See also Transit Routing, Scheduling, Evaluation.

See also Transit, Bus, Electric Vehicle Issues.

*Lin, W.S.*,
*Sheu, J.W.*,

**Metro Traffic Regulation by Adaptive Optimal Control**,

*ITS(12)*, No. 4, December 2011, pp. 1064-1073.

IEEE DOI
**1112**

BibRef

*Li, L.*,
*Zhang, H.*,
*Wang, X.*,
*Lu, W.*,
*Mu, Z.*,

**Urban Transit Coordination Using an Artificial Transportation System**,

*ITS(12)*, No. 2, June 2011, pp. 374-383.

IEEE DOI
**1101**

BibRef

*Noori, K.*,
*Jenab, K.*,

**Intelligent Traction Control Model for Speed Sensor Vehicles in
Computer-Based Transit System**,

*ITS(13)*, No. 2, June 2012, pp. 680-690.

IEEE DOI
**1206**

BibRef

*Blum, J.J.*,
*Mathew, T.V.*,

**Implications of the computational complexity of transit route network
redesign for metaheuristic optimisation systems**,

*IET-ITS(6)*, No. 2, 2012, pp. 124-131.

DOI Link
**1206**

BibRef

*Zhang, F.*,
*Jin, B.*,
*Wang, Z.*,
*Liu, H.*,
*Hu, J.*,
*Zhang, L.*,

**On Geocasting over Urban Bus-Based Networks by Mining Trajectories**,

*ITS(17)*, No. 6, June 2016, pp. 1734-1747.

IEEE DOI
**1606**

Delays
BibRef

*Jung, J.[Jaeyoung]*,
*Sohn, K.[Keemin]*,

**Deep-learning architecture to forecast destinations of bus passengers
from entry-only smart-card data**,

*IET-ITS(11)*, No. 6, August 2017, pp. 334-339.

DOI Link
**1707**

BibRef

*Chen, C.[Chao]*,
*Zhang, D.[Daqing]*,
*Li, N.[Nan]*,
*Zhou, Z.H.[Zhi-Hua]*,

**B-Planner: Planning Bidirectional Night Bus Routes Using Large-Scale
Taxi GPS Traces**,

*ITS(15)*, No. 4, August 2014, pp. 1451-1465.

IEEE DOI
**1410**

Global Positioning System
BibRef

*Zhang, G.*,
*Zhang, H.*,
*Li, L.*,
*Dai, C.*,

**Agent-Based Simulation and Optimization of Urban Transit System**,

*ITS(15)*, No. 2, April 2014, pp. 589-596.

IEEE DOI
**1404**

Algorithm design and analysis
BibRef

*Wang, Y.H.[Yi-Hui]*,
*de Schutter, B.*,
*van den Boom, T.J.J.*,
*Ning, B.[Bin]*,
*Tang, T.[Tao]*,

**Efficient Bilevel Approach for Urban Rail Transit Operation With
Stop-Skipping**,

*ITS(15)*, No. 6, December 2014, pp. 2658-2670.

IEEE DOI
**1412**

integer programming
BibRef

*van der Hurk, E.*,
*Kroon, L.*,
*Maroti, G.*,
*Vervest, P.*,

**Deduction of Passengers' Route Choices From Smart Card Data**,

*ITS(16)*, No. 1, February 2015, pp. 430-440.

IEEE DOI
**1502**

Clocks
BibRef

*Lin, Y.*,
*Wan, H.*,
*Jiang, R.*,
*Wu, Z.*,
*Jia, X.*,

**Inferring the Travel Purposes of Passenger Groups for Better
Understanding of Passengers**,

*ITS(16)*, No. 1, February 2015, pp. 235-243.

IEEE DOI
**1502**

Business
BibRef

*Syrjarinne, P.*,
*Nummenmaa, J.*,
*Thanisch, P.*,
*Kerminen, R.*,
*Hakulinen, E.*,

**Analysing traffic fluency from bus data**,

*IET-ITS(9)*, No. 6, 2015, pp. 566-572.

DOI Link
**1509**

data mining
BibRef

*Hosu, A.C.*,
*Kiss, Z.I.*,
*Ivanciu, I.A.*,
*Varga, M.*,
*Polgar, Z.A.*,

**Integrated ubiquitous connectivity and centralised information
platform for intelligent public transportation systems**,

*IET-ITS(9)*, No. 6, 2015, pp. 573-581.

DOI Link
**1509**

public transport
BibRef

*Daszczuk, W.B.*,
*Choromanski, W.*,
*Mies´cicki, J.*,
*Grabski, W.*,

**Empty vehicles management as a method for reducing passenger waiting
time in Personal Rapid Transit networks**,

*IET-ITS(9)*, No. 3, 2015, pp. 231-239.

DOI Link
**1506**

demand forecasting
BibRef

*Cadarso, L.*,
*Maroti, G.*,
*Marin, A.*,

**Smooth and Controlled Recovery Planning of Disruptions in Rapid
Transit Networks**,

*ITS(16)*, No. 4, August 2015, pp. 2192-2202.

IEEE DOI
**1508**

Computational modeling
BibRef

*An, S.[Shi]*,
*Zhang, X.M.[Xin-Ming]*,
*Wang, J.[Jian]*,

**Finding Causes of Irregular Headways Integrating Data Mining and AHP**,

*IJGI(4)*, No. 4, 2015, pp. 2604.

DOI Link
**1601**

Transit system flows.
BibRef

*Nunes, A.A.*,
*Galvao Dias, T.*,
*Falcao e Cunha, J.*,

**Passenger Journey Destination Estimation From Automated Fare
Collection System Data Using Spatial Validation**,

*ITS(17)*, No. 1, January 2016, pp. 133-142.

IEEE DOI
**1601**

Accuracy
BibRef

*Pinelli, F.*,
*Nair, R.*,
*Calabrese, F.*,
*Berlingerio, M.*,
*di Lorenzo, G.*,
*Sbodio, M.L.*,

**Data-Driven Transit Network Design From Mobile Phone Trajectories**,

*ITS(17)*, No. 6, June 2016, pp. 1724-1733.

IEEE DOI
**1606**

Antennas
BibRef

*Liu, Z.*,
*Jiang, S.*,
*Zhou, P.*,
*Li, M.*,

**A Participatory Urban Traffic Monitoring System:
The Power of Bus Riders**,

*ITS(18)*, No. 10, October 2017, pp. 2851-2864.

IEEE DOI
**1710**

Global Positioning System, Mobile handsets, Monitoring, Probes,
Roads, Sensors, Urban areas, Urban traffic monitoring, bus riders,
bus systems, cellular signal, participatory, sensing
BibRef

*Zhao, J.*,
*Zhang, F.*,
*Tu, L.*,
*Xu, C.*,
*Shen, D.*,
*Tian, C.*,
*Li, X.Y.*,
*Li, Z.*,

**Estimation of Passenger Route Choice Pattern Using Smart Card Data
for Complex Metro Systems**,

*ITS(18)*, No. 4, April 2017, pp. 790-801.

IEEE DOI
**1704**

Estimation
BibRef

*Zhao, J.*,
*Qu, Q.*,
*Zhang, F.*,
*Xu, C.*,
*Liu, S.*,

**Spatio-Temporal Analysis of Passenger Travel Patterns in Massive
Smart Card Data**,

*ITS(18)*, No. 11, November 2017, pp. 3135-3146.

IEEE DOI
**1711**

Companies, Data mining, Global Positioning System, Smart cards,
Space exploration, Transportation, Urban areas,
Passenger behavior analysis, metro system, smart card data,
spatio-temporal, analysis
BibRef

*Zhou, Y.[Yang]*,
*Fang, Z.X.[Zhi-Xiang]*,
*Zhan, Q.M.[Qing-Ming]*,
*Huang, Y.P.[Ya-Ping]*,
*Fu, X.W.[Xiong-Wu]*,

**Inferring Social Functions Available in the Metro Station Area from
Passengers' Staying Activities in Smart Card Data**,

*IJGI(6)*, No. 12, 2017, pp. xx-yy.

DOI Link
**1801**

BibRef

*Ni, M.*,
*He, Q.*,
*Gao, J.*,

**Forecasting the Subway Passenger Flow Under Event Occurrences With
Social Media**,

*ITS(18)*, No. 6, June 2017, pp. 1623-1632.

IEEE DOI
**1706**

Forecasting, Predictive models, Public transportation, Tagging,
Twitter, Social media, event identification, social sensing,
subway passenger flow prediction, transit, ridership
BibRef

*Singh, P.[Parul]*,
*Oh, K.[Kyuhyup]*,
*Jung, J.Y.[Jae-Yoon]*,

**Flow Orientation Analysis for Major Activity Regions Based on Smart
Card Transit Data**,

*IJGI(6)*, No. 10, 2017, pp. xx-yy.

DOI Link
**1710**

BibRef

*Dong, X.*,
*Lin, Y.*,
*Shen, D.*,
*Li, Z.*,
*Zhu, F.*,
*Hu, B.*,
*Fan, D.*,
*Xiong, G.*,

**A Parallel Transportation Management and Control System for Bus Rapid
Transit Using the ACP Approach**,

*ITS(18)*, No. 9, September 2017, pp. 2569-2574.

IEEE DOI
**1709**

ACP approach, BRT adaptive operations,
BRT forecasting, BRT incident management, BRT monitoring,
BRT warning, Guangzhou BRT, PTMS-BRT, artificial systems,
bus rapid transit, complex system theory,
mass transit service improvement,
parallel transportation management-and-control system,
Roads, Scheduling, ACP approach,
artificial transportation system,
dynamic perception,
BibRef

*Zhu, F.*,
*Li, Z.*,
*Chen, S.*,
*Xiong, G.*,

**Parallel Transportation Management and Control System and Its
Applications in Building Smart Cities**,

*ITS(17)*, No. 6, June 2016, pp. 1576-1585.

IEEE DOI
**1606**

Artificial intelligence
BibRef

*Xiong, G.*,
*Shen, D.*,
*Dong, X.*,
*Hu, B.*,
*Fan, D.*,
*Zhu, F.*,

**Parallel Transportation Management and Control System for Subways**,

*ITS(18)*, No. 7, July 2017, pp. 1974-1979.

IEEE DOI
**1706**

Accidents, Control systems, Generators, Monitoring, Planning,
Public transportation, ACP approach, Subways,
artificial subway system, computational experiments platform,
parallel execution system, status, perception
BibRef

*Zhang, J.*,
*Shen, D.*,
*Tu, L.*,
*Zhang, F.*,
*Xu, C.*,
*Wang, Y.*,
*Tian, C.*,
*Li, X.*,
*Huang, B.*,
*Li, Z.*,

**A Real-Time Passenger Flow Estimation and Prediction Method for Urban
Bus Transit Systems**,

*ITS(18)*, No. 11, November 2017, pp. 3168-3178.

IEEE DOI
**1711**

Estimation, Forecasting, Global Positioning System,
Neural networks, Real-time systems, Smart cards, Transportation,
BibRef

*Meng, X.L.[Xue-Lei]*,
*Jia, L.M.[Li-Min]*,
*Xiang, W.L.[Wan-Li]*,

**Complex network model for railway timetable stability optimisation**,

*IET-ITS(12)*, No. 10, December 2018, pp. 1369-1377.

DOI Link
**1812**

BibRef

*Ding, X.B.[Xiao-Bing]*,
*Liu, Z.G.[Zhi-Gang]*,
*Xu, H.B.[Hai-Bo]*,

**The passenger flow status identification based on image and WiFi
detection for urban rail transit stations**,

*JVCIR(58)*, 2019, pp. 119-129.

Elsevier DOI
**1901**

Rail transit, Safety of stations,
Passenger flow identification, Emergency warning
BibRef

*Cong, J.M.[Jia-Min]*,
*Gao, L.J.[Lin-Jie]*,
*Juan, Z.C.[Zhi-Cai]*,

**Improved algorithms for trip-chain estimation using massive student
behaviour data from urban transit systems**,

*IET-ITS(13)*, No. 3, March 2019, pp. 435-442.

DOI Link
**1903**

BibRef

*Jin, H.T.[Hai-Tao]*,
*Jin, F.J.[Feng-Jun]*,
*Zhu, H.[He]*,

**Measuring Spatial Mismatch between Public Transit Services and
Regular Riders: A Case Study of Beijing**,

*IJGI(8)*, No. 4, 2019, pp. xx-yy.

DOI Link
**1905**

BibRef

*Duan, Z.Y.[Zheng-Yu]*,
*Lei, Z.X.[Zeng-Xiang]*,
*Zhang, M.[Michael]*,
*Li, H.F.[Hai-Feng]*,
*Yang, D.Y.[Dong-Yuan]*,

**Understanding multiple days' metro travel demand at aggregate level**,

*IET-ITS(13)*, No. 5, May 2019, pp. 756-763.

DOI Link
**1906**

BibRef

*Wang, W.Y.[Wei-Yang]*,
*Hu, J.[Jia]*,
*Ji, Y.X.[Yu-Xiong]*,
*Du, Y.C.[Yu-Chuan]*,

**Improving fuel efficiency of connected and automated transit buses on
signallised corridors**,

*IET-ITS(13)*, No. 5, May 2019, pp. 870-879.

DOI Link
**1906**

BibRef

*Ma, X.*,
*Zhang, J.*,
*Du, B.*,
*Ding, C.*,
*Sun, L.*,

**Parallel Architecture of Convolutional Bi-Directional LSTM Neural
Networks for Network-Wide Metro Ridership Prediction**,

*ITS(20)*, No. 6, June 2019, pp. 2278-2288.

IEEE DOI
**1906**

Feature extraction, Predictive models, Data models,
Spatiotemporal phenomena, Forecasting, Neural networks,
parallel structure
BibRef

*Hou, Z.*,
*Dong, H.*,
*Gao, S.*,
*Nicholson, G.*,
*Chen, L.*,
*Roberts, C.*,

**Energy-Saving Metro Train Timetable Rescheduling Model Considering
ATO Profiles and Dynamic Passenger Flow**,

*ITS(20)*, No. 7, July 2019, pp. 2774-2785.

IEEE DOI
**1907**

Delays, Energy consumption, Rail transportation, Software,
Numerical models, Heuristic algorithms, Linear programming,
ATO profile
BibRef

*Feng, J.*,
*Ye, Z.*,
*Wang, C.*,
*Xu, M.*,
*Labi, S.*,

**An Integrated Optimization Model for Energy Saving in Metro
Operations**,

*ITS(20)*, No. 8, August 2019, pp. 3059-3069.

IEEE DOI
**1908**

Energy consumption, Acceleration, Optimization, Kinetic energy,
Switches, Mathematical model, Genetic algorithms, Timetable, speed,
cataclysmic genetic algorithm
BibRef

*Li, W.*,
*Cao, J.*,
*Guan, J.*,
*Zhou, S.*,
*Liang, G.*,
*So, W.K.Y.*,
*Szczecinski, M.*,

**A General Framework for Unmet Demand Prediction in On-Demand
Transport Services**,

*ITS(20)*, No. 8, August 2019, pp. 2820-2830.

IEEE DOI
**1908**

Public transportation, Feature extraction, Predictive models,
Vehicles, Vehicle dynamics, Data mining,
prediction model
BibRef

*Han, Y.[Yong]*,
*Wang, S.[Shukang]*,
*Ren, Y.[Yibin]*,
*Wang, C.[Cheng]*,
*Gao, P.[Peng]*,
*Chen, G.[Ge]*,

**Predicting Station-Level Short-Term Passenger Flow in a Citywide
Metro Network Using Spatiotemporal Graph Convolutional Neural
Networks**,

*IJGI(8)*, No. 6, 2019, pp. xx-yy.

DOI Link
**1908**

BibRef

*Guo, Z.Q.A.[Zhi-Qi-Ang]*,
*Zhao, X.[Xin]*,
*Chen, Y.X.[Ya-Xin]*,
*Wu, W.[Wei]*,
*Yang, J.[Jie]*,

**Short-term passenger flow forecast of urban rail transit based on GPR
and KRR**,

*IET-ITS(13)*, No. 9, September 2019, pp. 1374-1382.

DOI Link
**1908**

BibRef

*Pang, J.*,
*Huang, J.*,
*Du, Y.*,
*Yu, H.*,
*Huang, Q.*,
*Yin, B.*,

**Learning to Predict Bus Arrival Time From Heterogeneous Measurements
via Recurrent Neural Network**,

*ITS(20)*, No. 9, September 2019, pp. 3283-3293.

IEEE DOI
**1909**

Global Positioning System, Time measurement,
Recurrent neural networks, Task analysis, Transportation,
multi-step-ahead prediction
BibRef

*Koehler, L.A.*,
*Seman, L.O.*,
*Kraus, W.*,
*Camponogara, E.*,

**Real-Time Integrated Holding and Priority Control Strategy for
Transit Systems**,

*ITS(20)*, No. 9, September 2019, pp. 3459-3469.

IEEE DOI
**1909**

Delays, Indexes, Real-time systems, Automobiles, Optimization,
Predictive models, BRT, bus bunching, bus headway control,
transit signal priority
BibRef

*Liu, H.*,
*Zhou, M.*,
*Guo, X.*,
*Zhang, Z.*,
*Ning, B.*,
*Tang, T.*,

**Timetable Optimization for Regenerative Energy Utilization in Subway
Systems**,

*ITS(20)*, No. 9, September 2019, pp. 3247-3257.

IEEE DOI
**1909**

Optimization, Public transportation, Acceleration,
Mathematical model, Resistors, Genetic algorithms,
artificial bee colony
BibRef

*Qiu, G.*,
*Song, R.*,
*He, S.*,
*Xu, W.*,
*Jiang, M.*,

**Clustering Passenger Trip Data for the Potential Passenger
Investigation and Line Design of Customized Commuter Bus**,

*ITS(20)*, No. 9, September 2019, pp. 3351-3360.

IEEE DOI
**1909**

Clustering algorithms, Smart cards, Urban areas, Planning,
Estimation, Prediction algorithms,
density-based spatial clustering algorithm
BibRef

*Li, M.[Minmin]*,
*Guo, R.Z.[Ren-Zhong]*,
*Li, Y.[You]*,
*He, B.[Biao]*,
*Fan, Y.[Yong]*,

**The Distribution Pattern of the Railway Network in China at the
County Level**,

*IJGI(8)*, No. 8, 2019, pp. xx-yy.

DOI Link
**1909**

BibRef

*Yang, D.[Dan]*,
*Chen, K.[Kairun]*,
*Yang, M.N.[Meng-Ning]*,
*Zhao, X.C.[Xiao-Chao]*,

**Urban rail transit passenger flow forecast based on LSTM with enhanced
long-term features**,

*IET-ITS(13)*, No. 10, October 2019, pp. 1475-1482.

DOI Link
**1909**

BibRef

*Han, Y.[Yong]*,
*Wang, C.[Cheng]*,
*Ren, Y.[Yibin]*,
*Wang, S.K.[Shu-Kang]*,
*Zheng, H.C.[Huang-Cheng]*,
*Chen, G.[Ge]*,

**Short-Term Prediction of Bus Passenger Flow Based on a Hybrid
Optimized LSTM Network**,

*IJGI(8)*, No. 9, 2019, pp. xx-yy.

DOI Link
**1909**

BibRef

*Huang, J.W.[Jian-Wei]*,
*Liu, X.T.[Xin-Tao]*,
*Zhao, P.X.[Peng-Xiang]*,
*Zhang, J.W.[Jun-Wei]*,
*Kwan, M.P.[Mei-Po]*,

**Interactions between Bus, Metro, and Taxi Use before and after the
Chinese Spring Festival**,

*IJGI(8)*, No. 10, 2019, pp. xx-yy.

DOI Link
**1910**

BibRef

*Zhao, J.*,
*Zhou, X.*,

**Improving the Operational Efficiency of Buses With Dynamic Use of
Exclusive Bus Lane at Isolated Intersections**,

*ITS(20)*, No. 2, February 2019, pp. 642-653.

IEEE DOI
**1902**

Delays, Optimization, Vehicle dynamics, Roads, Resource management,
Legged locomotion, Exclusive bus lane, dynamic control,
signalized intersections
BibRef

*Pili, F.[Francesco]*,
*Olivo, A.[Alessandro]*,
*Barabino, B.[Benedetto]*,

**Evaluating alternative methods to estimate bus running times by
archived automatic vehicle location data**,

*IET-ITS(13)*, No. 3, March 2019, pp. 523-530.

DOI Link
**1903**

BibRef

*He, P.*,
*Jiang, G.*,
*Lam, S.*,
*Tang, D.*,

**Travel-Time Prediction of Bus Journey With Multiple Bus Trips**,

*ITS(20)*, No. 11, November 2019, pp. 4192-4205.

IEEE DOI
**1911**

Trajectory, Public transportation, Predictive models,
Real-time systems, Prediction algorithms, Data models,
interval-based historical average
BibRef

*Jia, F.F.[Fei-Fan]*,
*Li, H.Y.[Hai-Ying]*,
*Jiang, X.[Xi]*,
*Xu, X.Y.[Xin-Yue]*,

**Deep learning-based hybrid model for short-term subway passenger flow
prediction using automatic fare collection data**,

*IET-ITS(13)*, No. 11, November 2019, pp. 1708-1716.

DOI Link
**1911**

BibRef

*Moyo, T.*,
*Musakwa, W.*,

**Exploring The Potential of Crowd Sourced Data to Map Commuter Points Of
Interest: a Case Study of Johannesburg**,

*C3MGBD19*(1587-1592).

DOI Link
**1912**

BibRef

*Yang, X.P.[Xi-Ping]*,
*Lu, S.W.[Shi-Wei]*,
*Zhao, W.F.[Wei-Feng]*,
*Zhao, Z.Y.[Zhi-Yuan]*,

**Exploring the Characteristics of an Intra-Urban Bus Service Network:
A Case Study of Shenzhen, China**,

*IJGI(8)*, No. 11, 2019, pp. xx-yy.

DOI Link
**1912**

BibRef

*Cui, Z.Y.[Zhi-Yong]*,
*Long, Y.[Ying]*,

**Perspectives on stability and mobility of transit passenger's travel
behaviour through smart card data**,

*IET-ITS(13)*, No. 12, December 2019, pp. 1761-1769.

DOI Link
**1912**

BibRef

*Chen, X.[Xi]*,
*Wang, Y.H.[Yin-Hai]*,
*Tang, J.J.[Jin-Jun]*,
*Dai, Z.[Zhuang]*,
*Ma, X.L.[Xiao-Lei]*,

**Examining regional mobility patterns of public transit and automobile
users based on the smart card and mobile Internet data: a case study of
Chengdu, China**,

*IET-ITS(14)*, No. 1, January 2020, pp. 45-55.

DOI Link
**2001**

BibRef

*Gokasar, I.*,
*Cetinel, Y.*,
*Baydogan, M.G.*,

**Estimation of Influence Distance of Bus Stops Using Bus GPS Data and
Bus Stop Properties**,

*ITS(20)*, No. 12, December 2019, pp. 4635-4642.

IEEE DOI
**2001**

Vegetation, Global Positioning System, Public transportation,
Linear regression, Regression tree analysis, Data mining,
public transport
BibRef

*Barabino, B.*,
*Coni, M.*,
*Olivo, A.*,
*Pungillo, G.*,
*Rassu, N.*,

**Standing Passenger Comfort: A New Scale for Evaluating the Real-Time
Driving Style of Bus Transit Services**,

*ITS(20)*, No. 12, December 2019, pp. 4665-4678.

IEEE DOI
**2001**

Kinematics, Parameter estimation, Intelligent vehicles,
Accelerometers, On-board bus comfort,
passengers' perceptions
BibRef

*Zhang, Y.*,
*Cheng, T.*,

**A Deep Learning Approach to Infer Employment Status of Passengers by
Using Smart Card Data**,

*ITS(21)*, No. 2, February 2020, pp. 617-629.

IEEE DOI
**2002**

Employment, Feature extraction, Deep learning, Predictive models,
Smart cards, Transportation, Correlation, Deep learning,
temporal travel behavior
BibRef

*Markou, I.*,
*Rodrigues, F.*,
*Pereira, F.C.*,

**Is Travel Demand Actually Deep? An Application in Event Areas Using
Semantic Information**,

*ITS(21)*, No. 2, February 2020, pp. 641-652.

IEEE DOI
**2002**

Public transportation, Predictive models, Urban areas,
Deep learning, Internet, Semantics, Time series forecasting,
deep Gaussian processes
BibRef

*Falsafain, H.*,
*Tamannaei, M.*,

**A Novel Dynamic Programming Approach to the Train Marshalling Problem**,

*ITS(21)*, No. 2, February 2020, pp. 701-710.

IEEE DOI
**2002**

Heuristic algorithms, Optimization, Complexity theory,
Dynamic programming, Approximation algorithms, Search problems,
train marshalling problem
BibRef

*Islam, M.F.[Md Faqhrul]*,
*Fonzone, A.[Achille]*,
*MacIver, A.[Andrew]*,
*Dickinson, K.[Keith]*,

**Use of ubiquitous real-time bus passenger information**,

*IET-ITS(14)*, No. 3, March 2020, pp. 139-147.

DOI Link
**2003**

BibRef

*Hu, R.[Rong]*,
*Chiu, Y.C.[Yi-Chang]*,
*Hsieh, C.W.[Chih-Wei]*,

**Crowding prediction on mass rapid transit systems using a weighted
bidirectional recurrent neural network**,

*IET-ITS(14)*, No. 3, March 2020, pp. 196-203.

DOI Link
**2003**

BibRef

*Jiao, J.F.[Jun-Feng]*,
*Cai, M.M.[Ming-Ming]*,

**Using Open Source Data to Identify Transit Deserts in Four Major
Chinese Cities**,

*IJGI(9)*, No. 2, 2020, pp. xx-yy.

DOI Link
**2003**

BibRef

*Du, B.*,
*Peng, H.*,
*Wang, S.*,
*Bhuiyan, M.Z.A.*,
*Wang, L.*,
*Gong, Q.*,
*Liu, L.*,
*Li, J.*,

**Deep Irregular Convolutional Residual LSTM for Urban Traffic
Passenger Flows Prediction**,

*ITS(21)*, No. 3, March 2020, pp. 972-985.

IEEE DOI
**2003**

Predictive models, Deep learning, Market research, Data models,
Convolution, Public transportation, urban computing
BibRef

*Achar, A.*,
*Bharathi, D.*,
*Kumar, B.A.*,
*Vanajakshi, L.*,

**Bus Arrival Time Prediction: A Spatial Kalman Filter Approach**,

*ITS(21)*, No. 3, March 2020, pp. 1298-1307.

IEEE DOI
**2003**

Travel time prediction, Kalman filter, time series, non-stationary
BibRef

*Chen, E.*,
*Ye, Z.*,
*Wang, C.*,
*Xu, M.*,

**Subway Passenger Flow Prediction for Special Events Using Smart Card
Data**,

*ITS(21)*, No. 3, March 2020, pp. 1109-1120.

IEEE DOI
**2003**

Public transportation, Data models, Predictive models,
Analytical models, Autoregressive processes, Smart cards,
Asymmetry
BibRef

*Laskaris, G.*,
*Seredynski, M.*,
*Viti, F.*,

**Enhancing Bus Holding Control Using Cooperative ITS**,

*ITS(21)*, No. 4, April 2020, pp. 1767-1778.

IEEE DOI
**2004**

Public transport, holding strategy, cooperative ITS, driver advisory systems
BibRef

*Zhang, K.*,
*Liu, Z.*,
*Zheng, L.*,

**Short-Term Prediction of Passenger Demand in Multi-Zone Level:
Temporal Convolutional Neural Network With Multi-Task Learning**,

*ITS(21)*, No. 4, April 2020, pp. 1480-1490.

IEEE DOI
**2004**

Short-term passenger demand prediction, multi-task learning,
deep learning, convolutional neural network
BibRef

*Seo, J.[Jeongwook]*,
*Cho, S.H.[Shin-Hyung]*,
*Kim, D.K.[Dong-Kyu]*,
*Park, P.Y.J.[Peter Young-Jin]*,

**Analysis of overlapping origin-destination pairs between bus stations
to enhance the efficiency of bus operations**,

*IET-ITS(14)*, No. 6, June 2020, pp. 545-553.

DOI Link
**2005**

BibRef

*Jenelius, E.*,

**Data-Driven Metro Train Crowding Prediction Based on Real-Time Load
Data**,

*ITS(21)*, No. 6, June 2020, pp. 2254-2265.

IEEE DOI
**2006**

Real-time systems, Automobiles, Load modeling, Predictive models,
Focusing, Regression tree analysis, Public transit, metro, crowding,
boosted tree ensemble
BibRef

*Liu, R.*,
*Li, S.*,
*Yang, L.*,
*Yin, J.*,

**Energy-Efficient Subway Train Scheduling Design With Time-Dependent
Demand Based on an Approximate Dynamic Programming Approach**,

*SMCS(50)*, No. 7, July 2020, pp. 2475-2490.

IEEE DOI
**2006**

Public transportation, Energy consumption, Optimization,
Computational modeling, Heuristic algorithms,
train scheduling
BibRef

*Daszczuk, W.B.*,

**Measures of Structure and Operation of Automated Transit Networks**,

*ITS(21)*, No. 7, July 2020, pp. 2966-2979.

IEEE DOI
**2007**

Benchmark testing, Entropy, Throughput, Analytical models,
Intelligent transportation systems, Size measurement,
systems engineering and theory-modeling-simulation-systems simulation
BibRef

*Xia, F.*,
*Wang, J.*,
*Kong, X.*,
*Zhang, D.*,
*Wang, Z.*,

**Ranking Station Importance With Human Mobility Patterns Using Subway
Network Datasets**,

*ITS(21)*, No. 7, July 2020, pp. 2840-2852.

IEEE DOI
**2007**

Public transportation, Planning, Complex networks,
Analytical models, Urban areas, Human mobility patterns,
subway networks
BibRef

*Michalak, M.[Marcin]*,
*Górka, W.[Wojciech]*,
*Baginski, J.[Jacek]*,
*Rogowski, D.[Dariusz]*,
*Socha, M.[Michal]*,
*Steclik, T.[Tomasz]*,
*Flisiuk, B.[Barbara]*,
*Lesniak, D.[Dawid]*,
*Sikora, M.[Marek]*,

**Central threat register- a complex system for risk analysis and
decision support in railway transport**,

*IET-ITS(14)*, No. 8, August 2020, pp. 970-981.

DOI Link
**2007**

BibRef

*Sharmila, R.B.*,
*Velaga, N.R.[Nagendra R.]*,
*Choudhary, P.[Pushpa]*,

**Bus arrival time prediction and measure of uncertainties using survival
models**,

*IET-ITS(14)*, No. 8, August 2020, pp. 900-907.

DOI Link
**2007**

BibRef

*Cheng, Q.[Qian]*,
*Deng, W.[Wei]*,
*Raza, M.A.[Muhammad Ammar]*,

**Analysis of the departure time choices of metro passengers during peak
hours**,

*IET-ITS(14)*, No. 8, August 2020, pp. 866-872.

DOI Link
**2007**

BibRef

*Zhang, L.[Lukai]*,
*Feng, X.S.[Xue-Song]*,
*Ding, C.C.[Chuan-Chen]*,
*Liu, Y.[Yi]*,

**Mitigating errors of predicted delays of a train at neighbouring stops**,

*IET-ITS(14)*, No. 8, August 2020, pp. 873-879.

DOI Link
**2007**

BibRef

*Yenisetty, P.T.[Pavan Teja]*,
*Bahadure, P.[Pankaj]*,

**Measuring Accessibility to Various ASFs from Public Transit using
Spatial Distance Measures in Indian Cities**,

*IJGI(9)*, No. 7, 2020, pp. xx-yy.

DOI Link
**2007**

BibRef

*Lv, J.*,
*Sun, Q.*,
*Li, Q.*,
*Moreira-Matias, L.*,

**Multi-Scale and Multi-Scope Convolutional Neural Networks for
Destination Prediction of Trajectories**,

*ITS(21)*, No. 8, August 2020, pp. 3184-3195.

IEEE DOI
**2008**

Trajectory, Public transportation, Prediction algorithms,
Predictive models, Clustering algorithms, Hidden Markov models,
convolutional neural network (CNN)
BibRef

*Wepulanon, P.*,
*Sumalee, A.*,
*Lam, W.H.K.*,

**Temporal Signatures of Passive Wi-Fi Data for Estimating Bus
Passenger Waiting Time at a Single Bus Stop**,

*ITS(21)*, No. 8, August 2020, pp. 3366-3376.

IEEE DOI
**2008**

Wireless fidelity, Estimation, Monitoring, Mobile handsets, Sensors,
Intelligent transportation systems, Time measurement,
passenger waiting time estimation
BibRef

*Lin, D.[Diao]*,
*Zhu, R.X.[Ruo-Xin]*,
*Yang, J.[Jian]*,
*Meng, L.Q.[Li-Qiu]*,

**An Open-Source Framework of Generating Network-Based Transit
Catchment Areas by Walking**,

*IJGI(9)*, No. 8, 2020, pp. xx-yy.

DOI Link
**2008**

BibRef

*Cai, Z.*,
*Li, T.*,
*Su, X.*,
*Guo, L.*,
*Ding, Z.*,

**Research on Analysis Method of Characteristics Generation of Urban
Rail Transit**,

*ITS(21)*, No. 9, September 2020, pp. 3608-3620.

IEEE DOI
**2008**

Rails, Urban areas, Public transportation, Predictive models,
Planning, Semantics, Urban rail transit, RC-tree, top-k retrieval,
similarity
BibRef

*Li, N.*,
*Kong, L.*,
*Shu, W.*,
*Wu, M.*,

**Benefits of Short-Distance Walking and Fast-Route Scheduling in
Public Vehicle Service**,

*ITS(21)*, No. 9, September 2020, pp. 3706-3717.

IEEE DOI
**2008**

Legged locomotion, Vehicles, Roads, Public transportation,
Urban areas, Public vehicle, passenger delivery, efficiency
BibRef

*Zhang, J.L.[Jin-Lei]*,
*Chen, F.[Feng]*,
*Guo, Y.[Yinan]*,
*Li, X.H.[Xiao-Hong]*,

**Multi-graph convolutional network for short-term passenger flow
forecasting in urban rail transit**,

*IET-ITS(14)*, No. 10, October 2020, pp. 1210-1217.

DOI Link
**2009**

BibRef

*Zhang, J.L.[Jin-Lei]*,
*Chen, F.[Feng]*,
*Cui, Z.Y.[Zhi-Yong]*,
*Guo, Y.[Yinan]*,
*Zhu, Y.[Yadi]*,

**Deep Learning Architecture for Short-Term Passenger Flow Forecasting
in Urban Rail Transit**,

*ITS(22)*, No. 11, November 2021, pp. 7004-7014.

IEEE DOI
**2112**

Predictive models, Atmospheric modeling, Deep learning,
Public transportation, Meteorology, Mathematical model,
short-term passenger flow forecasting
BibRef

*Gkiotsalitis, K.*,
*Eikenbroek, O.A.L.*,
*Cats, O.*,

**Robust Network-Wide Bus Scheduling With Transfer Synchronizations**,

*ITS(21)*, No. 11, November 2020, pp. 4582-4592.

IEEE DOI
**2011**

Dispatching, Schedules, Rails, Optimization,
Intelligent transportation systems, Cats, Bus scheduling, minimax,
transfer coordination
BibRef

*Seman, L.O.*,
*Koehler, L.A.*,
*Camponogara, E.*,
*Zimmermann, L.*,
*Kraus, W.*,

**Headway Control in Bus Transit Corridors Served by Multiple Lines**,

*ITS(21)*, No. 11, November 2020, pp. 4680-4692.

IEEE DOI
**2011**

Modeling, Schedules, Indexes, Predictive control, Feedback control,
Reliability, Real-time systems, Reserved bus lane, shared lanes,
holding control
BibRef

*Zhong, X.Z.[Xin-Zhi]*,
*Zou, Y.J.[Ya-Jie]*,
*Dong, Z.[Zhi]*,
*Yuan, S.X.[Shao-Xin]*,
*Ijaz, M.[Muhammad]*,

**Finite mixture survival model for examining the variability of urban
arterial travel time for buses, passenger cars and taxis**,

*IET-ITS(14)*, No. 12, December 2020, pp. 1524-1533.

DOI Link
**2011**

BibRef

*Johari, M.[Mansour]*,
*Keyvan-Ekbatani, M.[Mehdi]*,
*Ngoduy, D.[Dong]*,

**Impacts of bus stop location and berth number on urban network traffic
performance**,

*IET-ITS(14)*, No. 12, December 2020, pp. 1546-1554.

DOI Link
**2011**

BibRef

*Gkiotsalitis, K.[Konstantinos]*,

**Bus scheduling considering trip-varying travel times, vehicle
availability and capacity**,

*IET-ITS(14)*, No. 12, December 2020, pp. 1594-1605.

DOI Link
**2011**

BibRef

*Han, S.[Shuang]*,
*Fu, H.[Hui]*,
*Zhao, J.H.[Jia-Hong]*,
*Lin, J.Z.[Jun-Zhou]*,
*Zeng, W.L.[Wei-Liang]*,

**Modelling and simulation of hierarchical scheduling of real-time
responsive customised bus**,

*IET-ITS(14)*, No. 12, December 2020, pp. 1615-1625.

DOI Link
**2011**

BibRef

*Zheng, F.F.[Fang-Fang]*,
*Chen, J.B.[Jin-Biao]*,
*Wang, H.[Heng]*,
*Liu, H.[Henry]*,
*Liu, X.B.[Xiao-Bo]*,

**Developing a dynamic utilisation scheme for exclusive bus lanes on
urban expressways: an enhanced CTM-based approach versus a
microsimulation-based approach**,

*IET-ITS(14)*, No. 12, December 2020, pp. 1657-1664.

DOI Link
**2011**

BibRef

*Bai, Y.*,
*Hu, Q.*,
*Ho, T.K.*,
*Guo, H.*,
*Mao, B.*,

**Timetable Optimization for Metro Lines Connecting to Intercity
Railway Stations to Minimize Passenger Waiting Time**,

*ITS(22)*, No. 1, January 2021, pp. 79-90.

IEEE DOI
**2012**

Mathematical model, Rail transportation, Optimization,
Predictive models, Genetic algorithms, Rails, Legged locomotion,
interior-point algorithm
BibRef

*Tong, P.*,
*Du, W.*,
*Li, M.*,
*Huang, J.*,
*Wang, W.*,
*Qin, Z.*,

**Last-Mile School Shuttle Planning With Crowdsensed Student
Trajectories**,

*ITS(22)*, No. 1, January 2021, pp. 293-306.

IEEE DOI
**2012**

Trajectory, Planning, Data structures, Optimization, Roads,
Wireless fidelity, Last-mile shuttle planning,
graph-based data structure
BibRef

*Shi, Z.C.[Zhi-Cheng]*,
*Pun-Cheng, L.S.C.[Lilian S. C.]*,
*Liu, X.[Xintao]*,
*Lai, J.H.[Jian-Hui]*,
*Tong, C.Z.[Cheng-Zhuo]*,
*Zhang, A.[Anshu]*,
*Zhang, M.[Min]*,
*Shi, W.Z.[Wen-Zhong]*,

**Analysis of the Temporal Characteristics of the Elderly Traveling by
Bus Using Smart Card Data**,

*IJGI(9)*, No. 12, 2020, pp. xx-yy.

DOI Link
**2012**

BibRef

*Zhang, Y.Y.[You-Yang]*,
*Zhu, C.F.[Chang-Feng]*,
*Wang, Q.R.[Qing-Rong]*,

**LightGBM-based model for metro passenger volume forecasting**,

*IET-ITS(14)*, No. 13, 15 December 2020, pp. 1815-1823.

DOI Link
**2102**

BibRef

*Shi, R.*,
*Steenkiste, P.*,
*Veloso, M.M.*,

**Improving the On-Vehicle Experience of Passengers Through SC-M*:
A Scalable Multi-Passenger Multi-Criteria Mobility Planner**,

*ITS(22)*, No. 2, February 2021, pp. 1026-1040.

IEEE DOI
**2102**

Planning, Urban areas, Path planning, Interference, Sociology,
Statistics, Scalability, Public transit system,
time-expanded graph
BibRef

*Perera, T.[Thilina]*,
*Wijesundera, D.[Deshya]*,
*Wijerathna, L.[Lahiru]*,
*Srikanthan, T.[Thambipillai]*,

**Directionality-centric bus transit network segmentation for on-demand
public transit**,

*IET-ITS(14)*, No. 13, 15 December 2020, pp. 1871-1881.

DOI Link
**2102**

BibRef

*Song, M.L.[Ming-Li]*,
*Jia, G.[Guangshe]*,

**Performance and Productivity of Regional Air Transport Systems in
China**,

*IJGI(10)*, No. 2, 2021, pp. xx-yy.

DOI Link
**2103**

BibRef

*Cui, H.F.[Hai-Fu]*,
*Wu, L.[Liang]*,
*Hu, S.[Sheng]*,
*Lu, R.J.[Ru-Juan]*,

**Measuring the Service Capacity of Public Facilities Based on a
Dynamic Voronoi Diagram**,

*RS(13)*, No. 5, 2021, pp. xx-yy.

DOI Link
**2103**

BibRef

*Ran, X.C.[Xin-Chen]*,
*Chen, S.K.[Shao-Kuan]*,
*Liu, G.H.[Ge-Hui]*,
*Bai, Y.[Yun]*,

**Energy-efficient approach combining train speed profile and timetable
optimisations for metro operations**,

*IET-ITS(14)*, No. 14, 27 December 2020, pp. 1967-1977.

DOI Link
**2103**

BibRef

*Lin, P.F.[Peng-Fei]*,
*Weng, J.C.[Jian-Cheng]*,
*Brands, D.K.[Devi K.]*,
*Qian, H.M.[Hui-Min]*,
*Yin, B.C.[Bao-Cai]*,

**Analysing the relationship between weather, built environment, and
public transport ridership**,

*IET-ITS(14)*, No. 14, 27 December 2020, pp. 1946-1954.

DOI Link
**2103**

BibRef

*Zheng, Z.H.[Zhi-Hao]*,
*Ling, X.M.[Xi-Man]*,
*Wang, P.[Pu]*,
*Xiao, J.H.[Jian-He]*,
*Zhang, F.[Fan]*,

**Hybrid model for predicting anomalous large passenger flow in urban
metros**,

*IET-ITS(14)*, No. 14, 27 December 2020, pp. 1987-1996.

DOI Link
**2103**

BibRef

*Ruiz-Pérez, M.[Maurici]*,
*Seguí-Pons, J.M.[Joana Maria]*,

**Bus Service Level and Horizontal Equity Analysis in the Context of
the Modifiable Areal Unit Problem**,

*IJGI(10)*, No. 3, 2021, pp. xx-yy.

DOI Link
**2104**

BibRef

*Das, R.D.[Rahul Deb]*,

**Understanding Users' Satisfaction towards Public Transit System in
India: A Case-Study of Mumbai**,

*IJGI(10)*, No. 3, 2021, pp. xx-yy.

DOI Link
**2104**

BibRef

*Li, B.[Bowen]*,
*Huang, Z.D.[Zheng-Dong]*,
*Xia, J.Z.[Ji-Zhe]*,
*Li, W.S.[Wen-Shu]*,
*Zhang, Y.[Ying]*,

**Coupling Degree between the Demand and Supply of Bus Services at
Stops: A Density-Based Approach**,

*IJGI(10)*, No. 3, 2021, pp. xx-yy.

DOI Link
**2104**

BibRef

*Wang, W.*,
*Zong, F.*,
*Yao, B.*,

**A Proactive Real-Time Control Strategy Based on Data-Driven Transit
Demand Prediction**,

*ITS(22)*, No. 4, April 2021, pp. 2404-2416.

IEEE DOI
**2104**

Real-time systems, Reliability, Dispatching, Public transportation,
Monitoring, Data-driven transit demand prediction,
dispatching time
BibRef

*Tang, J.*,
*Yang, Y.*,
*Hao, W.*,
*Liu, F.*,
*Wang, Y.*,

**A Data-Driven Timetable Optimization of Urban Bus Line Based on
Multi-Objective Genetic Algorithm**,

*ITS(22)*, No. 4, April 2021, pp. 2417-2429.

IEEE DOI
**2104**

Optimization, Global Positioning System, Companies,
Genetic algorithms, Smart cards, Encoding, Scheduling, Urban transit,
non-dominated sorting genetic algorithm-II (NSGA-II)
BibRef

*Lu, T.*,
*Yao, E.*,
*Zhang, Y.*,
*Yang, Y.*,

**Joint Optimal Scheduling for a Mixed Bus Fleet Under Micro Driving
Conditions**,

*ITS(22)*, No. 4, April 2021, pp. 2464-2475.

IEEE DOI
**2104**

Optimal scheduling, Job shop scheduling, Task analysis,
Transportation, Acceleration, Roads, Reliability, Bus scheduling,
vehicle scheduling
BibRef

*Yang, H.*,
*Zhang, Z.*,
*Fan, W.*,
*Xiao, F.*,

**Optimal Design for Demand Responsive Connector Service Considering
Elastic Demand**,

*ITS(22)*, No. 4, April 2021, pp. 2476-2486.

IEEE DOI
**2104**

Reliability, Numerical models, Uncertainty, Optimization, Connectors,
Transportation, Standards, Demand responsive connector,
traveling salesman problem
BibRef

*Liu, Y.*,
*Lyu, C.*,
*Liu, X.*,
*Liu, Z.*,

**Automatic Feature Engineering for Bus Passenger Flow Prediction Based
on Modular Convolutional Neural Network**,

*ITS(22)*, No. 4, April 2021, pp. 2349-2358.

IEEE DOI
**2104**

Machine learning, Microscopy, Integrated circuits, Neural networks,
Feature extraction, Time series analysis,
passenger flow prediction
BibRef

*Wu, W.*,
*Xia, Y.*,
*Jin, W.*,

**Predicting Bus Passenger Flow and Prioritizing Influential Factors
Using Multi-Source Data: Scaled Stacking Gradient Boosting Decision
Trees**,

*ITS(22)*, No. 4, April 2021, pp. 2510-2523.

IEEE DOI
**2104**

Predictive models, Data models, Boosting, Deep learning, Stacking,
Transportation, Decision trees, Public transport,
scaled stacking gradient boosting decision trees
BibRef

*Manchella, K.*,
*Umrawal, A.K.*,
*Aggarwal, V.*,

**FlexPool: A Distributed Model-Free Deep Reinforcement Learning
Algorithm for Joint Passengers and Goods Transportation**,

*ITS(22)*, No. 4, April 2021, pp. 2035-2047.

IEEE DOI
**2104**

Transportation, Reinforcement learning, Fuels, Adaptation models,
Urban areas, Public transportation, Heuristic algorithms,
fleet management
BibRef

*Iovino, L.[Ludovico]*,
*Nguyen, P.T.[Phuong T.]*,
*di Salle, A.[Amleto]*,
*Gallo, F.[Francesco]*,
*Flammini, M.[Michele]*,

**Unavailable Transit Feed Specification:
Making It Available with Recurrent Neural Networks**,

*ITS(22)*, No. 4, April 2021, pp. 2111-2122.

IEEE DOI
**2104**

Recurrent neural networks, Predictive models, Data mining,
Real-time systems, Hidden Markov models,
LSTM
BibRef

*Kazhamiakin, R.*,
*Loria, E.*,
*Marconi, A.*,
*Scanagatta, M.*,

**A Gamification Platform to Analyze and Influence Citizens' Daily
Transportation Choices**,

*ITS(22)*, No. 4, April 2021, pp. 2153-2167.

IEEE DOI
**2104**

Games, Urban areas, Public transportation, Ecosystems, Statistics,
Sociology, Engines, Sustainable mobility, smart city, gamification,
behavior change
BibRef

*Han, Y.[Yong]*,
*Peng, T.X.[Tong-Xin]*,
*Wang, C.[Cheng]*,
*Zhang, Z.H.[Zhi-Hao]*,
*Chen, G.[Ge]*,

**A Hybrid GLM Model for Predicting Citywide Spatio-Temporal Metro
Passenger Flow**,

*IJGI(10)*, No. 4, 2021, pp. xx-yy.

DOI Link
**2104**

BibRef

*Inturri, G.[Giuseppe]*,
*Giuffrida, N.[Nadia]*,
*Le Pira, M.[Michela]*,
*Fazio, M.[Martina]*,
*Ignaccolo, M.[Matteo]*,

**Linking Public Transport User Satisfaction with Service Accessibility
for Sustainable Mobility Planning**,

*IJGI(10)*, No. 4, 2021, pp. xx-yy.

DOI Link
**2104**

BibRef

*Lu, K.[Kai]*,
*Liu, J.T.[Jiang-Tao]*,
*Zhou, X.S.[Xue-Song]*,
*Han, B.M.[Bao-Ming]*,

**A Review of Big Data Applications in Urban Transit Systems**,

*ITS(22)*, No. 5, May 2021, pp. 2535-2552.

IEEE DOI
**2105**

Real-time systems, Optimization, Big Data applications,
Smart phones, Data models, Smart cards, Planning,
transit policy application
BibRef

*Díez-Jiménez, E.[Efrén]*,
*Fernández-Muñoz, M.[Miguel]*,
*Oliva-Domínguez, R.[Rubén]*,
*Fernández-Llorca, D.[David]*,
*Sotelo, M.Á.[Miguel Ángel]*,

**Personal Rapid Transport System Compatible With Current Railways and
Metros Infrastructure**,

*ITS(22)*, No. 5, May 2021, pp. 2891-2901.

IEEE DOI
**2105**

Rails, Rail transportation, Estimation, Wheels, Urban areas,
Autonomous vehicles, Person rapid transit, underground, subway,
individual transport
BibRef

*Bucchiarone, A.[Antonio]*,
*Battisti, S.[Sandro]*,
*Marconi, A.[Annapaola]*,
*Maldacea, R.[Roberto]*,
*Ponce, D.C.[Diego Cardona]*,

**Autonomous Shuttle-as-a-Service (ASaaS):
Challenges, Opportunities, and Social Implications**,

*ITS(22)*, No. 6, June 2021, pp. 3790-3799.

IEEE DOI
**2106**

Autonomous vehicles, Biological system modeling, Automobiles,
Safety, Smart cities, Smart mobility, autonomous shuttles,
mobility services
BibRef

*Sun, C.[Chao]*,
*Zhang, P.[Peng]*,
*Shi, Y.J.[Yu-Ji]*,
*Chang, Y.L.[Yu-Lin]*,

**Sensor Location Strategy and Scaling Rate Inference for
Origin-Destination Demand Estimation**,

*ITS(22)*, No. 6, June 2021, pp. 3455-3467.

IEEE DOI
**2106**

Estimation, Stochastic processes, Mobile handsets, Bayes methods,
Sociology, Statistics, Numerical models, Origin-destination demand,
Bayesian model
BibRef

*Li, P.Q.[Pei-Qing]*,
*Zhang, S.F.[Shun-Feng]*,
*Zhong, B.Q.[Bi-Qiang]*,
*Wu, J.[Jin]*,
*Zhang, H.[Hao]*,
*Chen, Y.K.[Yi-Kai]*,
*Fu, Y.[Yang]*,
*Wang, Q.B.[Qi-Bing]*,
*Li, Q.[Qipeng]*,

**Service quality evaluation of bus lines based on improved momentum
back-propagation neural network model: A study of Hangzhou in China**,

*IET-ITS(15)*, No. 7, 2021, pp. 958-972.

DOI Link
**2106**

BibRef

*Feng, F.[Fenling]*,
*Zhang, J.Q.[Jia-Qi]*,
*Liu, C.G.[Cheng-Guang]*,
*Li, W.[Wan]*,
*Jiang, Q.W.[Qi-Wei]*,

**Short-term railway passenger demand forecast using improved
Wasserstein generative adversarial nets and web search terms**,

*IET-ITS(15)*, No. 3, 2021, pp. 432-445.

DOI Link
**2106**

BibRef

*Xie, Z.[Ze]*,
*Zhu, J.S.[Jian-Sheng]*,
*Wang, F.Z.[Fu-Zhang]*,
*Li, W.[Wen]*,
*Wang, T.[Tuo]*,

**Long short-term memory based anomaly detection: A case study of China
railway passenger ticketing system**,

*IET-ITS(15)*, No. 1, 2021, pp. 98-106.

DOI Link
**2106**

BibRef

*Jing, Y.[Yun]*,
*Hu, H.T.[Hong-Tao]*,
*Guo, S.[Siye]*,
*Wang, X.[Xuan]*,
*Chen, F.Q.[Fang-Qiu]*,

**Short-Term Prediction of Urban Rail Transit Passenger Flow in
External Passenger Transport Hub Based on LSTM-LGB-DRS**,

*ITS(22)*, No. 7, July 2021, pp. 4611-4621.

IEEE DOI
**2107**

Rails, Predictive models, Adaptation models, Prediction algorithms,
Data models, Heuristic algorithms, Urban rail transit,
feature engineering
BibRef

*Qi, G.[Geqi]*,
*Ceder, A.[Avishai]*,
*Huang, A.[Ailing]*,
*Guan, W.[Wei]*,

**A Methodology to Attain Public Transit Origin-Destination Mobility
Patterns Using Multi-Layered Mesoscopic Analysis**,

*ITS(22)*, No. 10, October 2021, pp. 6256-6274.

IEEE DOI
**2110**

Urban areas, Tensile stress, Data mining, Clustering methods,
Smart cards, Correlation, Intelligent transportation systems,
smart card data
BibRef

*Hadjidimitriou, N.S.[Natalia Selini]*,
*Lippi, M.[Marco]*,
*Mamei, M.[Marco]*,

**A Data Driven Approach to Match Demand and Supply for Public
Transport Planning**,

*ITS(22)*, No. 10, October 2021, pp. 6384-6394.

IEEE DOI
**2110**

Global Positioning System, Clustering algorithms,
Mobile handsets, Public transportation, Urban areas, Estimation,
data fusion
BibRef

*Luo, D.[Dan]*,
*Zhao, D.[Dong]*,
*Ke, Q.[Qixue]*,
*You, X.Y.[Xiao-Yong]*,
*Liu, L.[Liang]*,
*Zhang, D.[Desheng]*,
*Ma, H.D.[Hua-Dong]*,
*Zuo, X.Q.[Xing-Quan]*,

**Fine-Grained Service-Level Passenger Flow Prediction for Bus Transit
Systems Based on Multitask Deep Learning**,

*ITS(22)*, No. 11, November 2021, pp. 7184-7199.

IEEE DOI
**2112**

Deep learning, Communications technology, Correlation, Urban areas,
Computer science, Predictive models, deep learning
BibRef

*Kumar, P.[Pramesh]*,
*Khani, A.[Alireza]*,

**Evaluating Special Event Transit Demand:
A Robust Principal Component Analysis Approach**,

*ITS(22)*, No. 12, December 2021, pp. 7370-7382.

IEEE DOI
**2112**

Matrix decomposition, Principal component analysis, Planning,
Road transportation, Smart cards, Estimation, Special event, outlier detection
BibRef

*Wang, J.C.[Jing-Cheng]*,
*Zhang, Y.[Yong]*,
*Wei, Y.[Yun]*,
*Hu, Y.L.[Yong-Li]*,
*Piao, X.L.[Xing-Lin]*,
*Yin, B.C.[Bao-Cai]*,

**Metro Passenger Flow Prediction via Dynamic Hypergraph Convolution
Networks**,

*ITS(22)*, No. 12, December 2021, pp. 7891-7903.

IEEE DOI
**2112**

Predictive models, Public transportation, Convolution,
Neural networks, Graph neural networks, Forecasting, Urban areas,
graph neural network
BibRef

*Zhu, K.L.[Kang-Li]*,
*Yin, H.D.[Hao-Dong]*,
*Qu, Y.C.[Yun-Chao]*,
*Wu, J.J.[Jian-Jun]*,

**Measuring the Similarity of Metro Stations Based on the Passenger
Visit Distribution**,

*IJGI(11)*, No. 1, 2022, pp. xx-yy.

DOI Link
**2201**

BibRef

*Ang, K.L.M.[Kenneth Li-Minn]*,
*Seng, J.K.P.[Jasmine Kah Phooi]*,
*Ngharamike, E.[Ericmoore]*,
*Ijemaru, G.K.[Gerald K.]*,

**Emerging Technologies for Smart Cities' Transportation:
Geo-Information, Data Analytics and Machine Learning Approaches**,

*IJGI(11)*, No. 2, 2022, pp. xx-yy.

DOI Link
**2202**

BibRef

*Wang, X.[Xi]*,
*Li, S.[Shukai]*,
*Tang, T.[Tao]*,
*Yang, L.X.[Li-Xing]*,

**Event-Triggered Predictive Control for Automatic Train Regulation and
Passenger Flow in Metro Rail Systems**,

*ITS(23)*, No. 3, March 2022, pp. 1782-1795.

IEEE DOI
**2203**

Delays, Schedules, Predictive control, Rails, Rail transportation,
Real-time systems, Dynamic scheduling,
model predictive control (MPC)
BibRef

*Haliem, M.[Marina]*,
*Aggarwal, V.[Vaneet]*,
*Bhargava, B.[Bharat]*,

**AdaPool: A Diurnal-Adaptive Fleet Management Framework Using
Model-Free Deep Reinforcement Learning and Change Point Detection**,

*ITS(23)*, No. 3, March 2022, pp. 2471-2481.

IEEE DOI
**2203**

Adaptation models, Dispatching, Vehicle dynamics, Planning,
Heuristic algorithms, Urban areas, Reinforcement learning,
non-stationary MDPs
BibRef

*Liu, L.B.[Ling-Bo]*,
*Chen, J.W.[Jing-Wen]*,
*Wu, H.F.[He-Feng]*,
*Zhen, J.J.[Jia-Jie]*,
*Li, G.B.[Guan-Bin]*,
*Lin, L.[Liang]*,

**Physical-Virtual Collaboration Modeling for Intra- and Inter-Station
Metro Ridership Prediction**,

*ITS(23)*, No. 4, April 2022, pp. 3377-3391.

IEEE DOI
**2204**

Topology, Network topology, Correlation, Predictive models,
Convolution, Task analysis, Logic gates, Metro system,
virtual topology
BibRef

*Chen, E.[Enhui]*,
*Zhang, W.B.[Wen-Bo]*,
*Ye, Z.[Zhirui]*,
*Yang, M.[Min]*,

**Unraveling Latent Transfer Patterns Between Metro and Bus From
Large-Scale Smart Card Data**,

*ITS(23)*, No. 4, April 2022, pp. 3351-3365.

IEEE DOI
**2204**

Smart cards, Data models, Analytical models, Urban areas,
Probabilistic logic, Legged locomotion, Correlation,
latent pattern
BibRef

*Xue, G.[Gang]*,
*Liu, S.F.[Shi-Feng]*,
*Gong, D.[Daqing]*,

**Identifying Abnormal Riding Behavior in Urban Rail Transit:
A Survey on 'In-Out' in the Same Subway Station**,

*ITS(23)*, No. 4, April 2022, pp. 3201-3213.

IEEE DOI
**2204**

Public transportation, Rails, Feature extraction,
Predictive models, Law enforcement, Data models, Abnormal behavior,
urban rail transit
BibRef

*Liu, S.[Shasha]*,
*Yamamoto, T.[Toshiyuki]*,
*Yao, E.[Enjian]*,
*Nakamura, T.[Toshiyuki]*,

**Exploring Travel Pattern Variability of Public Transport Users
Through Smart Card Data: Role of Gender and Age**,

*ITS(23)*, No. 5, May 2022, pp. 4247-4256.

IEEE DOI
**2205**

Smart cards, Aging, Pattern analysis,
Intelligent transportation systems, Clustering algorithms,
smart card data
BibRef

*Li, C.[Can]*,
*Bai, L.[Lei]*,
*Liu, W.[Wei]*,
*Yao, L.[Lina]*,
*Waller, S.T.[S Travis]*,

**Graph Neural Network for Robust Public Transit Demand Prediction**,

*ITS(23)*, No. 5, May 2022, pp. 4086-4098.

IEEE DOI
**2205**

Predictive models, Uncertainty, Convolution, Correlation,
Demand forecasting, Bayes methods, Planning,
Bayesian inference
BibRef

*Wen, S.T.[Shi-Ting]*,
*Gao, Y.J.[Yun-Jun]*,
*Zhang, D.[Detian]*,
*Yang, J.Q.[Jin-Qiu]*,
*Li, Q.[Qing]*,

**An Efficient Data Acquisition System for Large Numbers of Various
Vehicle Terminals**,

*ITS(23)*, No. 5, May 2022, pp. 4720-4725.

IEEE DOI
**2205**

Data acquisition, Quality of service, Transportation,
Real-time systems, Streaming media, Servers, Encapsulation,
intelligent transportation
BibRef

*Yang, H.[Hong]*,
*Ruan, Z.[Zehan]*,
*Li, W.S.[Wen-Shu]*,
*Zhu, H.J.[Huan-Jie]*,
*Zhao, J.[Jie]*,
*Peng, J.D.[Jian-Dong]*,

**The Impact of Built Environment Factors on Elderly People's
Mobility Characteristics by Metro System Considering Spatial
Heterogeneity**,

*IJGI(11)*, No. 5, 2022, pp. xx-yy.

DOI Link
**2206**

BibRef

*Noursalehi, P.[Peyman]*,
*Koutsopoulos, H.N.[Haris N.]*,
*Zhao, J.H.[Jin-Hua]*,

**Dynamic Origin-Destination Prediction in Urban Rail Systems: A
Multi-Resolution Spatio-Temporal Deep Learning Approach**,

*ITS(23)*, No. 6, June 2022, pp. 5106-5115.

IEEE DOI
**2206**

Predictive models, Discrete wavelet transforms,
Real-time systems, Data models, Deep learning,
origin-destination demand
BibRef

*Zhang, Y.[Yi]*,
*Su, R.[Rong]*,
*Zhang, Y.C.[Yi-Cheng]*,
*Guruge, N.S.G.[Nadeesha Sandamali Gammana]*,

**A Multi-Bus Dispatching Strategy Based on Boarding Control**,

*ITS(23)*, No. 6, June 2022, pp. 5029-5043.

IEEE DOI
**2206**

Dispatching, Vehicle dynamics, Optimization, Schedules,
Genetic algorithms, Uncertainty, Solid modeling, genetic algorithm
BibRef

*Zhang, Y.[Yi]*,
*Su, R.[Rong]*,
*Zhang, Y.C.[Yi-Cheng]*,
*Wang, B.[Bohui]*,

**Dynamic Multi-Bus Dispatching Strategy With Boarding and Holding
Control for Passenger Delay Alleviation and Schedule Reliability: A
Combined Dispatching-Operation System**,

*ITS(23)*, No. 8, August 2022, pp. 12846-12860.

IEEE DOI
**2208**

Dispatching, Optimization, Delays, Mathematical models, Schedules,
Reliability, Costs, Public transport systems,
Lagrangian relaxation
BibRef

*Wu, C.F.[Chih-Fu]*,
*Gao, C.[Chenhui]*,
*Lin, K.C.[Kai-Chieh]*,
*Chang, Y.H.[Yi-Hsin]*,

**Evaluating Impacts of Bus Route Map Design and Dynamic Real-Time
Information Presentation on Bus Route Map Search Efficiency and
Cognitive Load**,

*IJGI(11)*, No. 6, 2022, pp. xx-yy.

DOI Link
**2206**

BibRef

*Zhang, Z.H.[Zhi-Hao]*,
*Han, Y.[Yong]*,
*Peng, T.X.[Tong-Xin]*,
*Li, Z.X.[Zhen-Xin]*,
*Chen, G.[Ge]*,

**A Comprehensive Spatio-Temporal Model for Subway Passenger Flow
Prediction**,

*IJGI(11)*, No. 6, 2022, pp. xx-yy.

DOI Link
**2206**

BibRef

*Chen, P.F.[Peng-Fei]*,
*Fu, X.[Xuandi]*,
*Wang, X.[Xue]*,

**A Graph Convolutional Stacked Bidirectional Unidirectional-LSTM
Neural Network for Metro Ridership Prediction**,

*ITS(23)*, No. 7, July 2022, pp. 6950-6962.

IEEE DOI
**2207**

Forecasting, Predictive models, Convolution, Time series analysis,
Feature extraction, Deep learning, Correlation,
parallel structure
BibRef

*Lin, H.F.[Hai-Feng]*,
*Tang, C.[Chengpei]*,

**Intelligent Bus Operation Optimization by Integrating Cases and Data
Driven Based on Business Chain and Enhanced Quantum Genetic Algorithm**,

*ITS(23)*, No. 7, July 2022, pp. 9869-9882.

IEEE DOI
**2207**

Scheduling, Quantum computing, Optimization, Job shop scheduling,
Computational modeling, Heuristic algorithms, Dispatching,
travel feature analysis
BibRef

*Wang, K.[Kai]*,
*Tsung, F.[Fugee]*,

**Sparse and Robust Multivariate Functional Principal Component
Analysis for Passenger Flow Pattern Discovery in Metro Systems**,

*ITS(23)*, No. 7, July 2022, pp. 8367-8379.

IEEE DOI
**2207**

Principal component analysis, Eigenvalues and eigenfunctions,
Correlation, Robustness, Rail transportation, Market research,
sparsity regularization
BibRef

*Wei, Z.H.[Zhong-Hua]*,
*Liang, J.X.[Jing-Xuan]*,
*Qiu, S.[Shi]*,
*Wang, S.F.[Shao-Fan]*,
*Liu, S.[Sheng]*,

**How Many Facilities are Needed? Evaluating Configurations of Subway
Security Check Systems via a Hybrid Queueing Model**,

*ITS(23)*, No. 7, July 2022, pp. 8209-8222.

IEEE DOI
**2207**

Public transportation, Security, Atmospheric modeling, Airports,
Data models, Detectors, Queueing analysis, density flow map
BibRef

*Bešinovic, N.[Nikola]*,
*Wang, Y.H.[Yi-Hui]*,
*Zhu, S.W.[Song-Wei]*,
*Quaglietta, E.[Egidio]*,
*Tang, T.[Tao]*,
*Goverde, R.M.P.[Rob M. P.]*,

**A Matheuristic for the Integrated Disruption Management of Traffic,
Passengers and Stations in Urban Railway Lines**,

*ITS(23)*, No. 8, August 2022, pp. 10380-10394.

IEEE DOI
**2208**

Logic gates, Rail transportation, Mathematical model, Rails, Delays,
Iterative methods, Safety, Railway, disruption, resilience, passengers,
stations
BibRef

*Borges, R.M.[Rafael Mendes]*,
*Quaglietta, E.[Egidio]*,

**Assessing Hyperloop Transport Capacity Under Moving-Block and Virtual
Coupling Operations**,

*ITS(23)*, No. 8, August 2022, pp. 12612-12621.

IEEE DOI
**2208**

Rail transportation, Mathematical models, Junctions,
Electron tubes, Safety, Switches, Couplings, High-speed transport,
virtual coupling
BibRef

*Wang, T.[Tao]*,
*Xu, K.Y.[Ke-Yu]*,
*Tian, J.[Junfang]*,
*Zhang, J.[Jing]*,
*Gao, Z.Y.[Zi-You]*,
*Li, S.[Shubin]*,

**Boarding Time Estimation Using the Passenger Density Distribution on
the Bus**,

*ITS(23)*, No. 8, August 2022, pp. 13429-13442.

IEEE DOI
**2208**

Predictive models, Schedules, Uncertainty, Numerical models, Delays,
Data models, Business process re-engineering, Service time,
potential field
BibRef

*Fan, Z.Y.[Zhuang-Yuan]*,
*Zhang, F.[Fan]*,
*Loo, B.P.Y.[Becky P. Y.]*,

**Rhythm of Transit Stations - Uncovering the Activity-Travel Dynamics
of Transit-Oriented Development in the U.S.**,

*ITS(23)*, No. 8, August 2022, pp. 12503-12517.

IEEE DOI
**2208**

Urban areas, Fans, Planning, Space stations, Employment,
Density measurement, Clustering algorithms,
clustering analysis
BibRef

*Mo, B.[Baichuan]*,
*Zhao, Z.[Zhan]*,
*Koutsopoulos, H.N.[Haris N.]*,
*Zhao, J.H.[Jin-Hua]*,

**Individual Mobility Prediction in Mass Transit Systems Using Smart
Card Data: An Interpretable Activity-Based Hidden Markov Approach**,

*ITS(23)*, No. 8, August 2022, pp. 12014-12026.

IEEE DOI
**2208**

Hidden Markov models, Predictive models, Smart cards, Data models,
Spatiotemporal phenomena, History, Markov processes,
public transit
BibRef

*Xu, Z.Z.[Zi-Zhen]*,
*Chopra, S.S.[Shauhrat S.]*,
*Lee, H.[Hellas]*,

**Resilient Urban Public Transportation Infrastructure: A Comparison of
Five Flow-Weighted Metro Networks in Terms of the Resilience Cycle
Framework**,

*ITS(23)*, No. 8, August 2022, pp. 12688-12699.

IEEE DOI
**2208**

Resilience, Robustness, Measurement, Complex networks,
Public transportation, Urban areas, Faces, Complex network,
system performance
BibRef

*Zhao, J.J.[Juan-Juan]*,
*Zhang, L.[Liutao]*,
*Ye, J.X.[Jie-Xia]*,
*Xu, C.Z.[Cheng-Zhong]*,

**MDLF: A Multi-View-Based Deep Learning Framework for Individual Trip
Destination Prediction in Public Transportation Systems**,

*ITS(23)*, No. 8, August 2022, pp. 13316-13329.

IEEE DOI
**2208**

Global Positioning System, Predictive models, Feature extraction,
Real-time systems, Data models, Deep learning, Trajectory,
individual mobility
BibRef

*Wang, D.[Di]*,
*Dewancker, B.[Bart]*,
*Duan, Y.Q.[Ya-Qiong ]*,
*Zhao, M.[Meng]*,

**Exploring Spatial Features of Population Activities and Functional
Facilities in Rail Transit Station Realm Based on Real-Time
Positioning Data: A Case of Xi'an Metro Line 2**,

*IJGI(11)*, No. 9, 2022, pp. xx-yy.

DOI Link
**2209**

BibRef

*Büchel, B.[Beda]*,
*Corman, F.[Francesco]*,

**What Do We Know When? Modeling Predictability of Transit Operations**,

*ITS(23)*, No. 9, September 2022, pp. 15684-15695.

IEEE DOI
**2209**

Predictive models, Stochastic processes, Reliability, Delays,
Mathematical models, Real-time systems, Decision making,
travel time variability
BibRef

*Guimarães, M.[Marta]*,
*Soares, C.[Cláudia]*,
*Ventura, R.[Rodrigo]*,

**Decision Support Models for Predicting and Explaining Airport
Passenger Connectivity From Data**,

*ITS(23)*, No. 9, September 2022, pp. 16005-16015.

IEEE DOI
**2209**

Delays, Airports, Atmospheric modeling, Schedules, Costs,
Predictive models, Aircraft, Airline schedule planning,
decision support models
BibRef

*Kong, X.J.[Xiang-Jie]*,
*Wang, K.[Kailai]*,
*Hou, M.L.[Ming-Liang]*,
*Xia, F.[Feng]*,
*Karmakar, G.[Gour]*,
*Li, J.X.[Jian-Xin]*,

**Exploring Human Mobility for Multi-Pattern Passenger Prediction:
A Graph Learning Framework**,

*ITS(23)*, No. 9, September 2022, pp. 16148-16160.

IEEE DOI
**2209**

Autoregressive processes, Predictive models, Task analysis,
Optimization, Data models, Smart cities.
BibRef

*He, Y.X.[Yu-Xin]*,
*Li, L.S.[Li-Shuai]*,
*Zhu, X.T.[Xin-Ting]*,
*Tsui, K.L.[Kwok Leung]*,

**Multi-Graph Convolutional-Recurrent Neural Network (MGC-RNN) for
Short-Term Forecasting of Transit Passenger Flow**,

*ITS(23)*, No. 10, October 2022, pp. 18155-18174.

IEEE DOI
**2210**

Forecasting, Correlation, Spatiotemporal phenomena,
Predictive models, Transportation, Time series analysis, Rails,
multi-graph-convolution
BibRef

*Wang, K.P.[Kai-Peng]*,
*Wang, P.[Pu]*,
*Huang, Z.[Zhiren]*,
*Ling, X.[Ximan]*,
*Zhang, F.[Fan]*,
*Chen, A.[Anthony]*,

**A Two-Step Model for Predicting Travel Demand in Expanding Subways**,

*ITS(23)*, No. 10, October 2022, pp. 19534-19543.

IEEE DOI
**2210**

Public transportation, Predictive models, Data models, Urban areas,
Statistics, Sociology, Rails, Subway, travel demand prediction,
line extension
BibRef

*Fu, X.[Xin]*,
*Zhao, X.X.[Xiao-Xuan]*,
*Li, C.C.[Ceng-Ceng]*,
*Cui, M.Y.[Meng-Yan]*,
*Wang, J.W.[Jian-Wei]*,
*Qiang, Y.J.[Yong-Jie]*,

**Exploration of the spatiotemporal heterogeneity of metro ridership
prompted by built environment: A multi-source fusion perspective**,

*IET-ITS(16)*, No. 11, 2022, pp. 1455-1470.

DOI Link
**2210**

BibRef

*Xu, H.[Haihui]*,
*Zou, T.[Tao]*,
*Liu, M.Z.[Ming-Zhe]*,
*Qiao, Y.[Yanan]*,
*Wang, J.J.[Jing-Jing]*,
*Li, X.C.[Xu-Cheng]*,

**Adaptive Spatiotemporal Dependence Learning for Multi-Mode
Transportation Demand Prediction**,

*ITS(23)*, No. 10, October 2022, pp. 18632-18642.

IEEE DOI
**2210**

Feature extraction, Public transportation, Time series analysis,
Correlation, Convolution, Autoregressive processes, Semantics,
deep learning
BibRef

*Zhao, J.J.[Juan-Juan]*,
*Zhang, L.T.[Liu-Tao]*,
*Ye, K.J.[Ke-Jiang]*,
*Ye, J.X.[Jie-Xia]*,
*Zhang, J.[Jun]*,
*Zhang, F.[Fan]*,
*Xu, C.Z.[Cheng-Zhong]*,

**GLTC: A Metro Passenger Identification Method Across AFC Data and
Sparse WiFi Data**,

*ITS(23)*, No. 10, October 2022, pp. 18337-18351.

IEEE DOI
**2210**

Trajectory, Wireless fidelity, Soft sensors, Roads,
Space exploration, Spatiotemporal phenomena, passenger identification
BibRef

*Xie, Q.W.[Qi-Wei]*,
*Wu, X.[Xiao]*,
*Dai, Q.Z.[Qian-Zhi]*,
*Zheng, X.L.[Xiao-Long]*,
*Wang, F.Y.[Fei-Yue]*,

**An Integrated Data Envelopment Analysis and Non-Cooperative Game
Approach for Public Transportation Incentive Subsidy Allocation**,

*ITS(23)*, No. 11, November 2022, pp. 21515-21530.

IEEE DOI
**2212**

Resource management, Costs, Government, Games, Industries,
Behavioral sciences, Data envelopment analysis,
Nash non-cooperative game
BibRef

*Wei, L.[Li]*,
*Qiu, X.[Xiao]*,
*Pu, H.[Hao]*,
*Schonfeld, P.[Paul]*,
*Zhen, S.J.[Shu-Jun]*,
*Zhou, Y.H.[Yu-Hui]*,
*Xu, Z.J.[Zhan-Jun]*,

**Concurrent Optimization of Subway Vertical Alignments and Station
Elevations With Improved Particle Swarm Optimization Algorithm**,

*ITS(23)*, No. 12, December 2022, pp. 24929-24940.

IEEE DOI
**2212**

Optimization, Public transportation, Costs, Energy consumption,
Rail transportation, Linear programming, Rails, subway design
BibRef

*Sutopo, R.[Ricky]*,
*Lim, J.M.Y.[Joanne Mun-Yee]*,
*Baskaran, V.M.[Vishnu Monn]*,

**Efficient Long-Term Dependencies Learning for Passenger Flow
Prediction With Selective Feedback Mechanism**,

*ITS(23)*, No. 12, December 2022, pp. 24020-24030.

IEEE DOI
**2212**

Predictive models, Forecasting, Transformers,
Public transportation, Data models, Deep learning,
transformer
BibRef

*He, D.[Dan]*,
*Zhou, T.[Thomas]*,
*Zhou, X.F.[Xiao-Fang]*,
*Kim, J.[Jiwon]*,

**An Efficient Algorithm for Maximum Trajectory Coverage Query With
Approximation Guarantee**,

*ITS(23)*, No. 12, December 2022, pp. 24031-24043.

IEEE DOI
**2212**

Find k routes in a public transport system that can serve the maximum
number of users with given journey trajectories.
Trajectory, Greedy algorithms, Spatial databases, Urban areas,
Approximation algorithms, STEM, Optimization, Spatial database,
location-based applications
BibRef

*Chen, Y.Y.[Yan-Yan]*,
*Li, T.[Tongfei]*,
*Sun, Y.[Yan]*,
*Wu, J.J.[Jian-Jun]*,
*Guo, X.[Xin]*,
*Liu, D.[Di]*,

**Dynamic data-driven computation method for the number of waiting
passengers and waiting time in the urban rail transit network**,

*IET-ITS(17)*, No. 1, 2023, pp. 165-179.

DOI Link
**2301**

BibRef

*Xiong, Y.J.[Ya-Jun]*,
*Tang, H.[Hui]*,
*Xu, T.[Tao]*,

**High-Speed Railway Access Pattern and Spatial Overlap Characteristics
of the Yellow River Basin Urban Agglomeration**,

*IJGI(12)*, No. 1, 2023, pp. xx-yy.

DOI Link
**2301**

BibRef

*Wei, L.X.[Ling-Xiang]*,
*Guo, D.[Dongjun]*,
*Chen, Z.L.[Zhi-Long]*,
*Yang, J.C.[Jin-Cheng]*,
*Feng, T.L.[Tian-Liu]*,

**Forecasting Short-Term Passenger Flow of Subway Stations Based on the
Temporal Pattern Attention Mechanism and the Long Short-Term Memory
Network**,

*IJGI(12)*, No. 1, 2023, pp. xx-yy.

DOI Link
**2301**

BibRef

*Pei, J.M.[Jia-Ming]*,
*Zhong, K.Y.[Kai-Yang]*,
*Li, J.H.[Jin-Hai]*,
*Yu, Z.[Zhi]*,

**PAC: Partial Area Clustering for Re-Adjusting the Layout of Traffic
Stations in City's Public Transport**,

*ITS(24)*, No. 1, January 2023, pp. 1251-1260.

IEEE DOI
**2301**

Layout, Public transportation, Rails,
Picture archiving and communication systems, Urban areas,
station layout and optimization
BibRef

*Liu, L.B.[Ling-Bo]*,
*Zhu, Y.Y.[Yu-Ying]*,
*Li, G.B.[Guan-Bin]*,
*Wu, Z.[Ziyi]*,
*Bai, L.[Lei]*,
*Lin, L.[Liang]*,

**Online Metro Origin-Destination Prediction via Heterogeneous
Information Aggregation**,

*PAMI(45)*, No. 3, March 2023, pp. 3574-3589.

IEEE DOI
**2302**

Time series analysis, Sparse matrices, Predictive models,
Task analysis, Transformers, Public transportation, Forecasting,
origin-destination ridership
BibRef

*Wang, X.[Xin]*,
*Zhu, C.F.[Chang-Feng]*,
*Jiang, J.H.[Jia-Hao]*,

**A deep learning and ensemble learning based architecture for metro
passenger flow forecast**,

*IET-ITS(17)*, No. 3, 2023, pp. 483-498.

DOI Link
**2303**

BibRef

*Liu, B.[Ben]*,
*Xu, Y.F.[Yun-Fei]*,
*Guo, S.[Sizhen]*,
*Yu, M.M.[Ming-Ming]*,
*Lin, Z.[Ziyue]*,
*Yang, H.[Hong]*,

**Examining the Nonlinear Impacts of Origin-Destination Built
Environment on Metro Ridership at Station-to-Station Level**,

*IJGI(12)*, No. 2, 2023, pp. xx-yy.

DOI Link
**2303**

BibRef

*Lai, Y.W.[Yuan-Wen]*,
*Wang, Y.[Yang]*,
*Xu, X.Y.[Xin-Ying]*,
*Easa, S.M.[Said M.]*,
*Zhou, X.W.[Xiao-Wei]*,

**Hybrid Models of Subway Passenger Flow Prediction Based on
Convolutional Neural Network**,

*IET-ITS(17)*, No. 4, 2023, pp. 716-729.

DOI Link
**2304**

BibRef

*Lai, Y.W.[Yuan-Wen]*,
*Wang, Y.[Yang]*,

**Short-term passenger flow prediction for rail transit based on
improved particle swarm optimization algorithm**,

*IET-ITS(17)*, No. 4, 2023, pp. 825-834.

DOI Link
**2304**

neural nets, particle swarm optimisation, prediction theory, rail transportation
BibRef

*Zhu, L.[Li]*,
*Shen, C.Z.[Chun-Zi]*,
*Wang, X.[Xi]*,
*Liang, H.[Hao]*,
*Wang, H.W.[Hong-Wei]*,
*Tang, T.[Tao]*,

**A Learning Based Intelligent Train Regulation Method With Dynamic
Prediction for the Metro Passenger Flow**,

*ITS(24)*, No. 4, April 2023, pp. 3935-3948.

IEEE DOI
**2304**

Regulation, Real-time systems, Predictive models,
Heuristic algorithms, Generative adversarial networks, Rails,
deep Q-learning
BibRef

*Li, P.[Pei]*,
*Wang, S.[Sheng]*,
*Zhao, H.T.[Han-Tao]*,
*Yu, J.[Jia]*,
*Hu, L.Y.[Li-Yang]*,
*Yin, H.D.[Hao-Dong]*,
*Liu, Z.Y.[Zhi-Yuan]*,

**IG-Net: An Interaction Graph Network Model for Metro Passenger Flow
Forecasting**,

*ITS(24)*, No. 4, April 2023, pp. 4147-4157.

IEEE DOI
**2304**

Forecasting, Predictive models, Multitasking, Data models,
Task analysis, Deep learning, Correlation, Metro stations,
inter-station interaction
BibRef

*Mei, Z.Y.[Zhen-Yu]*,
*Yu, W.T.[Wan-Ting]*,
*Tang, W.[Wei]*,
*Yu, J.H.[Jia-Hao]*,
*Cai, Z.Y.[Zheng-Yi]*,

**Attention mechanism-based model for short-term bus traffic passenger
volume prediction**,

*IET-ITS(17)*, No. 4, 2023, pp. 767-779.

DOI Link
**2304**

attention mechanism, bus stop information encoding,
intelligent transportation, multi-headed mechanism,
short-term bus traffic passenger flow prediction
BibRef

*Xu, Y.H.[Yu-Hang]*,
*Lyu, Y.[Yan]*,
*Xiong, G.[Guangwei]*,
*Wang, S.Y.[Shu-Yu]*,
*Wu, W.W.[Wei-Wei]*,
*Cui, H.[Helei]*,
*Luo, J.Z.[Jun-Zhou]*,

**Adaptive Feature Fusion Networks for Origin-Destination Passenger
Flow Prediction in Metro Systems**,

*ITS(24)*, No. 5, May 2023, pp. 5296-5312.

IEEE DOI
**2305**

Estimation, Correlation, Predictive models, Task analysis,
Multitasking, Roads, Knowledge based systems, Metro system, multi-task
BibRef

*Tang, T.L.[Tian-Li]*,
*Liu, R.H.[Rong-Hui]*,
*Choudhury, C.[Charisma]*,
*Fonzone, A.[Achille]*,
*Wang, Y.Y.[Yuan-Yuan]*,

**Predicting Hourly Boarding Demand of Bus Passengers Using Imbalanced
Records From Smart-Cards: A Deep Learning Approach**,

*ITS(24)*, No. 5, May 2023, pp. 5105-5119.

IEEE DOI
**2305**

Predictive models, Machine learning, Data models, Training,
Generative adversarial networks, Ensemble learning, deep neural network
BibRef

*Yan, J.M.[Jin-Ming]*,
*Wan, Q.Y.[Qiu-Yu]*,
*Feng, J.Y.[Jing-Yi]*,
*Wang, J.J.[Jian-Jun]*,
*Hu, Y.[Yiwen]*,
*Yan, X.X.[Xue-Xin]*,

**The Non-Linear Influence of Built Environment on the School Commuting
Metro Ridership: The Case in Wuhan, China**,

*IJGI(12)*, No. 5, 2023, pp. xx-yy.

DOI Link
**2306**

BibRef

*Zhang, P.F.[Peng-Fei]*,
*Koutsopoulos, H.N.[Haris N.]*,
*Ma, Z.[Zhenliang]*,

**DeepTrip: A Deep Learning Model for the Individual Next Trip
Prediction With Arbitrary Prediction Times**,

*ITS(24)*, No. 6, June 2023, pp. 5842-5855.

IEEE DOI
**2306**

Predictive models, Numerical models, Data models, Deep learning,
Trajectory, Prediction algorithms, Global Positioning System,
metro systems
BibRef

*Wang, J.[Jianpo]*,
*Zhao, M.[Meng]*,
*Ai, T.[Teng]*,
*Wang, Q.[Qushun]*,
*Liu, Y.F.[Yu-Fan]*,

**Revealing the Influence of the Fine-Scale Built Environment on Urban
Rail Ridership with a Semiparametric GWPR Model**,

*IJGI(12)*, No. 6, 2023, pp. xx-yy.

DOI Link
**2307**

BibRef

*Wang, H.F.[Hong-Fei]*,
*Guan, H.Z.[Hong-Zhi]*,
*Qin, H.[Huanmei]*,
*Zhao, P.F.[Peng-Fei]*,

**Towards a more flexible demand responsive transit service with
compensation mechanism considering boundedly rational passengers**,

*IET-ITS(17)*, No. 6, 2023, pp. 1229-1246.

DOI Link
**2307**

bounded rationality, compensation mechanism,
demand responsive transit, Pareto front
BibRef

*Liu, J.[Jian]*,
*Meng, B.[Bin]*,
*Xu, J.[Jun]*,
*Li, R.Q.[Ruo-Qian]*,

**Exploring Public Transportation Supply-Demand Structure of Beijing
from the Perspective of Spatial Interaction Network**,

*IJGI(12)*, No. 6, 2023, pp. xx-yy.

DOI Link
**2307**

BibRef

*Yang, H.[Huajie]*,

**Assessing the Effects of New Light Rail Transit on Regional Traffic
Congestion and Transit Ridership: A Synthetic Control Approach**,

*ITS(24)*, No. 7, July 2023, pp. 7613-7620.

IEEE DOI
**2307**

Light rail systems, Rails, Urban areas, Investment, Vehicles,
Matrix converters, Extrapolation, Light rail transit,
new start
BibRef

*Chang, W.B.[Wen-Bo]*,
*Huang, B.Q.[Bao-Qi]*,
*Jia, B.[Bing]*,
*Li, W.[Wuyungerile]*,
*Xu, G.[Gang]*,

**Online Public Transit Ridership Monitoring Through Passive WiFi
Sensing**,

*ITS(24)*, No. 7, July 2023, pp. 7025-7034.

IEEE DOI
**2307**

Wireless fidelity, Sensors, Estimation, Monitoring, Mobile handsets,
Probes, Global Positioning System, Public transit, attention mechanism
BibRef

*Zhang, Y.[Yan]*,
*Sun, K.[Keyang]*,
*Wen, D.[Di]*,
*Chen, D.J.[Ding-Jun]*,
*Lv, H.X.[Hong-Xia]*,
*Zhang, Q.P.[Qing-Peng]*,

**Deep Learning for Metro Short-Term Origin-Destination Passenger Flow
Forecasting Considering Section Capacity Utilization Ratio**,

*ITS(24)*, No. 8, August 2023, pp. 7943-7960.

IEEE DOI
**2308**

Spatiotemporal phenomena, Convolutional neural networks,
Real-time systems, Forecasting, Feature extraction,
temporal convolutional neural network
BibRef

*Li, Y.C.[Yi-Cong]*,
*Zhang, T.[Tong]*,
*Lv, X.F.[Xiao-Fei]*,
*Lu, Y.X.[Ying-Xi]*,
*Wang, W.[Wangshu]*,

**Profiling Public Transit Passenger Mobility Using Adversarial
Learning**,

*IJGI(12)*, No. 8, 2023, pp. 338.

DOI Link
**2309**

BibRef

*Zhang, X.[Xuanrong]*,
*Wang, C.[Cheng]*,
*Chen, J.W.[Jian-Wei]*,
*Chen, D.[Ding]*,

**A deep neural network model with GCN and 3D convolutional network for
short-term metro passenger flow forecasting**,

*IET-ITS(17)*, No. 8, 2023, pp. 1599-1607.

DOI Link
**2309**

artificial intelligence, convolution,
convolutional neural nets, neural nets, rail traffic
BibRef

*Zhong, J.M.[Jia-Ming]*,
*He, Z.C.[Zhao-Cheng]*,
*Wang, J.W.[Jia-Wei]*,
*Xie, J.M.[Jie-Min]*,

**A Hierarchical Framework for Passenger Inflow Control in Metro System
With Reinforcement Learning**,

*ITS(24)*, No. 10, October 2023, pp. 10895-10911.

IEEE DOI
**2310**

BibRef

*Yu, Q.[Qian]*,
*Zhang, Y.D.[Ya-Dong]*,
*Guo, J.[Jin]*,
*Ma, W.G.[Wen-Gang]*,
*Liu, R.Q.[Rui-Qi]*,
*Lai, P.[Pei]*,

**A multiple spatio-temporal features fusion approach for short-term
passenger flow forecasting in urban rail transit**,

*IET-ITS(17)*, No. 9, 2023, pp. 1729-1741.

DOI Link
**2310**

adjacency graph, functional similarity graph,
short-term passenger flow forecasting, spatial dynamic, URT
BibRef

*Wei, X.[Xiulan]*,
*Zhang, Y.[Yong]*,
*Zhang, X.Y.[Xin-Yu]*,
*Ge, Q.[Qibin]*,
*Yin, B.C.[Bao-Cai]*,

**Real-time passenger flow anomaly detection in metro system**,

*IET-ITS(17)*, No. 10, 2023, pp. 2020-2033.

DOI Link
**2310**

intelligent transportation systems, management and control,
real-time systems, time series, traffic modelling
BibRef

*Luo, Y.[Yong]*,
*Zheng, J.Y.[Jian-Ying]*,
*Wang, X.[Xiang]*,
*Tao, Y.[Yanyun]*,
*Jiang, X.X.[Xing-Xing]*,

**A Neural Network Based on Spatial Decoupling and Patterns Diverging
for Urban Rail Transit Ridership Prediction**,

*ITS(24)*, No. 12, December 2023, pp. 15248-15258.

IEEE DOI
**2312**

BibRef

*Li, X.S.[Xiao-Song]*,
*Wu, Y.X.[Yan-Xia]*,
*Fu, Y.[Yan]*,
*Zhang, L.[Lidan]*,
*Hong, R.[Ruize]*,

**A lightweight bus passenger detection model based on YOLOv5**,

*IET-IPR(17)*, No. 14, 2023, pp. 3927-3937.

DOI Link
**2312**

convolutional neural networks, image recognition, object detection
BibRef

*Li, X.[Xinyi]*,
*Wang, C.[Cheng]*,

**Short-term origin-destination demand forecasting in bus rapid transit
based on dual attentive multi-scale convolutional network**,

*IET-ITS(18)*, No. 1, 2024, pp. 29-46.

DOI Link
**2401**

demand forecasting, intelligent transportation systems, neural nets
BibRef

*Jang, H.[Hanme]*,
*Yu, K.[Kiyun]*,
*Kim, J.Y.[Ji-Young]*,

**Generating Spatial Knowledge Graphs with 2D Indoor Floorplan Data: A
Case Study on the Jeonju Express Bus Terminal**,

*IJGI(13)*, No. 2, 2024, pp. 52.

DOI Link
**2402**

BibRef

*Xi, Y.F.[Ya-Fei]*,
*Hou, Q.H.[Quan-Hua]*,
*Duan, Y.Q.[Ya-Qiong]*,
*Lei, K.[Kexin]*,
*Wu, Y.[Yan]*,
*Cheng, Q.Y.[Qian-Yu]*,

**Exploring the Spatiotemporal Effects of the Built Environment on the
Nonlinear Impacts of Metro Ridership: Evidence from Xi'an, China**,

*IJGI(13)*, No. 3, 2024, pp. 105.

DOI Link
**2404**

BibRef

*Zhang, Y.[Yang]*,
*Chen, Y.L.[Yan-Ling]*,
*Wang, Z.[Ziliang]*,
*Xin, D.R.[Dong-Rong]*,

**TMFO-AGGRU: A Graph Convolutional Gated Recurrent Network for Metro
Passenger Flow Forecasting**,

*ITS(25)*, No. 3, March 2024, pp. 2893-2907.

IEEE DOI
**2405**

Predictive models, Forecasting, Adaptation models, Correlation,
Data models, Logic gates, Prediction algorithms, T mutation
BibRef

*Zhang, S.[Shuxin]*,
*Zhang, J.[Jinlei]*,
*Yang, L.X.[Li-Xing]*,
*Wang, C.C.[Cheng-Cheng]*,
*Gao, Z.Y.[Zi-You]*,

**COV-STFormer for Short-Term Passenger Flow Prediction During COVID-19
in Urban Rail Transit Systems**,

*ITS(25)*, No. 5, May 2024, pp. 3793-3811.

IEEE DOI
**2405**

COVID-19, Predictive models, Feature extraction,
Public transportation, Convolutional neural networks,
short-term passenger flow prediction
BibRef

*Li, C.[Can]*,
*Liu, W.[Wei]*,

**Multimodal Transport Demand Forecasting via Federated Learning**,

*ITS(25)*, No. 5, May 2024, pp. 4009-4020.

IEEE DOI
**2405**

Demand forecasting, Predictive models, Data models, Federated learning,
Convolution, Hidden Markov models, Correlation, fine-grained graph
BibRef

*Xiao, S.S.[Shi-Shi]*,
*Shi, Q.[Qing]*,
*Shao, L.D.[Ling-Dan]*,
*Du, B.[Bo]*,
*Wang, Y.[Yang]*,
*Shen, Q.[Qiaomu]*,
*Zeng, W.[Wei]*,

**MetroBUX: A Topology-Based Visual Analytics for Bus Operational
Uncertainty EXploration**,

*ITS(25)*, No. 6, June 2024, pp. 5525-5538.

IEEE DOI
**2406**

Uncertainty, Data visualization, Visual analytics, Schedules,
Analytical models, Space exploration, Decision making,
visual analytics
BibRef

*Kong, X.J.[Xiang-Jie]*,
*Shen, Z.[Zhehui]*,
*Wang, K.[Kailai]*,
*Shen, G.J.[Guo-Jiang]*,
*Fu, Y.J.[Yan-Jie]*,

**Exploring Bus Stop Mobility Pattern: A Multi-Pattern Deep Learning
Prediction Framework**,

*ITS(25)*, No. 7, July 2024, pp. 6604-6616.

IEEE DOI
**2407**

Task analysis, Prediction algorithms, Feature extraction,
Convolution, Predictive models, Graph neural networks, deep learning
BibRef

IEEE DOI

Streaming media, Roads, Delays, Detectors, Wireless communication, Optimization, urban traffic, video detection, bus priority, VISSIM simulation BibRef

*Jamalul Shamsudin, N.L.*,
*Abdul Khanan, M.F.*,
*Umar, H.A.*,
*Atan, S.N.*,
*Din, A.H.M.*,

**Integrating Network Concept Into Multi Criteria Analysis for Suggesting
Bus Rapid Transit Routes**,

*GGT19*(309-317).

DOI Link
**1912**

BibRef

*Vergara, K.A.*,
*Sanchez, J.*,
*Bautista, E.L.*,

**Site Selection for New Point to Point (P2P) Bus Endpoints and Routes In
Metro Manila, Philippines**,

*GGT19*(659-666).

DOI Link
**1912**

BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in

Traffic Collisions, Accidents, Analysis, Congestion, Not Image Analysis .

Last update:Jul 18, 2024 at 20:50:34