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A two-level hidden Markov model for characterizing data traffic from vehicles

Yuhong Li, Xiaoyu Hao, Han Zheng, Xiang Su, Jukka Riekki, Chao Sun, Hanyu Wei, Hao Wang, Lei Han
2017 Proceedings of the Seventh International Conference on the Internet of Things - IoT '17  
Based on this, we propose a two-level hidden Markov model to describe both large and small temporal characteristics of data traffic from vehicles aggregated on base stations.  ...  We evaluate the proposed model by comparing the original and synthesized data. The results show that the proposed model can well characterize the data traffic from vehicles.  ...  Aggregated data of 24 hours in Cologne TWO-LEVEL HIDDEN MARKOV MODEL Having the data aggregated at each base station, we analyze the characteristics of the data and use a two-level Hidden Markov Model  ... 
doi:10.1145/3131542.3131556 dblp:conf/iot/LiHZSRSWWH17 fatcat:eybmxpimijcyhf3poyk4l5ixmi

Observing on-road vehicle behavior: Issues, approaches, and perspectives

Sayanan Sivaraman, Brendan Morris, Mohan Trivedi
2013 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)  
The ITS community has approached this topic both from vehicle-based and infrastructure-based sensing.  ...  However, the popular methods for behavior characterization differ between the sensing methodologies.  ...  Given the large volume of data available, researchers have looked at characterizing the behavior of vehicles on the road from two distinct vantage points.  ... 
doi:10.1109/itsc.2013.6728485 dblp:conf/itsc/SivaramanMT13 fatcat:vjp5qicfwvhy7epupfvm5vaera

Probabilistic situation recognition for vehicular traffic scenarios

D. Meyer-Delius, C. Plagemann, W. Burgard
2009 2009 IEEE International Conference on Robotics and Automation  
Each situation is characterized by an individual hidden Markov model that describes the corresponding distribution.  ...  Additionally, we show that our models can be used for predicting the position of the tracked vehicles.  ...  We take a model-based approach in which hidden Markov models (HMMs) are used for characterizing and recognizing situations.  ... 
doi:10.1109/robot.2009.5152838 dblp:conf/icra/Meyer-DeliusPB09 fatcat:gijsobq2fjag3ln2guzltori5y

A Driver Behavior Learning Framework for Enhancing Traffic Simulation

Ramona Maria Paven, Mihai Pachia, Dan Pescaru
2014 Carpathian Journal of Electronic and Computer Engineering  
The work presented in this paper proposes a framework for learning driver behavior based on a Hidden Markov Model technique.  ...  However, realistic traffic models are hard to be implemented especially for microscopic traffic simulation.  ...  Instead of that the model is learned from real traffic recorded from investigated area using a Hidden Markov Model technique. The rest of the paper is structured as following.  ... 
doaj:40025a0980174380bb3157faf6910e86 fatcat:3uei4i5gm5f2bojm5445k2bwiq

A Driving Intention Prediction Method Based on Hidden Markov Model for Autonomous Driving [article]

Shiwen Liu, Kan Zheng, Long Zhao, Pingzhi Fan
2019 arXiv   pre-print
In this paper, a driving intention prediction method based on Hidden Markov Model (HMM) is proposed for autonomous vehicles.  ...  HMMs representing different driving intentions are trained and tested with field collected data from a flyover.  ...  In this paper, a driving intention prediction method based on Hidden Markov Model (HMM) is proposed for autonomous vehicles.  ... 
arXiv:1902.09068v1 fatcat:qdcctbdxjrdy3pa4yiwqaj37gi

Intelligent Vehicular Traffic Light Control using Hidden Markov Model

Dominic Asamoah, Samuel Winful, Stephen Opoku
2017 Communications on Applied Electronics  
This research uses Hidden Markov Model (HMM) as a component with unsupervised clustering scheme to determine the traffic situation of a road in a traffic video.  ...  The three HMM models are constructed for each traffic state with each cluster corresponding to a state in the HMM.  ...  Hidden Markov Model (HMM).  ... 
doi:10.5120/cae2017652668 fatcat:uwuq2a2f3zdmldstgex6hewswm

Modeling Pipeline Driving Behaviors: Hidden Markov Model Approach

Xi Zou, David Levinson
2006 Transportation Research Record  
This study used hidden Markov models (HMMs) to model the driving behavior of through-going vehicles on major roads at intersections. Observed vehicle movement data were used to estimate the model.  ...  A single HMM was used to cluster movements when vehicles were close to the intersection.  ...  HIDDEN MARKOV DRIVING MODEL A driver model relates the driver's behavior to his perception, physical and psychological conditions, driving experience, and preferences under traffic conditions.  ... 
doi:10.3141/1980-05 fatcat:xmilz4wpzfhztj2sdqwformtze

Probabilistic Maneuver Prediction in Traffic Scenarios

Jonas Firl, Quan Tran
2011 European Conference on Mobile Robots  
We use Hidden Markov Models (HMMs) for modeling the spatiotemporal dependencies of traffic situations.  ...  The parameters of the individual models are learned from a data base, generated by a professional driving simulation software.  ...  THEORETICAL FRAMEWORK Hidden Markov Models (HMMs) are one of the most popular methods for probabilistic modeling of sequential data.  ... 
dblp:conf/ecmr/FirlT11 fatcat:bvpf3cn54zb2xnd2emsrfci65i

Finite Mixture of the Hidden Markov Model for Driving Style Analysis

Lusa Ding, Ting Zhu, Yanli Wang, Yajie Zou, Octavian Adrian Postolache
2022 Journal of Advanced Transportation  
The hidden Markov model (HMM) and the finite mixture of the hidden Markov model (MHMM) are adopted to extract behavior semantics.  ...  In this paper, we propose a driving style analysis to describe the personalized driving styles from time-series driving data without specifying the levels in advance but by estimating them from the data  ...  research was funded by the National Natural Science Foundation of China (Grant no. 71971160), the Shanghai Science and Technology Committee (Grant no. 19210745700), and the Fundamental Research Funds for  ... 
doi:10.1155/2022/4989947 fatcat:jnja3wuwlbfldgbumxudexhiqe

Vision based Traffic Police Hand Signal Recognition in Surveillance Video - A Survey

R. Sathya, M. Kalaiselvi Geetha
2013 International Journal of Computer Applications  
The recognition of human hand gesture movement can be performed at various level of abstraction. This survey concentrate on approaches that aim on recognizing traffic police hand signals.  ...  Human gesture recognition has become a very important topic in computer vision. The purpose of this survey is to provide a detailed overview and categories of current issues and trends.  ...  Two types of HMM model. The Hidden Markov Models are a popular technique for recognizing human gesture in a varity of applicatisons and sensor configuration.  ... 
doi:10.5120/14037-2192 fatcat:dtns3iu3fje77dnrgsn2346qoq

On the estimation of arterial route travel time distribution with Markov chains

Mohsen Ramezani, Nikolas Geroliminis
2012 Transportation Research Part B: Methodological  
In the proposed technique, given probe vehicles travel times of the traversing links, a two-dimensional (2D) diagram is established with data points representing travel times of a probe vehicle crossing  ...  By applying a Markov chain procedure, we integrate the correlation between states of 2D diagrams for successive links.  ...  The authors propose a statistical modeling framework that captures the evolution of traffic flow as a Coupled Hidden Markov Model (CHMM).  ... 
doi:10.1016/j.trb.2012.08.004 fatcat:5e6qgrbswrbrzabqes6ey2yux4

On the reliability of safety message broadcastin urban vehicular ad hoc networks

Saeed Bastani, Bjorn Landfeldt, Lavy Libman
2011 Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems - MSWiM '11  
From the perspective of safety, the application performance depends foremost on two metrics: for the event-driven warning messages, the probability of message reception; and for periodic messages, the  ...  Focusing on a road segment linked to a signalized junction as a basic building block of urban traffic systems, we apply a novel road traffic density model to investigate the dynamics of the reliability  ...  rate of the queue, thus more positions will experience a high average per-vehicle hidden terminal level.  ... 
doi:10.1145/2068897.2068951 dblp:conf/mswim/BastaniLL11 fatcat:uhtwzy54l5banaxsz7iamh2noy

Modeling Pipeline Driving Behaviors

Xi Zou, David M. Levinson
2006 Transportation Research Record  
This study used hidden Markov models (HMMs) to model the driving behavior of through-going vehicles on major roads at intersections. Observed vehicle movement data were used to estimate the model.  ...  A single HMM was used to cluster movements when vehicles were close to the intersection.  ...  HIDDEN MARKOV DRIVING MODEL A driver model relates the driver's behavior to his perception, physical and psychological conditions, driving experience, and preferences under traffic conditions.  ... 
doi:10.1177/0361198106198000104 fatcat:yp67gb5yezfxzlac2qdnheufpy

Understanding vehicular traffic behavior from video: a survey of unsupervised approaches

Brendan Tran Morris, Mohan Manubhai Trivedi
2013 Journal of Electronic Imaging (JEI)  
The review focuses on two main methods for scene description, trajectory clustering and topic modeling. Example applications that utilize the behavioral modeling techniques are also presented.  ...  Recent emerging trends for automatic behavior analysis and understanding from infrastructure video are reviewed.  ...  The authors would like to thank the reviewers for their useful comments and members of the CVRR laboratory for their support.  ... 
doi:10.1117/1.jei.22.4.041113 fatcat:ftd2elgj5vd4vaada3hxfsfiby

Short-term traffic prediction by two-level data driven model in 5G-enabled edge computing networks

Yupin Huang, Liping Qian, Anqi Feng, Ningning Yu, Yuan Wu
2019 IEEE Access  
Therefore, we propose a two-level data driven model for short-term traffic prediction in an edge computing environment.  ...  INDEX TERMS Short-term traffic prediction, deep belief network, hidden Markov model, edge computing.  ...  CONCLUSION In this paper, we have proposed a two-level data-driven model for short-term traffic prediction in the context of edge computing.  ... 
doi:10.1109/access.2019.2938236 fatcat:ebbdrr6cyveunbsm45tpn2ibzu
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