkusuri, S.V.[Satish V.],
Understanding Spatiotemporal Variations of Ridership by Multiple Taxi Services,
IJGI(9), No. 12, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Schweizer, J.[Joerg], Rupi, F.[Federico], Poliziani, C.[Cristian],
Estimation of link-cost function for cyclists based on stochastic optimisation and GPS traces,
IET-ITS(14), No. 13, 15 December 2020, pp. 1810-1814.
DOI Link 2102
BibRef

Rechkemmer, S.K., Zang, X., Boronka, A., Zhang, W., Sawodny, O.,
Utilization of Smartphone Data for Driving Cycle Synthesis Based on Electric Two-Wheelers in Shanghai,
ITS(22), No. 2, February 2021, pp. 876-886.
IEEE DOI 2102
Data collection, Motorcycles, Data acquisition, Global Positioning System, Instruments, Current measurement, frequency analysis BibRef

Tang, L., Duan, Z., Zhu, Y., Ma, J., Liu, Z.,
Recommendation for Ridesharing Groups Through Destination Prediction on Trajectory Data,
ITS(22), No. 2, February 2021, pp. 1320-1333.
IEEE DOI 2102
Trajectory, Automobiles, Semantics, Roads, Global Positioning System, Ridesharing group, recommendation, destination prediction, trajectory BibRef

Wu, P., Yang, C.H., Chu, F., Zhou, M., Sedraoui, K., Sokhiry, F.S.A.[F. S. Al],
Cost-Profit Trade-Off for Optimally Locating Automotive Service Firms Under Uncertainty,
ITS(22), No. 2, February 2021, pp. 1014-1025.
IEEE DOI 2102
Stochastic processes, Transportation, Computational modeling, Analytical models, Monte Carlo methods, Automotive engineering, distribution-free model BibRef

Gan, Y.T.[Yi-Tong], Fan, H.C.[Hong-Chao], Jiao, W.[Wei], Sun, M.Q.[Meng-Qi],
Exploring the Influence of E-Hailing Applications on the Taxi Industry: From the Perspective of the Drivers,
IJGI(10), No. 2, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Albuquerque, V.[Vitória], Dias, M.S.[Miguel Sales], Bacao, F.[Fernando],
Machine Learning Approaches to Bike-Sharing Systems: A Systematic Literature Review,
IJGI(10), No. 2, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Gong, Y.J., Liu, Y.W., Lin, Y., Chen, W.N., Zhang, J.,
Real-Time Taxi-Passenger Matching Using a Differential Evolutionary Fuzzy Controller,
SMCS(51), No. 5, May 2021, pp. 2712-2725.
IEEE DOI 2104
Public transportation, Optimization, Quality of service, Real-time systems, Bipartite graph, Greedy algorithms, taxi dispatch system BibRef

Toro, J.F., Carrion, D., Brovelli, M.A., Percoco, M.,
Bikemi Bike-sharing Service Exploratory Analysis on Mobility Patterns,
ISPRS20(B4:197-203).
DOI Link 2012
BibRef

Yan, J., Xiang, L., Wu, C., Wu, H.,
City-scale Taxi Demand Prediction Using Multisource Urban Geospatial Data,
ISPRS20(B4:213-220).
DOI Link 2012
BibRef

Berdeddouch, A., Yahyaouy, A., Benanni, Y., Verde, R.,
Deep Based Recommender System For Relevant K Pick-up Points,
ISCV20(1-7)
IEEE DOI 2011
driver information systems, intelligent transportation systems, learning (artificial intelligence), neural nets, Meters BibRef

Naseri Gorgoon, M., Davoodi, M., Davoodi, M., Motieyan, H.,
An Agent-based Modelling for Ride Sharing Optimization Using A* Algorithm and Clustering Approach,
SMPR19(793-796).
DOI Link 1912
BibRef

Mojtabaee, P., Molavi, M., Taleai, M.,
Exploring Driving Factors of Higher Paid Taxi Trips Using Origin-destination Gps Data (case Study: Green Taxis of New York City),
SMPR19(745-748).
DOI Link 1912
BibRef

Coskun, I.B., Sertok, S., Anbaroglu, B.,
K-nearest Neighbour Query Performance Analyses On a Large Scale Taxi Dataset: Postgresql Vs. Mongodb,
C3MGBD19(1531-1538).
DOI Link 1912
BibRef

Wang, H., Chen, X.J., Wang, Y., Shan, J.,
Local Maximum Density Approach for Small-scale Clustering of Urban Taxi Stops,
SmartGeoApps19(1361-1367).
DOI Link 1912
BibRef

Rangriz, S., Davoodi, M., Saberian, J.,
A Novel Approach to Optimize The Ridesharing Problem Using Genetic Algorithm,
SMPR19(875-878).
DOI Link 1912
BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Transit Traffic Analysis, Public Transit, Bus .