Milanes, V.,
Villagra, J.,
Godoy, J.,
Simo, J.,
Perez, J.,
Onieva, E.,
An Intelligent V2I-Based Traffic Management System,
ITS(13), No. 1, March 2012, pp. 49-58.
IEEE DOI
1203
BibRef
And:
Erratum:
ITS(14), No. 3, 2013, pp. 1556-1556.
IEEE DOI
1309
Accident prevention; Collision avoidance; Fuzzy control; Traffic control
BibRef
Dong, J.,
Mahmassani, H.S.,
Stochastic Modeling of Traffic Flow Breakdown Phenomenon:
Application to Predicting Travel Time Reliability,
ITS(13), No. 4, December 2012, pp. 1803-1809.
IEEE DOI
1212
BibRef
Chung, Y.,
Recker, W.W.,
A Methodological Approach for Estimating Temporal and Spatial Extent of
Delays Caused by Freeway Accidents,
ITS(13), No. 3, September 2012, pp. 1454-1461.
IEEE DOI
1209
BibRef
Chung, Y.,
Recker, W.W.,
Spatiotemporal Analysis of Traffic Congestion Caused by Rubbernecking
at Freeway Accidents,
ITS(14), No. 3, 2013, pp. 1416-1422.
IEEE DOI
1309
Binary integer programming (BIP)
BibRef
Gerber, M.S.,
Tang, L.,
Automatic Quality Control of Transportation Reports Using Statistical
Language Processing,
ITS(14), No. 4, 2013, pp. 1681-1689.
IEEE DOI
1312
Accidents
BibRef
Chou, C.S.[Chih-Sheng],
Nichols, A.P.,
Deriving a surrogate safety measure for freeway incidents based on
predicted end-of-queue properties,
IET-ITS(9), No. 1, 2015, pp. 22-29.
DOI Link
1503
queueing theory
BibRef
Lei, C.,
Lin, W.,
Miao, L.,
A Stochastic Emergency Vehicle Redeployment Model for an Effective
Response to Traffic Incidents,
ITS(16), No. 2, April 2015, pp. 898-909.
IEEE DOI
1504
Dispatching
BibRef
Fleming, C.H.,
Leveson, N.G.,
Early Concept Development and Safety Analysis of Future
Transportation Systems,
ITS(17), No. 12, December 2016, pp. 3512-3523.
IEEE DOI
1612
Accidents
BibRef
Zhang, Y.Y.[Ying-Ya],
Ye, N.[Ning],
Wang, R.[Ruchuan],
Malekian, R.[Reza],
A Method for Traffic Congestion Clustering Judgment Based on Grey
Relational Analysis,
IJGI(5), No. 5, 2016, pp. 71.
DOI Link
1606
BibRef
Chung, Y.,
Recker, W.W.,
Frailty Models for the Estimation of Spatiotemporally Maximum
Congested Impact Information on Freeway Accidents,
ITS(16), No. 4, August 2015, pp. 2104-2112.
IEEE DOI
1508
Accidents
BibRef
Liu, C.[Chun],
Zhang, S.[Shuhang],
Wu, H.[Hangbin],
Fu, Q.A.[Qi-Ang],
A Dynamic Spatiotemporal Analysis Model for Traffic Incident
Influence Prediction on Urban Road Networks,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link
1712
BibRef
Li, Z.,
Liu, P.,
Xu, C.,
Duan, H.,
Wang, W.,
Reinforcement Learning-Based Variable Speed Limit Control Strategy to
Reduce Traffic Congestion at Freeway Recurrent Bottlenecks,
ITS(18), No. 11, November 2017, pp. 3204-3217.
IEEE DOI
1711
Adaptive control, Computational modeling, Heuristic algorithms,
Optimization, Traffic control, Variable speed limit,
BibRef
Li, Z.,
Liu, P.,
Wang, W.,
Xu, C.,
Development of a Control Strategy of Variable Speed Limits to Reduce
Rear-End Collision Risks Near Freeway Recurrent Bottlenecks,
ITS(15), No. 2, April 2014, pp. 866-877.
IEEE DOI
1404
Computer crashes
BibRef
Li, Y.,
Xu, C.,
Xing, L.,
Wang, W.,
Integrated Cooperative Adaptive Cruise and Variable Speed Limit
Controls for Reducing Rear-End Collision Risks Near Freeway
Bottlenecks Based on Micro-Simulations,
ITS(18), No. 11, November 2017, pp. 3157-3167.
IEEE DOI
1711
Adaptation models, Automobiles, Data models, Manuals, Safety,
Traffic control, Cooperative adaptive cruise control,
BibRef
Al Mallah, R.,
Quintero, A.,
Farooq, B.,
Distributed Classification of Urban Congestion Using VANET,
ITS(18), No. 9, September 2017, pp. 2435-2442.
IEEE DOI
1709
traffic engineering computing,
heterogeneous urban road network,
real-time distributed classification,
Feature extraction, Meteorology,
Monitoring, Trajectory, Event classification,
BibRef
Ahmad, A.[Asif],
Arshad, R.[Rabia],
Mahmud, S.A.[Sahibzada Ali],
Ahmad, G.M.K.[Gul Muhammad Khan
Shortest Processing Time Scheduling to Reduce Traffic Congestion in
Dense Urban Areas,
SMCS(47), No. 5, May 2017, pp. 838-855.
IEEE DOI
1704
Algorithm design and analysis
BibRef
Lopez-Garcia, P.,
Onieva, E.,
Osaba, E.,
Masegosa, A.D.,
Perallos, A.,
A Hybrid Method for Short-Term Traffic Congestion Forecasting Using
Genetic Algorithms and Cross Entropy,
ITS(17), No. 2, February 2016, pp. 557-569.
IEEE DOI
1602
Artificial neural networks
BibRef
van Westrenen, F.,
Ellerbroek, J.,
The Effect of Traffic Complexity on the Development of Near Misses on
the North Sea,
SMCS(47), No. 3, March 2017, pp. 432-440.
IEEE DOI
1703
Accidents
BibRef
Ma, X.,
Ding, C.,
Luan, S.,
Wang, Y.,
Wang, Y.,
Prioritizing Influential Factors for Freeway Incident Clearance Time
Prediction Using the Gradient Boosting Decision Trees Method,
ITS(18), No. 9, September 2017, pp. 2303-2310.
IEEE DOI
1709
decision trees,
road accidents,
BibRef
Wang, Q.[Qi],
Wan, J.[Jia],
Yuan, Y.[Yuan],
Locality constraint distance metric learning for traffic congestion
detection,
PR(75), No. 1, 2018, pp. 272-281.
Elsevier DOI
1712
Distance metric learning
BibRef
Ou, J.[Jishun],
Yang, S.[Shu],
Wu, Y.J.[Yao-Jan],
An, C.C.[Cheng-Chuan],
Xia, J.X.[Jing-Xin],
Systematic clustering method to identify and characterise
spatiotemporal congestion on freeway corridors,
IET-ITS(12), No. 8, October 2018, pp. 826-837.
DOI Link
1809
BibRef
Chen, M.,
Yu, X.,
Liu, Y.,
PCNN: Deep Convolutional Networks for Short-Term Traffic Congestion
Prediction,
ITS(19), No. 11, November 2018, pp. 3550-3559.
IEEE DOI
1812
convolution, feedforward neural nets,
learning (artificial intelligence), road traffic, time series,
convolutional neural network
BibRef
Galatioto, F.[Fabio],
Catalano, M.[Mario],
Shaikh, N.[Nabeel],
McCormick, E.[Ecaterina],
Johnston, R.[Ryan],
Advanced accident prediction models and impacts assessment,
IET-ITS(12), No. 9, November 2018, pp. 1131-1141.
DOI Link
1810
BibRef
Hollenstein, D.[Daria],
Hess, M.[Martin],
Jordan, D.[Denis],
Bleisch, S.[Susanne],
Investigating Roundabout Properties and Bicycle Accident Occurrence
at Swiss Roundabouts: A Logistic Regression Approach,
IJGI(8), No. 2, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Attal, F.,
Boubezoul, A.,
Samé, A.,
Oukhellou, L.,
Espié, S.,
Powered Two-Wheelers Critical Events Detection and Recognition Using
Data-Driven Approaches,
ITS(19), No. 12, December 2018, pp. 4011-4022.
IEEE DOI
1812
Roads, Accidents, Sensors, Safety, Event detection, Angular velocity,
Acceleration, Powered two-wheelers,
data mining approaches
BibRef
Ke, X.,
Shi, L.,
Guo, W.,
Chen, D.,
Multi-Dimensional Traffic Congestion Detection Based on Fusion of
Visual Features and Convolutional Neural Network,
ITS(20), No. 6, June 2019, pp. 2157-2170.
IEEE DOI
1906
Roads, Feature extraction, Videos, Visualization, Cameras,
Surveillance, Traffic congestion detection,
optical flow
BibRef
Yu, Q.[Qingying],
Luo, Y.[Yonglong],
Chen, C.[Chuanming],
Zheng, X.[Xiaoyao],
Road Congestion Detection Based on Trajectory Stay-Place Clustering,
IJGI(8), No. 6, 2019, pp. xx-yy.
DOI Link
1908
BibRef
Zhou, H.C.[Hua-Chun],
Zhou, S.[Sheng],
Scene categorization towards urban tunnel traffic by image quality
assessment,
JVCIR(65), 2019, pp. 102655.
Elsevier DOI
1912
Scene categorization, Tunnel traffic analysis,
Information entropy, Rough clustering, Image quality model
BibRef
Mallah, R.A.[R. Al],
Quintero, A.,
Farooq, B.,
Cooperative Evaluation of the Cause of Urban Traffic Congestion via
Connected Vehicles,
ITS(21), No. 1, January 2020, pp. 59-67.
IEEE DOI
2001
Roads, Data mining, Uncertainty, Monitoring, Fuses, Connected vehicles,
Vehicular ad hoc networks, Cooperation, data mining,
connected vehicle
BibRef
Han, Y.,
Ahn, S.,
Variable Speed Release (VSR): Speed Control to Increase Bottleneck
Capacity,
ITS(21), No. 1, January 2020, pp. 298-307.
IEEE DOI
2001
Electric breakdown, Time factors, Merging, Stochastic processes,
Vehicles, Delays, Mathematical model,
variable speed release (VSR)
BibRef
Xu, M.,
Wu, J.,
Wang, H.,
Cao, M.,
Anomaly Detection in Road Networks Using Sliding-Window Tensor
Factorization,
ITS(20), No. 12, December 2019, pp. 4704-4713.
IEEE DOI
2001
Roads, Anomaly detection, Trajectory,
Anomaly detection, tensor factorization, sliding window, trajectory data
BibRef
Panagopoulos, G.,
Pavlidis, I.,
Forecasting Markers of Habitual Driving Behaviors Associated With
Crash Risk,
ITS(21), No. 2, February 2020, pp. 841-851.
IEEE DOI
2002
Vehicles, Stress, Monitoring, Bayes methods, Accidents, Boosting,
Physiology, Affective computing, distracted driving,
thermal imaging
BibRef
Gu, Y.[Yanyan],
Wang, Y.D.[Yan-Dong],
Dong, S.[Shihai],
Public Traffic Congestion Estimation Using an Artificial Neural
Network,
IJGI(9), No. 3, 2020, pp. xx-yy.
DOI Link
2004
BibRef
Gillis, D.[Dominique],
Gautama, S.[Sidharta],
Van Gheluwe, C.[Casper],
Semanjski, I.[Ivana],
Lopez, A.J.[Angel J.],
Lauwers, D.[Dirk],
Measuring Delays for Bicycles at Signalized Intersections Using
Smartphone GPS Tracking Data,
IJGI(9), No. 3, 2020, pp. xx-yy.
DOI Link
2004
BibRef
Tang, J.Q.[Jun-Qing],
Wan, L.[Li],
Nochta, T.[Timea],
Schooling, J.[Jennifer],
Yang, T.[Tianren],
Exploring Resilient Observability in Traffic-Monitoring Sensor
Networks: A Study of Spatial-Temporal Vehicle Patterns,
IJGI(9), No. 4, 2020, pp. xx-yy.
DOI Link
2005
BibRef
Liu, Z.Y.[Zhi-Yong],
Li, R.[Ruimin],
Will the vehicle restriction policy maintain a long-term deterrent
effect?,
IET-ITS(14), No. 6, June 2020, pp. 562-569.
DOI Link
2005
BibRef
Luo, J.,
Huang, Y.,
Weng, Y.,
Design of Variable Traffic Light Control Systems for Preventing
Two-Way Grid Network Traffic Jams Using Timed Petri Nets,
ITS(21), No. 7, July 2020, pp. 3117-3127.
IEEE DOI
2007
Accidents, Control systems, Transportation, Petri nets, Safety,
Analytical models, Cell transmission model (CTM), traffic jam,
traffic safety
BibRef
Park, S.,
Seonwoo, Y.,
Kim, J.,
Kim, J.,
Oh, A.,
Denoising Recurrent Neural Networks for Classifying Crash-Related
Events,
ITS(21), No. 7, July 2020, pp. 2906-2917.
IEEE DOI
2007
Data models, Noise reduction, Accidents, Videos,
Recurrent neural networks, Task analysis, driving events
BibRef
Fukuda, S.[Shota],
Uchida, H.[Hideaki],
Fujii, H.[Hideki],
Yamada, T.[Tomonori],
Short-term prediction of traffic flow under incident conditions using
graph convolutional recurrent neural network and traffic simulation,
IET-ITS(14), No. 8, August 2020, pp. 936-946.
DOI Link
2007
BibRef
Yan, F.,
Zhang, S.,
Majumdar, A.,
Tang, T.,
Ma, J.,
A Failure Mapping and Genealogical Research on Metro Operational
Incidents,
ITS(21), No. 8, August 2020, pp. 3551-3560.
IEEE DOI
2008
Accidents, Safety, Resilience, Analytical models,
Rail transportation, Urban areas, Data analysis, Metro operation,
incident analysis
BibRef
Sanayei, R.,
Vafainejad, A.R.,
Karami, J.,
Aghamohammadi, H.,
Traffic Collision Time Series Analysis (a Case Study of Karaj-Qazvin
Freeway),
SMPR19(941-948).
DOI Link
1912
BibRef
Suzuki, T.,
Kataoka, H.,
Aoki, Y.,
Satoh, Y.,
Anticipating Traffic Accidents with Adaptive Loss and Large-Scale
Incident DB,
CVPR18(3521-3529)
IEEE DOI
1812
Accidents, Training, Databases, Adaptation models, Videos,
Autonomous automobiles, Task analysis
BibRef
Alaigba, D.B.,
Soumah, M.,
Banjo, M.O.,
Heterogeneity Index for the Assessment of Relationship Between Land Use
Pattern and Road Traffic Congestion in Apapa-Oworoshoki Express Way,
Lagos Metropolis,
Hannover17(189-196).
DOI Link
1805
BibRef
Anbaroglu, B.,
Heydecker, B.,
Cheng, T.,
How Travel Demand Affects Detection Of Non-recurrent Traffic Congestion
On Urban Road Networks,
ISPRS16(B2: 159-164).
DOI Link
1610
BibRef
Al Halawani, S.[Sawsan],
Mitra, N.J.[Niloy J.],
Congestion-Aware Warehouse Flow Analysis and Optimization,
ISVC15(II: 702-711).
Springer DOI
1601
BibRef
Shad, R.,
Mesgar, A.,
Moghimi, R.,
Extraction of Accidents Prediction Maps Modeling Hot Spots in
Geospatial Information System,
SMPR13(487-492).
HTML Version.
1311
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Traffic Signal Control, Traffic Analysis, Not Image Analysis .