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Elsevier DOI
1202
Award, U.V. Helava, ISPRS.
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IEEE DOI
0912
Ad hoc shared ride systems.
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Seow, K.T.,
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1003
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Martin, E.W.,
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Greenhouse Gas Emission Impacts of Carsharing in North America,
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IEEE DOI
1112
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Yan, S.,
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Lin, Y.F.,
A Model With a Heuristic Algorithm for Solving the Long-Term
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IEEE DOI
1112
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Jia, T.[Tao],
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Exploring Human Activity Patterns Using Taxicab Static Points,
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Dimitrakopoulos, G.,
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Intelligent Management Functionality for Improving Transportation
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ITS(13), No. 2, June 2012, pp. 424-436.
IEEE DOI
1206
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Moreira-Matias, L.,
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ITS(14), No. 3, 2013, pp. 1393-1402.
IEEE DOI
1309
Autoregressive integrated moving average (ARIMA)
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Yan, S.Y.[Shang-Yao],
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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.,
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Dynamic Vehicle Redistribution and Online Price Incentives in Shared
Mobility Systems,
ITS(15), No. 4, August 2014, pp. 1567-1578.
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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
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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
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Arena, M.,
Azzone, G.,
Colorni, A.,
Conte, A.,
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Service design in electric vehicle sharing: evidence from Italy,
IET-ITS(9), No. 2, 2015, pp. 145-155.
DOI Link
1504
electric vehicles
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Jorge, D.,
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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
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He, W.[Wen],
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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
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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
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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
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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
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Yang, G.[Gege],
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Shu, H.[Hua],
Zhang, J.[Jia],
Pei, T.[Tao],
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(OD) Data,
IJGI(5), No. 9, 2016, pp. 157.
DOI Link
1610
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Schweizer, J.,
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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
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.[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
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
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.,
Abrahăo, 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],
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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 .