16.7.2.7.11 Traffic Accidents, Analysis, Congestion, Not Image Analysis

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 KhanFawad], Mahmud, S.A.[Sahibzada Ali], Yousaf, F.Z.[Faqir Zarrar],
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

Lu, L.[Lili], Wang, J.[Jian], He, Z.B.[Zheng-Bing], Chan, C.Y.[Ching-Yao],
Real-time estimation of freeway travel time with recurrent congestion based on sparse detector data,
IET-ITS(12), No. 1, February 2018, pp. 2-11.
DOI Link 1801
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

Singh, D., Mohan, C.K.,
Deep Spatio-Temporal Representation for Detection of Road Accidents Using Stacked Autoencoder,
ITS(20), No. 3, March 2019, pp. 879-887.
IEEE DOI 1903
Accidents, Videos, Trajectory, Feature extraction, Target tracking, Urban areas, Accident detection, anomaly detection, deep learning, stacked autoencoder BibRef

Yu, Y.L.[Yuan-Long], Xu, M.X.[Miao-Xing], Gu, J.[Jason],
Vision-based traffic accident detection using sparse spatio-temporal features and weighted extreme learning machine,
IET-ITS(13), No. 9, September 2019, pp. 1417-1428.
DOI Link 1908
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.Y.[Qing-Ying], Luo, Y.L.[Yong-Long], Chen, C.M.[Chuan-Ming], Zheng, X.Y.[Xiao-Yao],
Road Congestion Detection Based on Trajectory Stay-Place Clustering,
IJGI(8), No. 6, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Naboureh, A.[Amin], Feizizadeh, B.[Bakhtiar], Naboureh, A.[Abbas], Bian, J.H.[Jin-Hu], Blaschke, T.[Thomas], Ghorbanzadeh, O.[Omid], Moharrami, M.[Meisam],
Traffic Accident Spatial Simulation Modeling for Planning of Road Emergency Services,
IJGI(8), No. 9, 2019, pp. xx-yy.
DOI Link 1909
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

Ghosh, B., Asif, M.T., Dauwels, J., Fastenrath, U., Guo, H.,
Dynamic Prediction of the Incident Duration Using Adaptive Feature Set,
ITS(20), No. 11, November 2019, pp. 4019-4031.
IEEE DOI 1911
Predictive models, Accidents, Adaptation models, Data models, Analytical models, Neural networks, Forecasting, sequential prediction BibRef

Al Mallah, R., 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

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.Y.[Yan-Yan], Wang, Y.D.[Yan-Dong], Dong, S.H.[Shi-Hai],
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

Qi, X.Z.[Xin-Zhou], Sun, T.[Tuo], Ma, W.J.[Wan-Jing], Wang, L.[Ling], Yu, C.H.[Chun-Hui],
Evaluation of a variable speed limit system using a hierarchical framework under a connected vehicles environment: a case study of a field test in Seattle,
IET-ITS(14), No. 9, September 2020, pp. 1125-1131.
DOI Link 2008
BibRef

Orsini, F.[Federico], Gecchele, G.[Gregorio], Gastaldi, M.[Massimiliano], Rossi, R.[Riccardo],
Large-scale road safety evaluation using extreme value theory,
IET-ITS(14), No. 9, September 2020, pp. 1004-1012.
DOI Link 2008
BibRef

Colombaroni, C.[Chiara], Fusco, G.[Gaetano], Isaenko, N.[Natalia],
Coherence analysis of road safe speed and driving behaviour from floating car data,
IET-ITS(14), No. 9, September 2020, pp. 985-992.
DOI Link 2008
BibRef

Han, F.[Fei], Zhang, S.[Su],
Evaluation of Spatial Resilience of Highway Networks in Response to Adverse Weather Conditions,
IJGI(9), No. 8, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Sun, J., Qi, X., Xu, Y., Tian, Y.,
Vehicle Turning Behavior Modeling at Conflicting Areas of Mixed-Flow Intersections Based on Deep Learning,
ITS(21), No. 9, September 2020, pp. 3674-3685.
IEEE DOI 2008
Turning, Feature extraction, Hidden Markov models, Deep learning, Planning, Convolution, Vehicle, turning behavior, mixed-flow intersections BibRef

Rahman, M.T.[Muhammad Tauhidur], Jamal, A.[Arshad], Al-Ahmadi, H.M.[Hassan M.],
Examining Hotspots of Traffic Collisions and their Spatial Relationships with Land Use: A GIS-Based Geographically Weighted Regression Approach for Dammam, Saudi Arabia,
IJGI(9), No. 9, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Hadjidimitriou, N.S., Lippi, M., Dell'Amico, M., Skiera, A.,
Machine Learning for Severity Classification of Accidents Involving Powered Two Wheelers,
ITS(21), No. 10, October 2020, pp. 4308-4317.
IEEE DOI 2010
Accidents, Neural networks, Machine learning, Machine learning algorithms, Support vector machines, emergency call BibRef

Catalano, M.[Mario], Galatioto, F.[Fabio], Shaikh, N.[Nabeel],
Accident-related cost analysis and decision-making support through econometric modelling,
IET-ITS(14), No. 12, December 2020, pp. 1573-1581.
DOI Link 2011
BibRef

Wang, H., Fang, Y.P., Zio, E.,
Risk Assessment of an Electrical Power System Considering the Influence of Traffic Congestion on a Hypothetical Scenario of Electrified Transportation System in New York State,
ITS(22), No. 1, January 2021, pp. 142-155.
IEEE DOI 2012
Load modeling, Computational modeling, Electric vehicle charging, Power system stability, Mathematical model, transportation system BibRef

Papageorgiou, M., Mountakis, K.S., Karafyllis, I., Papamichail, I., Wang, Y.,
Lane-Free Artificial-Fluid Concept for Vehicular Traffic,
PIEEE(109), No. 2, February 2021, pp. 114-121.
IEEE DOI 2101
Road traffic, Traffic congestion, Urban areas, Safety, Pollution, Public infrastructure, Fuels, Economics BibRef

Ghadami, A., Epureanu, B.I.,
Forecasting the Onset of Traffic Congestions on Circular Roads,
ITS(22), No. 2, February 2021, pp. 1196-1205.
IEEE DOI 2102
Bifurcation, Forecasting, Vehicle dynamics, Automobiles, Perturbation methods, Predictive models, Roads, stop-and-go traffic BibRef

Pu, Z., Li, Z., Jiang, Y., Wang, Y.,
Full Bayesian Before-After Analysis of Safety Effects of Variable Speed Limit System,
ITS(22), No. 2, February 2021, pp. 964-976.
IEEE DOI 2102
Accidents, Safety, Computer crashes, Detectors, Traffic control, Road transportation, Variable speed limit, safety effect, speed effect BibRef

Rämä, P.[Pirkko], Innamaa, S.[Satu],
Safety assessment of local cooperative warnings and speed limit information,
IET-ITS(14), No. 13, 15 December 2020, pp. 1769-1777.
DOI Link 2102
BibRef

Babu, C.N.[C. Narendra], Sure, P., Bhuma, C.M.,
Sparse Bayesian Learning Assisted Approaches for Road Network Traffic State Estimation,
ITS(22), No. 3, March 2021, pp. 1733-1741.
IEEE DOI 2103
Roads, State estimation, Sparse matrices, Kernel, Probes, Sensors, Relevance vector machine, sparse Bayesian learning, traffic state estimation BibRef

Parsola, J.[Jyoti], Gangodkar, D.[Durgaprasad], Mittal, A.[Ankush],
Automated system for road extraction and traffic volume estimation for traffic jam detection,
IJCVR(11), No. 2, 2021, pp. 127-150.
DOI Link 2103
BibRef

Li, T.[Tao], Ni, A.[Anning], Zhang, C.Q.[Chun-Qin], Xiao, G.N.[Guang-Nian], Gao, L.J.[Lin-Jie],
Short-term traffic congestion prediction with Conv-BiLSTM considering spatio-temporal features,
IET-ITS(14), No. 14, 27 December 2020, pp. 1978-1986.
DOI Link 2103
BibRef

Tempelmeier, N.[Nicolas], Feuerhake, U.[Udo], Wage, O.[Oskar], Demidova, E.[Elena],
Mining Topological Dependencies of Recurrent Congestion in Road Networks,
IJGI(10), No. 4, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Wang, C.[Ce], Li, S.[Shuo], Shan, J.[Jie],
Non-Stationary Modeling of Microlevel Road-Curve Crash Frequency with Geographically Weighted Regression,
IJGI(10), No. 5, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Gao, H.[Hong], Yan, Z.J.[Zhen-Jun], Hu, X.[Xu], Yu, Z.Y.[Zhao-Yuan], Luo, W.[Wen], Yuan, L.W.[Lin-Wang], Zhang, J.[Jiyi],
A Method for Exploring and Analyzing Spatiotemporal Patterns of Traffic Congestion in Expressway Networks Based on Origin-Destination Data,
IJGI(10), No. 5, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Peng, L.Q.[Li-Qun], Wang, Y.[Yiting], Zhang, F.[Fan], Zhang, J.S.[Ji-Sheng], Li, Z.X.[Zhi-Xiong],
Evaluation of emergency driving behaviour and vehicle collision risk in connected vehicle environment: A deep learning approach,
IET-ITS(15), No. 4, 2021, pp. 584-594.
DOI Link 2106
BibRef

Li, H.T.[Hai-Tao], Bai, Q.[Qiaowen], Zhao, Y.H.[Yong-Hua], Qu, Z.W.[Zhao-Wei], Xin, W.[Wang],
TSDCN: Traffic safety state deep clustering network for real-time traffic crash-prediction,
IET-ITS(15), No. 1, 2021, pp. 132-146.
DOI Link 2106
BibRef

Hale, D.[David], Chrysikopoulos, G.[Georgios], Kondyli, A.[Alexandra], Ghiasi, A.[Amir],
Evaluation of data-driven performance measures for comparing and ranking traffic bottlenecks,
IET-ITS(15), No. 4, 2021, pp. 504-513.
DOI Link 2106
BibRef

Hassija, V.[Vikas], Gupta, V.[Vatsal], Garg, S.[Sahil], Chamola, V.[Vinay],
Traffic Jam Probability Estimation Based on Blockchain and Deep Neural Networks,
ITS(22), No. 7, July 2021, pp. 3919-3928.
IEEE DOI 2107
Crowdsourcing, Blockchain, Estimation, Predictive models, Neural networks, Roads, Deep learning, blockchain BibRef

Ashraf, J.[Javed], Bakhshi, A.D.[Asim D.], Moustafa, N.[Nour], Khurshid, H.[Hasnat], Javed, A.[Abdullah], Beheshti, A.[Amin],
Novel Deep Learning-Enabled LSTM Autoencoder Architecture for Discovering Anomalous Events From Intelligent Transportation Systems,
ITS(22), No. 7, July 2021, pp. 4507-4518.
IEEE DOI 2107
Computer crime, Training, Autonomous vehicles, Intrusion detection, autoencoder BibRef

Li, Q.P.[Qiu-Ping], Luo, H.W.[Hao-Wen], Luan, X.C.[Xue-Chen],
Multistage Impacts of the Heavy Rain Process on the Travel Speeds of Urban Roads,
IJGI(10), No. 8, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Gatto, R.C.[Rubens Cruz], Forster, C.H.Q.[Carlos Henrique Quartucci],
Audio-Based Machine Learning Model for Traffic Congestion Detection,
ITS(22), No. 11, November 2021, pp. 7200-7207.
IEEE DOI 2112
Roads, Urban areas, Machine learning, Monitoring, Training, Global Positioning System, Mel frequency cepstral coefficient, audio signal processing BibRef

Khattak, Z.H.[Zulqarnain H.], Fontaine, M.D.[Michael D.], Smith, B.L.[Brian L.],
Exploratory Investigation of Disengagements and Crashes in Autonomous Vehicles Under Mixed Traffic: An Endogenous Switching Regime Framework,
ITS(22), No. 12, December 2021, pp. 7485-7495.
IEEE DOI 2112
Vehicle crash testing, Computer crashes, Vehicles, Safety, Roads, Testing, Google, Autonomous vehicles, disengagements, software and sensor failure BibRef

Zhou, J.Z.[Jia-Zhen], Jin, L.[Li], Wang, X.[Xiao], Sun, D.[Dengfeng],
Resilient UAV Traffic Congestion Control Using Fluid Queuing Models,
ITS(22), No. 12, December 2021, pp. 7561-7572.
IEEE DOI 2112
Meteorology, Uncertainty, Atmospheric modeling, Stability analysis, Markov processes, Mathematical model, Numerical stability, piecewise-deterministic Markov process BibRef

Deng, Z.P.[Zhen-Ping], Huang, D.R.[Da-Rong], Liu, J.Y.[Jin-Yu], Mi, B.[Bo], Liu, Y.[Yang],
An Assessment Method for Traffic State Vulnerability Based on a Cloud Model for Urban Road Network Traffic Systems,
ITS(22), No. 11, November 2021, pp. 7155-7168.
IEEE DOI 2112
Roads, Indexes, Complex networks, Delays, Reliability, Analytical models, Uncertainty, Complex network, state vulnerability BibRef

Wang, X.D.[Xu-Dong], Sun, L.J.[Li-Jun],
Diagnosing Spatiotemporal Traffic Anomalies With Low-Rank Tensor Autoregression,
ITS(22), No. 12, December 2021, pp. 7904-7913.
IEEE DOI 2112
Spatiotemporal phenomena, Tensors, Data models, Time series analysis, Anomaly detection, Transportation, tensor learning BibRef

Chen, X.Y.[Xin-Yu], Lei, M.Y.[Meng-Ying], Saunier, N.[Nicolas], Sun, L.J.[Li-Jun],
Low-Rank Autoregressive Tensor Completion for Spatiotemporal Traffic Data Imputation,
ITS(23), No. 8, August 2022, pp. 12301-12310.
IEEE DOI 2208
Tensors, Time series analysis, Spatiotemporal phenomena, Data models, Minimization, Market research, Optimization, autoregressive time series model BibRef

Hu, C.C.[Chun-Chun], Chen, S.[Si],
Massively Parallel Discovery of Loosely Moving Congestion Patterns from Trajectory Data,
IJGI(10), No. 11, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Qu, X.Y.[Xin-Yu], Zhu, X.Y.[Xin-Yan], Xiao, X.W.[Xiong-Wu], Wu, H.Y.[Hua-Yi], Guo, B.X.[Bing-Xuan], Li, D.R.[De-Ren],
Exploring the Influences of Point-of-Interest on Traffic Crashes during Weekdays and Weekends via Multi-Scale Geographically Weighted Regression,
IJGI(10), No. 11, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Luan, S.[Sen], Ma, X.L.[Xiao-Lei], Li, M.[Meng], Su, Y.L.[Yue-Long], Dong, Z.N.[Zhen-Ning],
Detecting and interpreting non-recurrent congestion from traffic and social media data,
IET-ITS(15), No. 12, 2021, pp. 1461-1477.
DOI Link 2112
BibRef

Yue, W.W.[Wen-Wei], Li, C.[Changle], Wang, S.[Shangbo], Xu, Z.G.[Zhi-Gang], Mao, G.Q.[Guo-Qiang],
Towards Enhanced Recovery and System Stability: Analytical Solutions for Dynamic Incident Effects in Road Networks,
ITS(23), No. 1, January 2022, pp. 483-498.
IEEE DOI 2201
Roads, Stability analysis, Numerical stability, Delays, Real-time systems, Switches, Mathematical model, system stability BibRef

Li, S.[Shen], Cheng, Y.[Yang], Jin, P.[Peter], Ding, F.[Fan], Li, Q.[Qing], Ran, B.[Bin],
A Feature-Based Approach to Large-Scale Freeway Congestion Detection Using Full Cellular Activity Data,
ITS(23), No. 2, February 2022, pp. 1323-1331.
IEEE DOI 2202
Poles and towers, Traffic control, Roads, Probes, Feature extraction, Calibration, Real-time systems, Cellular probe, freeway congestion detection BibRef

Zheng, Z.W.[Zeng-Wei], Zhou, M.X.[Ming-Xuan], Chen, Y.[Yuanyi], Huo, M.M.[Mei-Mei], Sun, L.[Lin], Zhao, S.[Sha], Chen, D.[Dan],
A Fused Method of Machine Learning and Dynamic Time Warping for Road Anomalies Detection,
ITS(23), No. 2, February 2022, pp. 827-839.
IEEE DOI 2202
Roads, Acceleration, Feature extraction, Data models, Machine learning, Vehicle dynamics, Data mining, machine learning BibRef

Lyu, N.C.[Neng-Chao], Wen, J.Q.[Jia-Qiang], Duan, Z.C.[Zhi-Cheng], Wu, C.Z.[Chao-Zhong],
Vehicle Trajectory Prediction and Cut-In Collision Warning Model in a Connected Vehicle Environment,
ITS(23), No. 2, February 2022, pp. 966-981.
IEEE DOI 2202
Vehicles, Safety, Predictive models, Trajectory, Accidents, Alarm systems, Vehicle dynamics, long-term and short-term memory networks BibRef

Liyanage, Y.W.[Yasitha Warahena], Zois, D.S.[Daphney-Stavroula], Chelmis, C.[Charalampos],
Near Real-Time Freeway Accident Detection,
ITS(23), No. 2, February 2022, pp. 1467-1478.
IEEE DOI 2202
Accidents, Traffic control, Delays, Computational modeling, Sensor phenomena and characterization, Feature extraction, sensor decisions aggregation BibRef

Wang, Y.[Yiwen], He, Z.[Zhi], Hu, J.[Jie],
Traffic Information Mining From Social Media Based on the MC-LSTM-Conv Model,
ITS(23), No. 2, February 2022, pp. 1132-1144.
IEEE DOI 2202
Social network services, Feature extraction, Roads, Data mining, Machine learning, Dictionaries, Monitoring, Sina Weibo, traffic jam BibRef

Yamamoto, S.[Shuhei], Kurashima, T.[Takeshi], Toda, H.[Hiroyuki],
Classifying Near-Miss Traffic Incidents through Video, Sensor, and Object Features,
IEICE(E105-D), No. 2, February 2022, pp. 377-386.
WWW Link. 2202
BibRef

Riaz, W.[Waqar], Chen-Qiang, G.[Gao], Azeem, A.[Abdullah], Saifullah, Bux, J.A.[Jamshaid Allah], Ullah, A.[Asif],
Traffic Anomaly Prediction System Using Predictive Network,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Mesquitela, J.[Joao], Elvas, L.B.[Luis B.], Ferreira, J.C.[Joao C.], Nunes, L.[Luis],
Data Analytics Process over Road Accidents Data: A Case Study of Lisbon City,
IJGI(11), No. 2, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Lin, D.J.[Da-Jie], Chen, M.Y.[Mu-Yen], Chiang, H.S.[Hsiu-Sen], Sharma, P.K.[Pradip Kumar],
Intelligent Traffic Accident Prediction Model for Internet of Vehicles With Deep Learning Approach,
ITS(23), No. 3, March 2022, pp. 2340-2349.
IEEE DOI 2203
Accidents, Predictive models, Support vector machines, Bayes methods, Logistics, Roads, Neural networks, deep learning BibRef

Zhang, J.M.[Jia-Ming], Yang, K.[Kailun], Stiefelhagen, R.[Rainer],
Exploring Event-Driven Dynamic Context for Accident Scene Segmentation,
ITS(23), No. 3, March 2022, pp. 2606-2622.
IEEE DOI 2203
Accidents, Semantics, Image segmentation, Sensors, Motion segmentation, Object segmentation, Task analysis, intelligent vehicles BibRef

Jiang, S.[Shan], Jafari, M.[Mohsen], Kharbeche, M.[Mohamed], Jalayer, M.[Mohammad], Al-Khalifa, K.N.[Khalifa N.],
Safe Route Mapping of Roadways Using Multiple Sourced Data,
ITS(23), No. 4, April 2022, pp. 3169-3179.
IEEE DOI 2204
Accidents, Safety, Data models, Nickel, Vehicles, Computer crashes, Heating systems, Traffic safety, traffic conflict analysis, dynamic risk heat mapping BibRef

Ju, U.[Uijong], Chuang, L.L.[Lewis L.], Wallraven, C.[Christian],
Acoustic Cues Increase Situational Awareness in Accident Situations: A VR Car-Driving Study,
ITS(23), No. 4, April 2022, pp. 3281-3291.
IEEE DOI 2204
Accidents, Automobiles, Visualization, Vehicles, Alarm systems, Training, Roads, Decision-making, virtual reality, auditory warning, situational awareness BibRef

Hazaymeh, K.[Khaled], Almagbile, A.[Ali], Alomari, A.H.[Ahmad H.],
Spatiotemporal Analysis of Traffic Accidents Hotspots Based on Geospatial Techniques,
IJGI(11), No. 4, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Boujemaa, K.S.[Kaoutar Sefrioui], Berrada, I.[Ismail], Fardousse, K.[Khalid], Naggar, O.[Othmane], Bourzeix, F.[François],
Toward Road Safety Recommender Systems: Formal Concepts and Technical Basics,
ITS(23), No. 6, June 2022, pp. 5211-5230.
IEEE DOI 2206
Accidents, Road safety, Predictive models, Task analysis, Safety, Prediction algorithms, Data models, Traffic accident analysis, road safety countermeasures BibRef

Nguyen, T.T.[Tin T.], Calvert, S.C.[Simeon C.], Vu, H.L.[Hai L.], van Lint, H.[Hans],
An Automated Detection Framework for Multiple Highway Bottleneck Activations,
ITS(23), No. 6, June 2022, pp. 5678-5692.
IEEE DOI 2206
Roads, Detectors, Tin, Topology, Time series analysis, Smoothing methods, Network topology, Highway bottleneck, logistic function BibRef

Gao, Y.F.[Yun-Feng], Hu, H.[Hua], Liu, Y.[Yue],
Coordinated Arterial Dilemma Zone Protection Through Dynamic Signal Timing Optimization,
ITS(23), No. 6, June 2022, pp. 5434-5445.
IEEE DOI 2206
Safety, Vehicle dynamics, Accidents, Delays, Optimization methods, Roads, Green products, Arterial street, weighted combination BibRef

Zhu, S.X.[Shi-Xiang], Ding, R.[Ruyi], Zhang, M.[Minghe], van Hentenryck, P.[Pascal], Xie, Y.[Yao],
Spatio-Temporal Point Processes With Attention for Traffic Congestion Event Modeling,
ITS(23), No. 7, July 2022, pp. 7298-7309.
IEEE DOI 2207
Sensors, Road transportation, Law enforcement, Roads, Data models, Predictive models, Emergency services, Traffic congestion, point process BibRef

Karim, M.M.[Muhammad Monjurul], Li, Y.[Yu], Qin, R.[Ruwen], Yin, Z.Z.[Zhao-Zheng],
A Dynamic Spatial-Temporal Attention Network for Early Anticipation of Traffic Accidents,
ITS(23), No. 7, July 2022, pp. 9590-9600.
IEEE DOI 2207
Accidents, Feature extraction, Vehicle dynamics, Training, Logic gates, Autonomous vehicles, Predictive models, human-inspired AI BibRef

Fang, J.[Jianwu], Qiao, J.H.[Jia-Huan], Bai, J.[Jie], Yu, H.K.[Hong-Kai], Xue, J.R.[Jian-Ru],
Traffic Accident Detection via Self-Supervised Consistency Learning in Driving Scenarios,
ITS(23), No. 7, July 2022, pp. 9601-9614.
IEEE DOI 2207
Accidents, Trajectory, Anomaly detection, Roads, Multitasking, Collaboration, Visualization, Traffic accident detection, adversarial learning BibRef

Robinson, P.[Pamela], Sun, L.[Landy], Furey, H.[Heidi], Jenkins, R.[Ryan], Phillips, C.R.M.[Christopher R. M.], Powers, T.M.[Thomas M.], Ritterson, R.S.[Ryan S.], Xie, Y.C.[Yuan-Chang], Casagrande, R.[Rocco], Evans, N.G.[Nicholas G.],
Modelling Ethical Algorithms in Autonomous Vehicles Using Crash Data,
ITS(23), No. 7, July 2022, pp. 7775-7784.
IEEE DOI 2207
Accidents, Automobiles, Ethics, Vehicles, Data models, Injuries, Safety, Autonomous vehicles, ethics, crash data, safety BibRef

El Mallahi, I.[Imad], Dlia, A.[Asmae], Riffi, J.[Jamal], Mahraz, M.A.[Mohamed Adnane], Tairi, H.[Hamid],
Prediction of Traffic Accidents using Random Forest Model,
ISCV22(1-7)
IEEE DOI 2208
Support vector machines, Road accidents, Urban areas, Artificial neural networks, Prediction algorithms, convolutional neural network BibRef

Ghadami, A.[Amin], Doering, C.R.[Charles R.], Drake, J.M.[John M.], Rohani, P.[Pejman], Epureanu, B.I.[Bogdan I.],
Stability and Resilience of Transportation Systems: Is a Traffic Jam About to Occur?,
ITS(23), No. 8, August 2022, pp. 10803-10814.
IEEE DOI 2208
Resilience, Mathematical model, Vehicle dynamics, Roads, Transportation, Numerical models, Numerical stability, complex system BibRef

Santhosh, K.K.[Kelathodi Kumaran], Dogra, D.P.[Debi Prosad], Roy, P.P.[Partha Pratim], Mitra, A.[Adway],
Vehicular Trajectory Classification and Traffic Anomaly Detection in Videos Using a Hybrid CNN-VAE Architecture,
ITS(23), No. 8, August 2022, pp. 11891-11902.
IEEE DOI 2208
Trajectory, Image color analysis, Videos, Anomaly detection, Convolutional neural networks, Feature extraction, Training data, traffic anomaly detection BibRef

Liu, C.S.[Chun-Sheng], Li, Z.J.[Zi-Jian], Chang, F.[Faliang], Li, S.[Shuang], Xie, J.[Jincan],
Temporal Shift and Spatial Attention-Based Two-Stream Network for Traffic Risk Assessment,
ITS(23), No. 8, August 2022, pp. 12518-12530.
IEEE DOI 2208
Videos, Risk management, Feature extraction, Complexity theory, Accidents, Cameras, Vehicles, Traffic risk assessment, spatial and channel attention mechanism BibRef

Zhou, Y.M.[Yao-Ming], Li, S.P.[Si-Ping], Wang, J.W.[Jun-Wei],
Modeling Stochastic Behavior of Road Networks With Disruptions Using Percolation Theory,
ITS(23), No. 8, August 2022, pp. 13230-13241.
IEEE DOI 2208
Roads, Stochastic processes, Measurement, Transportation, Size measurement, Optimization, Analytical models, Connectivity, performance evaluation BibRef

Sun, Y.[Yidan], Jiang, G.Y.[Gui-Yuan], Lam, S.K.[Siew-Kei], He, P.[Peilan],
Learning Traffic Network Embeddings for Predicting Congestion Propagation,
ITS(23), No. 8, August 2022, pp. 11591-11604.
IEEE DOI 2208
Roads, Microscopy, Spatiotemporal phenomena, Predictive models, Vehicle dynamics, Sun, Intelligent transportation systems, propagation model BibRef

Kubin, L.[Luca], Bianconcini, T.[Tommaso], de Andrade, D.C.[Douglas Coimbra], Simoncini, M.[Matteo], Taccari, L.[Leonardo], Sambo, F.[Francesco],
Deep Crash Detection From Vehicular Sensor Data With Multimodal Self-Supervision,
ITS(23), No. 8, August 2022, pp. 12480-12489.
IEEE DOI 2208
Accidents, Time series analysis, Feature extraction, Task analysis, Global Positioning System, Deep learning, Training, time series classification BibRef

Wang, C.[Chong], Xu, Y.[Yang], Zhang, J.[Jian], Ran, B.[Bin],
Integrated Traffic Control for Freeway Recurrent Bottleneck Based on Deep Reinforcement Learning,
ITS(23), No. 9, September 2022, pp. 15522-15535.
IEEE DOI 2209
Traffic control, Roads, Reinforcement learning, Transceivers, Simulation, Terminology, Synchronization, freeway traffic management BibRef

Shen, G.J.[Guo-Jiang], Han, X.[Xiao], Chin, K.[Kwaisang], Kong, X.J.[Xiang-Jie],
An Attention-Based Digraph Convolution Network Enabled Framework for Congestion Recognition in Three-Dimensional Road Networks,
ITS(23), No. 9, September 2022, pp. 14413-14426.
IEEE DOI 2209
Roads, Data models, Data mining, Convolution, Convolutional neural networks, Spatiotemporal phenomena, intelligent transportation systems BibRef

Cheng, Z.Y.[Ze-Yang], Yuan, J.H.[Jing-Hui], Yu, B.[Bo], Lu, J.[Jian], Zhao, Y.[Yi],
Crash Risks Evaluation of Urban Expressways: A Case Study in Shanghai,
ITS(23), No. 9, September 2022, pp. 15329-15339.
IEEE DOI 2209
Computer crashes, Accidents, Roads, Real-time systems, Predictive models, Safety management, Analytical models, crash risk classification BibRef

Qi, H.S.[Hong-Sheng], Yu, Y.[Yi], Tang, Q.[Qing], Hu, X.B.[Xian-Biao],
Intersection traffic deadlock formation and its probability: A petri net-based modeling approach,
IET-ITS(16), No. 10, 2022, pp. 1342-1363.
DOI Link 2209
BibRef

Luo, X.Y.[Xin-Yu], Zhang, J.[JiaMing], Yang, K.[Kailun], Roitberg, A.[Alina], Peng, K.[Kunyu], Stiefelhagen, R.[Rainer],
Towards Robust Semantic Segmentation of Accident Scenes via Multi-Source Mixed Sampling and Meta-Learning,
WAD22(4428-4438)
IEEE DOI 2210
Image segmentation, Adaptation models, Semantics, Transportation, Benchmark testing, Transformers, Robustness BibRef

Chen, M.Y.[Mu-Yen], Chiang, H.S.[Hsiu-Sen], Huang, W.K.[Wei-Kai],
Efficient Generative Adversarial Networks for Imbalanced Traffic Collision Datasets,
ITS(23), No. 10, October 2022, pp. 19864-19873.
IEEE DOI 2210
Generative adversarial networks, Generators, Training, Data models, Probability distribution, Prediction algorithms, Deep learning, GDAGAN BibRef

Thakare, K.V.[Kamalakar Vijay], Dogra, D.P.[Debi Prosad], Choi, H.[Heeseung], Kim, H.[Haksub], Kim, I.J.[Ig-Jae],
Object Interaction-Based Localization and Description of Road Accident Events Using Deep Learning,
ITS(23), No. 11, November 2022, pp. 20601-20613.
IEEE DOI 2212
Proposals, Feature extraction, Road accidents, Videos, Roads, Location awareness, Task analysis, Anomaly detection, object localization BibRef

Othman, B.[Bassel], de Nunzio, G.[Giovanni], di Domenico, D.[Domenico], Canudas-de-Wit, C.[Carlos],
Analysis of the Impact of Variable Speed Limits on Environmental Sustainability and Traffic Performance in Urban Networks,
ITS(23), No. 11, November 2022, pp. 21766-21776.
IEEE DOI 2212
Biological system modeling, Roads, Green products, Predictive models, Adaptation models, Fuels, Variable speed limits, artificial neural networks BibRef

Hao, W.[Wei], Rong, D.[Donglei], Zhang, Z.[Zhaolei], Wu, Q.Y.[Qi-Yu], Byon, Y.J.[Young-Ji], Yi, K.[Kefu], Tang, J.J.[Jin-Jun], Lyu, N.[Nengchao],
Development of a Safety Prediction Method for Arterial Roads Based on Big-Data Technology and Stacked AutoEncoder-Gated Recurrent Unit,
ITS(23), No. 11, November 2022, pp. 20110-20122.
IEEE DOI 2212
Safety, Data models, Predictive models, Character recognition, Real-time systems, Analytical models, Training, Active safety, Stacked AutoEncoder-Gated Recurrent Unit BibRef

Rempe, D.[Davis], Philion, J.[Jonah], Guibas, L.J.[Leonidas J.], Fidler, S.[Sanja], Litany, O.[Or],
Generating Useful Accident-Prone Driving Scenarios via a Learned Traffic Prior,
CVPR22(17284-17294)
IEEE DOI 2210
Trajectory, Planning, Pattern recognition, Behavioral sciences, Optimization, Autonomous vehicles, Motion and tracking BibRef

Park, K.H.[Kyung Ho], Chung, H.[Hyunhee],
Don't Wait Until the Accident Happens: Few-Shot Classification Framework for Car Accident Inspection in a Real World,
CIAP22(I:560-571).
Springer DOI 2205
BibRef

Almeida, A.[Ana], Brás, S.[Susana], Sargento, S.[Susana], Oliveira, I.[Ilídio],
Using Bus Tracking Data to Detect Potential Hazard Driving Zones,
IbPRIA22(667-679).
Springer DOI 2205
BibRef

Makansi, O.[Osama], Çiçek, Ö.[Özgün], Marrakchi, Y.[Yassine], Brox, T.[Thomas],
On Exposing the Challenging Long Tail in Future Prediction of Traffic Actors,
ICCV21(13127-13137)
IEEE DOI 2203
Manifolds, Codes, Autonomous systems, Computational modeling, Network architecture, Trajectory, Motion and tracking, Vision for robotics and autonomous vehicles BibRef

He, S.T.[Song-Tao], Sadeghi, M.A.[Mohammad Amin], Chawla, S.[Sanjay], Alizadeh, M.[Mohammad], Balakrishnan, H.[Hari], Madden, S.[Samuel],
Inferring high-resolution traffic accident risk maps based on satellite imagery and GPS trajectories,
ICCV21(11957-11965)
IEEE DOI 2203
Satellites, Roads, Computational modeling, Urban areas, Estimation, Predictive models, Data models, Vision applications and systems, Vision for robotics and autonomous vehicles BibRef

Owire, B., Shibwabo Kasamani, B.,
A Smart GPS-based IoT System for Blackspot Notification,
SmartCityApp21(405-410).
DOI Link 2201
Length of the road marked as having high road accidents potential. BibRef

Golze, J., Feuerhake, U., Koetsier, C., Sester, M.,
Impact Analysis of Accidents on the Traffic Flow Based on Massive Floating Car Data,
ISPRS21(B4-2021: 95-102).
DOI Link 2201
BibRef

Rezaei, Z.[Zahra], Ebrahimpour-Komleh, H.[Hossein],
Prediction and Detection of car accidents in video by deep learning,
IPRIA21(1-9)
IEEE DOI 2201
Deep learning, Road accidents, Surveillance, Object detection, Streaming media, Sensor phenomena and characterization, Cameras BibRef

Gitahi, J., Hahn, M., Storz, M., Bernhard, C., Feldges, M., Nordentoft, R.,
Multi-sensor Traffic Data Fusion for Congestion Detection and Tracking,
ISPRS20(B1:173-180).
DOI Link 2012
BibRef

Sevinc, H.K., Karas, I.R., Demiral, E.,
Mobile-web-base Volunteered Geographic Information Application And Geometric Accuracy Analysis for Traffic Accidents,
SmartCityApp20(375-378).
DOI Link 2012
BibRef

Grimaldi, D.,
More Traffic Means More Accidents? the Case of French Nice Highway,
SmartCity20(25-27).
DOI Link 2012
BibRef

Mbarek, A., Jiber, M., Yahyaouy, A., Sabri, A.,
Road traffic mortality in Morocco: Analysis of statistical data,
ISCV20(1-7)
IEEE DOI 2011
data analysis, data mining, injuries, road accidents, road safety, road traffic, statistical analysis, Case fatality rate BibRef

You, T.[Tackgeun], Han, B.H.[Bo-Hyung],
Traffic Accident Benchmark for Causality Recognition,
ECCV20(VII:540-556).
Springer DOI 2011
BibRef

Berrouk, S.[Sara], El Fazziki, A.[Abdelaziz], Sadgal, M.[Mohammed],
Fuzzy-based Approach for Assessing Traffic Congestion in Urban Areas,
ICISP20(112-121).
Springer DOI 2009
BibRef

EslamiNezhad, S.A., Delavar, M.R.,
An Integrated Network-constrained Spatial Analysis for Car Accidents: A Case Study of Tehran City, Iran,
SMPR19(335-342).
DOI Link 1912
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

Ullah, H.[Habib], Ullah, M.[Mohib], Afridi, H.[Hina], Conci, N.[Nicola], de Natale, F.G.B.[Francesco G.B.],
Traffic accident detection through a hydrodynamic lens,
ICIP15(2470-2474)
IEEE DOI 1512
Optical flow; enthalpy model; kernel function; motion field BibRef

Bahnsen, C.[Chris], Moeslund, T.B.[Thomas B.],
Detecting Road Users at Intersections Through Changing Weather Using RGB-Thermal Video,
ISVC15(I: 741-751).
Springer DOI 1601
BibRef
Earlier:
Detecting road user actions in traffic intersections using RGB and thermal video,
AVSS15(1-6)
IEEE DOI 1511
Accidents; Cameras; Detectors; Roads; Safety; Turning; Vehicles 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

Bernas, M.[Marcin],
Objects Detection and Tracking in Highly Congested Traffic Using Compressed Video Sequences,
ICCVG12(296-303).
Springer DOI 1210
BibRef

Sadeky, S.[Samy], Al-Hamadiy, A.[Ayoub], Michaelisy, B.[Bernd], Sayed, U.[Usama],
Real-Time Automatic Traffic Accident Recognition Using HFG,
ICPR10(3348-3351).
IEEE DOI 1008
BibRef

Yu, Z.J.[Zhi-Jing], Liu, B.[Bing], Tian, W.[Wei], Chen, F.[Fei],
Coded Target Based Traffic Accident Vision Swift Reconnaissance System,
CISP09(1-4).
IEEE DOI 0910
BibRef

Adeli-Mosabbeb, E.[Ehsan], Sadeghi, M.[Maryam], Fathy, M.[Mahmood], Bahekmat, M.[Maliheh],
A low-cost strong shadow-based segmentation approach for vehicle tracking in congested traffic scenes,
ICMV07(147-152).
IEEE DOI 0712
BibRef

Adeli-Mosabbeb, E.[Ehsan], Sadeghi, M.[Maryam], Fathy, M.[Mahmoud],
A New Approach for Vehicle Detection in Congested Traffic Scenes Based on Strong Shadow Segmentation,
ISVC07(II: 427-436).
Springer DOI 0711
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 .

Last update:Dec 4, 2022 at 15:58:45