A red-light running prevention system based on artificial neural network and vehicle trajectory data.

Abstract:

:The high frequency of red-light running and complex driving behaviors at the yellow onset at intersections cannot be explained solely by the dilemma zone and vehicle kinematics. In this paper, the author presented a red-light running prevention system which was based on artificial neural networks (ANNs) to approximate the complex driver behaviors during yellow and all-red clearance and serve as the basis of an innovative red-light running prevention system. The artificial neural network and vehicle trajectory are applied to identify the potential red-light runners. The ANN training time was also acceptable and its predicting accurate rate was over 80%. Lastly, a prototype red-light running prevention system with the trained ANN model was described. This new system can be directly retrofitted into the existing traffic signal systems.

journal_name

Comput Intell Neurosci

authors

Li P,Li Y,Guo X

doi

10.1155/2014/892132

subject

Has Abstract

pub_date

2014-01-01 00:00:00

pages

892132

eissn

1687-5265

issn

1687-5273

journal_volume

2014

pub_type

杂志文章
  • Improved Transductive Support Vector Machine for a Small Labelled Set in Motor Imagery-Based Brain-Computer Interface.

    abstract::Long and tedious calibration time hinders the development of motor imagery- (MI-) based brain-computer interface (BCI). To tackle this problem, we use a limited labelled set and a relatively large unlabelled set from the same subject for training based on the transductive support vector machine (TSVM) framework. We fi...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/2087132

    authors: Xu Y,Hua J,Zhang H,Hu R,Huang X,Liu J,Guo F

    更新日期:2019-11-25 00:00:00

  • A reinforcement learning framework for spiking networks with dynamic synapses.

    abstract::An integration of both the Hebbian-based and reinforcement learning (RL) rules is presented for dynamic synapses. The proposed framework permits the Hebbian rule to update the hidden synaptic model parameters regulating the synaptic response rather than the synaptic weights. This is performed using both the value and ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2011/869348

    authors: El-Laithy K,Bogdan M

    更新日期:2011-01-01 00:00:00

  • SGB-ELM: An Advanced Stochastic Gradient Boosting-Based Ensemble Scheme for Extreme Learning Machine.

    abstract::A novel ensemble scheme for extreme learning machine (ELM), named Stochastic Gradient Boosting-based Extreme Learning Machine (SGB-ELM), is proposed in this paper. Instead of incorporating the stochastic gradient boosting method into ELM ensemble procedure primitively, SGB-ELM constructs a sequence of weak ELMs where ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/4058403

    authors: Guo H,Wang J,Ao W,He Y

    更新日期:2018-06-26 00:00:00

  • Operating Comfort Prediction Model of Human-Machine Interface Layout for Cabin Based on GEP.

    abstract::In view of the evaluation and decision-making problem of human-machine interface layout design for cabin, the operating comfort prediction model is proposed based on GEP (Gene Expression Programming), using operating comfort to evaluate layout scheme. Through joint angles to describe operating posture of upper limb, t...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/896072

    authors: Deng L,Wang G,Chen B

    更新日期:2015-01-01 00:00:00

  • Effectiveness of Serious Games for Leap Motion on the Functionality of the Upper Limb in Parkinson's Disease: A Feasibility Study.

    abstract::The design and application of Serious Games (SG) based on the Leap Motion sensor are presented as a tool to support the rehabilitation therapies for upper limbs. Initially, the design principles and their implementation are described, focusing on improving both unilateral and bilateral manual dexterity and coordinatio...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/7148427

    authors: Oña ED,Balaguer C,Cano-de la Cuerda R,Collado-Vázquez S,Jardón A

    更新日期:2018-04-11 00:00:00

  • Evolutionary Spiking Neural Networks for Solving Supervised Classification Problems.

    abstract::This paper presents a grammatical evolution (GE)-based methodology to automatically design third generation artificial neural networks (ANNs), also known as spiking neural networks (SNNs), for solving supervised classification problems. The proposal performs the SNN design by exploring the search space of three-layere...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/4182639

    authors: López-Vázquez G,Ornelas-Rodriguez M,Espinal A,Soria-Alcaraz JA,Rojas-Domínguez A,Puga-Soberanes HJ,Carpio JM,Rostro-Gonzalez H

    更新日期:2019-03-28 00:00:00

  • RnRTD: Intelligent Approach Based on the Relationship-Driven Neural Network and Restricted Tensor Decomposition for Multiple Accusation Judgment in Legal Cases.

    abstract::The use of intelligent judgment technology to assist in judgment is an inevitable trend in the development of judgment in contemporary social legal cases. Using big data and artificial intelligence technology to accurately determine multiple accusations involved in legal cases is an urgent problem to be solved in lega...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/6705405

    authors: Guo X,Zhang H,Ye L,Li S

    更新日期:2019-07-07 00:00:00

  • Rifle Shooting Performance Correlates with Electroencephalogram Beta Rhythm Network Activity during Aiming.

    abstract::To study the relationship between brain network and shooting performance during shooting aiming, we collected electroencephalogram (EEG) signals from 40 skilled shooters during rifle shooting and calculated the EEG functional coupling, functional brain network topology, and correlation coefficients between these EEG c...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/4097561

    authors: Gong A,Liu J,Jiang C,Fu Y

    更新日期:2018-11-11 00:00:00

  • A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

    abstract::Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheri...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/8734214

    authors: Yang JH,Cheng CH,Chan CP

    更新日期:2017-01-01 00:00:00

  • Intelligence Is beyond Learning: A Context-Aware Artificial Intelligent System for Video Understanding.

    abstract::Understanding video files is a challenging task. While the current video understanding techniques rely on deep learning, the obtained results suffer from a lack of real trustful meaning. Deep learning recognizes patterns from big data, leading to deep feature abstraction, not deep understanding. Deep learning tries to...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/8813089

    authors: Ghozia A,Attiya G,Adly E,El-Fishawy N

    更新日期:2020-12-23 00:00:00

  • Classifying EEG Signals during Stereoscopic Visualization to Estimate Visual Comfort.

    abstract::With stereoscopic displays a sensation of depth that is too strong could impede visual comfort and may result in fatigue or pain. We used Electroencephalography (EEG) to develop a novel brain-computer interface that monitors users' states in order to reduce visual strain. We present the first system that discriminates...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/2758103

    authors: Frey J,Appriou A,Lotte F,Hachet M

    更新日期:2016-01-01 00:00:00

  • A Genetic Algorithm and Fuzzy Logic Approach for Video Shot Boundary Detection.

    abstract::This paper proposed a shot boundary detection approach using Genetic Algorithm and Fuzzy Logic. In this, the membership functions of the fuzzy system are calculated using Genetic Algorithm by taking preobserved actual values for shot boundaries. The classification of the types of shot transitions is done by the fuzzy ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/8469428

    authors: Thounaojam DM,Khelchandra T,Manglem Singh Kh,Roy S

    更新日期:2016-01-01 00:00:00

  • Characterizing the Input-Output Function of the Olfactory-Limbic Pathway in the Guinea Pig.

    abstract::Nowadays the neuroscientific community is taking more and more advantage of the continuous interaction between engineers and computational neuroscientists in order to develop neuroprostheses aimed at replacing damaged brain areas with artificial devices. To this end, a technological effort is required to develop neura...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/359590

    authors: Breschi GL,Ciliberto C,Nieus T,Rosasco L,Taverna S,Chiappalone M,Pasquale V

    更新日期:2015-01-01 00:00:00

  • Inferring functional brain states using temporal evolution of regularized classifiers.

    abstract::We present a framework for inferring functional brain state from electrophysiological (MEG or EEG) brain signals. Our approach is adapted to the needs of functional brain imaging rather than EEG-based brain-computer interface (BCI). This choice leads to a different set of requirements, in particular to the demand for ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2007/52609

    authors: Zhdanov A,Hendler T,Ungerleider L,Intrator N

    更新日期:2007-01-01 00:00:00

  • Assessment of Multivariate Neural Time Series by Phase Synchrony Clustering in a Time-Frequency-Topography Representation.

    abstract::Most EEG phase synchrony measures are of bivariate nature. Those that are multivariate focus on producing global indices of the synchronization state of the system. Thus, better descriptions of spatial and temporal local interactions are still in demand. A framework for characterization of phase synchrony relationship...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/2406909

    authors: Porta-Garcia MA,Valdes-Cristerna R,Yanez-Suarez O

    更新日期:2018-03-21 00:00:00

  • On Ev-Degree and Ve-Degree Topological Properties of Tickysim Spiking Neural Network.

    abstract::Topological indices are indispensable tools for analyzing networks to understand the underlying topology of these networks. Spiking neural network architecture (SpiNNaker or TSNN) is a million-core calculating engine which aims at simulating the behavior of aggregates of up to a billion neurons in real time. Tickysim ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/8429120

    authors: Cancan M

    更新日期:2019-06-02 00:00:00

  • Modeling spike-train processing in the cerebellum granular layer and changes in plasticity reveal single neuron effects in neural ensembles.

    abstract::The cerebellum input stage has been known to perform combinatorial operations on input signals. In this paper, two types of mathematical models were used to reproduce the role of feed-forward inhibition and computation in the granular layer microcircuitry to investigate spike train processing. A simple spiking model a...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2012/359529

    authors: Medini C,Nair B,D'Angelo E,Naldi G,Diwakar S

    更新日期:2012-01-01 00:00:00

  • Random bin for analyzing neuron spike trains.

    abstract::When analyzing neuron spike trains, it is always the problem of how to set the time bin. Bin width affects much to analyzed results of such as periodicity of the spike trains. Many approaches have been proposed to determine the bin setting. However, these bins are fixed through the analysis. In this paper, we propose ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2012/153496

    authors: Tamura S,Miyoshi T,Sawai H,Mizuno-Matsumoto Y

    更新日期:2012-01-01 00:00:00

  • Analyzing the effects of gap junction blockade on neural synchrony via a motoneuron network computational model.

    abstract::In specific regions of the central nervous system (CNS), gap junctions have been shown to participate in neuronal synchrony. Amongst the CNS regions identified, some populations of brainstem motoneurons are known to be coupled by gap junctions. The application of various gap junction blockers to these motoneuron popul...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2012/575129

    authors: Memelli H,Horn KG,Wittie LD,Solomon IC

    更新日期:2012-01-01 00:00:00

  • A functional model of sensemaking in a neurocognitive architecture.

    abstract::Sensemaking is the active process of constructing a meaningful representation (i.e., making sense) of some complex aspect of the world. In relation to intelligence analysis, sensemaking is the act of finding and interpreting relevant facts amongst the sea of incoming reports, images, and intelligence. We present a cog...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2013/921695

    authors: Lebiere C,Pirolli P,Thomson R,Paik J,Rutledge-Taylor M,Staszewski J,Anderson JR

    更新日期:2013-01-01 00:00:00

  • New algorithms for computing the time-to-collision in freeway traffic simulation models.

    abstract::Ways to estimate the time-to-collision are explored. In the context of traffic simulation models, classical lane-based notions of vehicle location are relaxed and new, fast, and efficient algorithms are examined. With trajectory conflicts being the main focus, computational procedures are explored which use a two-dime...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2014/761047

    authors: Hou J,List GF,Guo X

    更新日期:2014-01-01 00:00:00

  • An Efficient Robust Eye Localization by Learning the Convolution Distribution Using Eye Template.

    abstract::Eye localization is a fundamental process in many facial analyses. In practical use, it is often challenged by illumination, head pose, facial expression, occlusion, and other factors. It remains great difficulty to achieve high accuracy with short prediction time and low training cost at the same time. This paper pre...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/709072

    authors: Li X,Dou Y,Niu X,Xu J,Xiao R

    更新日期:2015-01-01 00:00:00

  • Real-Time Monitoring and Fault Diagnosis of a Low Power Hub Motor Using Feedforward Neural Network.

    abstract::Low power hub motors are widely used in electromechanical systems such as electrical bicycles and solar vehicles due to their robustness and compact structure. Such systems driven by hub motors (in wheel motors) encounter previously defined and undefined faults under operation. It may inevitably lead to the interrupti...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/7129376

    authors: Şimşir M,Bayır R,Uyaroğlu Y

    更新日期:2016-01-01 00:00:00

  • A novel multiple instance learning method based on extreme learning machine.

    abstract::Since real-world data sets usually contain large instances, it is meaningful to develop efficient and effective multiple instance learning (MIL) algorithm. As a learning paradigm, MIL is different from traditional supervised learning that handles the classification of bags comprising unlabeled instances. In this paper...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/405890

    authors: Wang J,Cai L,Peng J,Jia Y

    更新日期:2015-01-01 00:00:00

  • Robust SAR Automatic Target Recognition Based on Transferred MS-CNN with L2-Regularization.

    abstract::Though Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) via Convolutional Neural Networks (CNNs) has made huge progress toward deep learning, some key issues still remain unsolved due to the lack of sufficient samples and robust model. In this paper, we proposed an efficient transferred Max-Slice CNN ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/9140167

    authors: Zhai Y,Deng W,Xu Y,Ke Q,Gan J,Sun B,Zeng J,Piuri V

    更新日期:2019-11-15 00:00:00

  • Estimation of critical gap based on Raff's definition.

    abstract::Critical gap is an important parameter used to calculate the capacity and delay of minor road in gap acceptance theory of unsignalized intersections. At an unsignalized intersection with two one-way traffic flows, it is assumed that two events are independent between vehicles' arrival of major stream and vehicles' arr...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2014/236072

    authors: Guo RJ,Wang XJ,Wang WX

    更新日期:2014-01-01 00:00:00

  • Deep Learning for Plant Identification in Natural Environment.

    abstract::Plant image identification has become an interdisciplinary focus in both botanical taxonomy and computer vision. The first plant image dataset collected by mobile phone in natural scene is presented, which contains 10,000 images of 100 ornamental plant species in Beijing Forestry University campus. A 26-layer deep lea...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/7361042

    authors: Sun Y,Liu Y,Wang G,Zhang H

    更新日期:2017-01-01 00:00:00

  • Software Development Effort Estimation Using Regression Fuzzy Models.

    abstract::Software effort estimation plays a critical role in project management. Erroneous results may lead to overestimating or underestimating effort, which can have catastrophic consequences on project resources. Machine-learning techniques are increasingly popular in the field. Fuzzy logic models, in particular, are widely...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/8367214

    authors: Nassif AB,Azzeh M,Idri A,Abran A

    更新日期:2019-02-20 00:00:00

  • An effective hybrid cuckoo search algorithm with improved shuffled frog leaping algorithm for 0-1 knapsack problems.

    abstract::An effective hybrid cuckoo search algorithm (CS) with improved shuffled frog-leaping algorithm (ISFLA) is put forward for solving 0-1 knapsack problem. First of all, with the framework of SFLA, an improved frog-leap operator is designed with the effect of the global optimal information on the frog leaping and informat...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2014/857254

    authors: Feng Y,Wang GG,Feng Q,Zhao XJ

    更新日期:2014-01-01 00:00:00

  • A novel design of 4-class BCI using two binary classifiers and parallel mental tasks.

    abstract::A novel 4-class single-trial brain computer interface (BCI) based on two (rather than four or more) binary linear discriminant analysis (LDA) classifiers is proposed, which is called a "parallel BCI." Unlike other BCIs where mental tasks are executed and classified in a serial way one after another, the parallel BCI u...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2008/437306

    authors: Geng T,Gan JQ,Dyson M,Tsui CS,Sepulveda F

    更新日期:2008-01-01 00:00:00