Journal articles: 'The traffic square'

1

Mukherjee, G., and S. S. Manna. "Traffic flow on directed square lattice." Physica A: Statistical Mechanics and its Applications 346, no. 1-2 (February 2005): 132–38. http://dx.doi.org/10.1016/j.physa.2004.08.059.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Chandra, Anjan Kumar. "Jamming of directed traffic on a square lattice." Journal of Statistical Mechanics: Theory and Experiment 2006, no. 08 (August 4, 2006): P08005. http://dx.doi.org/10.1088/1742-5468/2006/08/p08005.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Nurdin, Ade. "Potensi Pelanggaran Lalu Lintas Di Simpang Mayang Tujuan Jambi Town Square Mall." Jurnal Civronlit Unbari 5, no. 2 (October 16, 2020): 49. http://dx.doi.org/10.33087/civronlit.v5i2.68.

Full text

Abstract:

One of the biggest factors causing traffic accidents is a violation committed by drivers who are less orderly in traffic. This research was conducted on Jalan Kapten A. Bakarudin Simpang Mayang, Jambi Town Square Mall (Jamtos mall). The research objective is to find out how much the traffic sign violations at the Intersection of Jamtos mall. The results show that the highest traffic sign violations occurred on Sunday, August 16, 2020, with 1996 vehicles : 1494 two-wheeled vehicles and 502 four-wheeled vehicles. Meanwhile, the vehicles that enter Jamtos mall consist of 519 two-wheeled vehicles and 237 four-wheeled vehicles with the highest violation rate of two-wheeled vehicles at 19.00-20.00 WIB totaling 145 vehicles and 52 four-wheeled vehicles at 13.00-14. 00 WIB. The largest percentage of traffic violations to the Jamtos mall destination occurred on Tuesday, August 18, 2020, amounting to 41%, hereby stating that there was a large turn-around traffic sign violation.

APA, Harvard, Vancouver, ISO, and other styles

4

Tran Quang, Duy, and Sang Hoon Bae. "A Hybrid Deep Convolutional Neural Network Approach for Predicting the Traffic Congestion Index." Promet - Traffic&Transportation 33, no. 3 (May 31, 2021): 373–85. http://dx.doi.org/10.7307/ptt.v33i3.3657.

Full text

Abstract:

Traffic congestion is one of the most important issues in large cities, and the overall travel speed is an important factor that reflects the traffic status on road networks. This study proposes a hybrid deep convolutional neural network (CNN) method that uses gradient descent optimization algorithms and pooling operations for predicting the short-term traffic congestion index in urban networks based on probe vehicles. First, the input data are collected by the probe vehicles to calculate the traffic congestion index (output label). Then, a CNN that uses gradient descent optimization algorithms and pooling operations is applied to enhance its performance. Finally, the proposed model is chosen on the basis of the R-squared (R2) and root mean square error (RMSE) values. In the best-case scenario, the proposed model achieved an R2 value of 98.7%. In addition, the experiments showed that the proposed model significantly outperforms other algorithms, namely the ordinary least squares (OLS), k-nearest neighbors (KNN), random forest (RF), recurrent neural network (RNN), artificial neural network (ANN), and convolutional long short-term memory (ConvLSTM), in predicting traffic congestion index. Furthermore, using the proposed method, the time-series changes in the traffic congestion status can be reliably visualized for the entire urban network.

APA, Harvard, Vancouver, ISO, and other styles

5

Gandhi, Sanyam S. "Review on Advanced Traffic Management at Square (Chowk) in India." International Journal for Research in Applied Science and Engineering Technology 7, no. 3 (March 31, 2019): 1161–64. http://dx.doi.org/10.22214/ijraset.2019.3207.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Skupień, Emilia, and Mateusz Rydlewski. "Analysis of the influence of traffic lights on the functioning of public transport within Kosciuszko square in Wroclaw." Transportation Overview - Przeglad Komunikacyjny 2018, no. 4 (April 1, 2018): 1–10. http://dx.doi.org/10.35117/a_eng_18_04_01.

Full text

Abstract:

Traffic management in a city, even assisted by intelligent transport systems, is a very complex process. Analyzing a single intersection may not produce the intended effect or even contribute to a deterioration from the initial state. The most important element of introducing changes should be traffic monitoring. The article presents the influence of traffic lights on the functioning of public transport, on the example of Kosciuszko Square in Wroclaw. Presented proposals were preceded by several hours of traffic observations, some of the results were presented at this paper. The article proposes changes to streamline public transport within the square.

APA, Harvard, Vancouver, ISO, and other styles

7

Yao, Baozhen, Qianqian Yan, Qian Chen, Zhihui Tian, and Xuefeng Zhu. "Simulation-based optimization for urban transportation demand management strategy." SIMULATION 94, no. 7 (March 16, 2018): 637–47. http://dx.doi.org/10.1177/0037549718761189.

Full text

Abstract:

Transportation demand management (TDM) is one of the important methods for solving the problem of increasingly severe urban traffic congestion. This paper proposes a bi-level model to optimize urban TDM strategies based on simulation. The upper level is the TDM strategy optimization model, searching for the optimal TDM strategy. The lower level is a traffic assignment model based on the simulation, assigning traffic flow to multimodal transport networks according to the candidate TDM strategies. A heuristic algorithm is also defined and implemented to optimize TDM strategies. Based on VISSIM simulation, the optimization for TDM strategies proposed in this paper is validated with the research area of Harbor Square–San Ba Square–Er Qi Square in Dalian in China. The results show that the optimization of urban TDM strategies can effectively alleviate urban traffic congestion. It provides a scientific decision basis for urban TDM policy.

APA, Harvard, Vancouver, ISO, and other styles

8

Kamble, Rahul K. "Traffic Intersections Noise Levels and Daily Noise Exposure in Chandrapur City, Central India." Indonesian Journal of Environmental Management and Sustainability 3, no. 3 (September 30, 2019): 80–92. http://dx.doi.org/10.26554/ijems.2019.3.3.80-92.

Full text

Abstract:

Noise level monitoring was carried out at nine important traffic intersections of the Chandrapur city to ascertain noise levels and daily noise exposure. A pre-calibrated mini sound level meter was used for noise measurement. Observations were recorded for 24 hours and noise level during the day, night and for 24-hours was computed. Maximum noise level during daytime was 84.27 dB(A) at Bangali camp square; whereas, minimum 79.23 dB(A) at Priyadarshani square. In case of nighttime maximum 85.90 dB(A) was at Warora naka square and minimum 70.06 dB(A) at the Jatpura gate. Minimum noise level during 24-hours was at Bagla square 84.34 dB(A) and maximum 91.14 dB(A) at Warora naka square. Noise level during day and night were above the Indian noise standard for the commercial area. The Bangali camp square was identified as the most ear-splitting square during daytime and Warora naka square at nighttime and for 24-hours also. Peak noise was recorded from 10.00 am to 11.00 am and 3.00 pm to 7.00 pm. Vehicular noise, horns, and improper road design contributed significantly to noise levels at traffic intersections. Daily noise exposure analysis by Health and Safety Executive, UK software revealed Bangali camp square and Ramnagar police station square’s daily noise exposure for 0.25 hour was maximum 70 LEP,d and minimum at Gandhi square and Bagla square 65 LEP,d. Noise levels indicated no immediate effect for hearing loss. Control measures for reduction of noise levels at traffic intersections have also been proposed.

APA, Harvard, Vancouver, ISO, and other styles

9

Al –Azawee, Esraa Thamir. "Evaluation of Traffic Performance of Ahmed Urabi Square in Baghdad City." Journal of Engineering 24, no. 6 (June 1, 2018): 86. http://dx.doi.org/10.31026/j.eng.2018.06.07.

Full text

Abstract:

At present, smooth movement on the roads is a matter which is needed for each user. Many roads, especially in urban areas geometrically improved because of the number of vehicles increase from time to time. In this research, Highway capacity software, HCS, 2000, will be adopted to determine the effectiveness of roundabout in terms of capacity of roundabout, delay and level of service of roundabout. The results of the analysis indicated that the Ahmed Urabi roundabout operates under level of service F with an average control delay of 300 seconds per vehicle during the peak hours. The through movements of Alkarrada- Aljadiriya direction (Major Direction) represent the heaviest traffic volumes in Ahmed Urabi intersection. The use of underpass to serve the through movements in Alkarrada-Aljadiriya direction will lead to release the traffic volume in the Ahmed Urabi intersection with a rate 51 % .After the adoption of the proposed geometric design, it will operate at LOS B in the design year (2037). The proposed circulatory roadway width for the roundabout is 16m and the required number of lanes equal to three lanes for each side of the underpass and four lanes for all the approaches of the roundabout.

APA, Harvard, Vancouver, ISO, and other styles

10

Horiguchi, Tsuyoshi, and Takehito Sakakibara. "Numerical simulations for traffic-flow models on a decorated square lattice." Physica A: Statistical Mechanics and its Applications 252, no. 3-4 (April 1998): 388–404. http://dx.doi.org/10.1016/s0378-4371(97)00628-6.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Zhou, Jingjing, Jiahai Yang, Yang Yang, Hongbo Liu, and Ming Zeng. "Traffic matrix estimation based on a square root Kalman filtering algorithm." International Journal of Network Management 18, no. 6 (November 2008): 539–51. http://dx.doi.org/10.1002/nem.708.

Full text

APA, Harvard, Vancouver, ISO, and other styles

12

Liu, Jun-Xia, and Zhen-Hong Jia. "Telecommunication Traffic Prediction Based on Improved LSSVM." International Journal of Pattern Recognition and Artificial Intelligence 32, no. 03 (November 22, 2017): 1850007. http://dx.doi.org/10.1142/s0218001418500076.

Full text

Abstract:

Telecommunication traffic prediction is an important aspect of data analysis and processing in communication networks. In this study, we utilize the least-squares support vector machine (LSSVM) prediction method to improve the prediction performance of telecommunication traffic. As the parameters of LSSVM are difficult to determine, we propose to optimize the LSSVM parameters using the improved artificial bee colony (IABC) algorithm based on the fitness-prediction strategy (i.e. FP-IABC). We employ real traffic data collected on site to establish a telecommunication traffic forecasting model based on FP-IABC optimizing LSSVM (FP-IABC-LSSVM). The experiment results indicate that in the case involving no increase in the computational complexity, the proposed telecommunication traffic forecasting model-based FP-IABC-LSSVM has a higher prediction accuracy than the prediction model based on the ABC optimizing LSSVM (ABC-LSSVM), particle swarm optimizing LSSVM (PSO-LSSVM), and genetic algorithm optimizing LSSVM (GA-LSSVM). Further, with respect to the standard root mean square error and the average computation time, the proposed FP-IABC-LSSVM is the optimal prediction method of all of the comparison methods. The proposed prediction method not only improves the prediction accuracy, but also reduces the average computation time.

APA, Harvard, Vancouver, ISO, and other styles

13

Kim, Amy, Lysandra Medal, Shuoqi Wang, and Timothy Larson. "Indoor and Outdoor Concentrations of Particulate Matter in an Airport Terminal Building: A Pilot Study at Soekarno-Hatta International Airport in Indonesia." Buildings 10, no. 2 (February 7, 2020): 25. http://dx.doi.org/10.3390/buildings10020025.

Full text

Abstract:

The air quality inside airport terminal buildings is a lesser studied area compared to ambient air quality at the airport. The contribution of outdoor particulate matter (PM), aircraft traffic, and passenger traffic to indoor PM concentration is not well understood. Using the largest airport in Southeast Asia as the study site (extends 17.9 square kilometers), the objective of this paper is to conduct a preliminary analysis to examine the mass concentrations of fine particles, including PM1 and PM2.5, and coarse particles PM2.5–10 inside a four-story terminal building spanning 400,000 square meters in Jakarta, Indonesia. The results showed the indoor/outdoor (I/O) ratio of 0.42 for PM1 with 15-min time lag and 0.33 for PM2.5 with 30-min time lag. The aircraft traffic appeared to have a significant impact on indoor PM1 and PM2.5, whereas the passenger traffic showed an influence on indoor PM2.5–10.

APA, Harvard, Vancouver, ISO, and other styles

14

Li, Zongzhi, Hoang Dao, Harshingar Patel, Yi Liu, and Bei Zhou. "Incorporating Traffic Control and Safety Hardware Performance Functions into Risk-based Highway Safety Analysis." PROMET - Traffic&Transportation 29, no. 2 (April 19, 2017): 143–53. http://dx.doi.org/10.7307/ptt.v29i2.2041.

Full text

Abstract:

Traffic control and safety hardware such as traffic signs, lighting, signals, pavement markings, guardrails, barriers, and crash cushions form an important and inseparable part of highway infrastructure affecting safety performance. Significant progress has been made in recent decades to develop safety performance functions and crash modification factors for site-specific crash predictions. However, the existing models and methods lack rigorous treatments of safety impacts of time-deteriorating conditions of traffic control and safety hardware. This study introduces a refined method for computing the Safety Index (SI) as a means of crash predictions for a highway segment that incorporates traffic control and safety hardware performance functions into the analysis. The proposed method is applied in a computation experiment using five-year data on nearly two hundred rural and urban highway segments. The root-mean square error (RMSE), Chi-square, Spearman’s rank correlation, and Mann-Whitney U tests are employed for validation.

APA, Harvard, Vancouver, ISO, and other styles

15

Zhao, Jing. "The Exploration of the Design Principle of the Railway Station Square." Applied Mechanics and Materials 716-717 (December 2014): 232–35. http://dx.doi.org/10.4028/www.scientific.net/amm.716-717.232.

Full text

Abstract:

Railway station square is integrated planning designed, then we need to consider multiple relation factors in the designing. The different activities’ manners all need to make consideration. The premise of design is smooth square crowd scattered, safe traffic and comfort square environment. And as one part of urban spatial environment, the square should be designed as the image of city gateway. This paper makes exploration of railway square design from every aspect.

APA, Harvard, Vancouver, ISO, and other styles

16

Li, Ming Shun, and Zuo Hui Zhu. "Construction of Adjustment Model of Traffic Volume Forecast in The Latter Part of Expressway Operating." Applied Mechanics and Materials 178-181 (May 2012): 1526–31. http://dx.doi.org/10.4028/www.scientific.net/amm.178-181.1526.

Full text

Abstract:

This paper focuses on the problem of serious deviation about predicted traffic flow on the feasibility study stage of expressway,puts forward an idea to compare and analyse the predicted traffic flow in feasibility study stage and the actual traffic after project operation,introducts least square method model, and finds out the linear relationship between them, thus predicts traffic flow of expressway operation. Finally, the calculation is made by combining with concrete expressway project,which proves that this method is usefull to improving the accuracy of the traffic flow forecast.

APA, Harvard, Vancouver, ISO, and other styles

17

Chen, Fei, Wei Lu, and Jun Cai. "Traffic Accessibility Research for Daily Activities of Davos Square in Dalian, China." Journal of Civil Engineering and Science 4, no. 3 (September 30, 2015): 101–5. http://dx.doi.org/10.5963/jces0403005.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

Adekitan, Aderibigbe, and Claudius Awosope. "Internet data traffic analysis for identifying usage trends on each day of the week in a university." Indonesian Journal of Electrical Engineering and Computer Science 17, no. 3 (March 1, 2020): 1442. http://dx.doi.org/10.11591/ijeecs.v17.i3.pp1442-1452.

Full text

Abstract:

<p><em>Internet data traffic monitoring and management are important requirements for ensuring top notch quality of service in a network. Data traffic logs contain useful hidden information that can be harnessed and interpreted as a resource for making informed network management decisions. In this study, logged internet data traffic for both the upload and download traffic in a university for one year was analysed using statistics and partial least squares approach to structural equation modelling (PLS-SEM). Time series plots, statistical properties and trends for each day of the week over a 51-week period were developed. The result shows that the most data was downloaded on Thursdays while the most upload occurred on Mondays. A path model was developed using Smart PLS3, and the performance of the model was evaluated using the construct reliability and validity of the model. The results reveal that the weekly variance is majorly accounted for by usage variations on Tuesdays, Fridays and Saturdays. An overall model R-square value of 0.876 was observed.</em></p>

APA, Harvard, Vancouver, ISO, and other styles

19

Zhang, Chunbo, Xiucheng Guo, and Zhenping Xi. "Determination of Observation Weight to Calibrate Freeway Traffic Fundamental Diagram Using Weighted Least Square Method (WLSM)." PROMET - Traffic&Transportation 29, no. 2 (April 21, 2017): 203–12. http://dx.doi.org/10.7307/ptt.v29i2.2088.

Full text

Abstract:

Due to unbalanced speed-density observations, the one-regime traffic fundamental diagram and speed-density relationship models using least square method (LSM) cannot reflect actual conditions under congested/jam traffic. In that case, it is inevitable to adopt the weighted least square method (WLSM). This paper used freeway Georgia State Route 400 observation data and proposed 5 weight determination methods except the LSM to analyse 5 wellknown one-regime speed-density models to determine the best calibrating models. The results indicated that different one-regime speed-density models have different best calibrating models, for Greenberg, it was possible to find a specific weight using LSM, which is similar for Underwood and Northwestern Models, but different for that one known as 3PL model. An interesting case is the Newell's Model which fits well with two distinct calibration weights. This paper can make contribution to calibrating a more precise traffic fundamental diagram.

APA, Harvard, Vancouver, ISO, and other styles

20

Chen, Kuan Min, Lai Fa Xie, and Wen Sen Xiang. "Traffic Accidents Prediction Using Improved Grey-Markov Model." Advanced Materials Research 378-379 (October 2011): 222–25. http://dx.doi.org/10.4028/www.scientific.net/amr.378-379.222.

Full text

Abstract:

Considering the grey feature of traffic accident occurrence, grey model optimized by least-square theory is introduced to prejudge the future trend of traffic accident. To improve the prediction precision of this model, an amendment factor of boundary value and Markov chain are proposed and the numerical application proves the effectiveness of this Grey –Markov predict model.

APA, Harvard, Vancouver, ISO, and other styles

21

Turgut, Duygu Turgut. "CASE STUDY ON HOLISTIC ASSESSMENT OF THE RELATIONSHIP BETWEEN CITY AND SQUARE." JOURNAL OF ARCHITECTURE AND URBANISM 44, no. 2 (October 16, 2020): 152–65. http://dx.doi.org/10.3846/jau.2020.11331.

Full text

Abstract:

While the squares have been in the network of relations with the political, social and religious structure of the society since the early days of history, today, they have been associated with the cars, speed and technology in the process formed with the modernization movement. In some squares, there are tramways, public transportation routes and stops, and there are also motor vehicles. The squares have turned into places where there is a continuous flow with fast traffic except for waiting at the bus stops and railway station. With this change, our needs also changed, and with the introduction of motor vehicles in our lives, the squares remained as neglected urban spaces in an effort to create a transportation network. The use of the squares belongs to the period in which people have habit of being together, but now squares use belongs to a period in which we are not together even if we are side by side. Within the scope of this study, nowadays, approaches and practices for the squares that is an urban space in the world have been investigated. According to the results of sections, the criteria for evaluating the completeness of the city-square relationship in today’s conditions are set out in a table. The selected from the Trafalgar Square, Bryant Park and Taksim Square samples consecutively examined in the context of these criteria.

APA, Harvard, Vancouver, ISO, and other styles

22

Mirunalini, K., and Dr Vasantha Kalyani David. "Traffic sign Detection using CNN." International Journal of Engineering and Advanced Technology 10, no. 3 (February 28, 2021): 129–35. http://dx.doi.org/10.35940/ijeat.c2245.0210321.

Full text

Abstract:

Lane Detection and Traffic sign detection are the essential components in ADAS .Although there has been significant quantity of analysis dedicated to the detection of lane detection and sign detection in the past, there is still need robustness in the system. An important challenge in the current algorithm is to cope with the bad weather and illumination. In this paper proposes an improved Hough transform algorithm in order to achieve detection of straight line while for the detection of curved sections, the tracking algorithm is studied. The proposed method uses Hybrid KSVD for removing the noise and Hybrid Lane Detection Algorithm is used for identifying the lanes and CNN based approach is used for the Traffic sign Detection. The proposed method offers better Peak Signal to Noise Ratio (PSNR) and Root Mean Square (RMS) in contrast to the existing methods.

APA, Harvard, Vancouver, ISO, and other styles

23

Xu, Fei, Yao Zhong Shi, and Ke Wang. "Study and Application of Traffic Flow Forecast Based on PSO-WLSSVM." Advanced Materials Research 779-780 (September 2013): 453–56. http://dx.doi.org/10.4028/www.scientific.net/amr.779-780.453.

Full text

Abstract:

With wavelet function introduced to improve least square support vector machine kernel function and the wavelet least square support vector machine (WLSSVM) improved using particle swarm optimization (PSO), PSO-WLSSVM for traffic flow prediction is proposed. PSO-WLSSVM inherits good time and frequency domain distinguishing ability from wavelet transform, and the nonlinear learning performance from LSSVM; PSO is used to conduct global optimum search of super parameters so that the blindness of human selection could be avoid. Thus the accuracy of model predictions is improved. The simulation result shows that the forecasted traffic flow of PSO-WLSSVM are in good agreement with the measured value, and the forecasting precision of PSO-WLSSVM than the traditional LSSVM, thus indicating that the PSO-WLSSVM is feasible and precise and can be well applied to the forecast of traffic flow.

APA, Harvard, Vancouver, ISO, and other styles

24

Ren, Hai Ping, and Jin Ping Li. "Bayes Estimation of Traffic Intensity in M/M/1 Queue under a New Weighted Square Error Loss Function." Advanced Materials Research 485 (February 2012): 490–93. http://dx.doi.org/10.4028/www.scientific.net/amr.485.490.

Full text

Abstract:

Bayesian estimator of the traffic intensity in an M/M/1 queue is derived under a new weighted square error loss function. The Bayes estimators are obtained by using two different priors of the traffic intensity,namely,quasi-prior and beta prior. Finally, a Monte Carelo numerical simulation is used to compare these Bayes estimators with the corresponding maximum likelihood estimators.

APA, Harvard, Vancouver, ISO, and other styles

25

Li, Jiang Bao, Zhen Hong Jia, Xi Zhong Qin, Lei Sheng, and Li Chen. "Research on Combined Prediction Model for Busy Telephone Traffic." Applied Mechanics and Materials 610 (August 2014): 789–96. http://dx.doi.org/10.4028/www.scientific.net/amm.610.789.

Full text

Abstract:

In order to improve the prediction accuracy of busy telephone traffic, this study proposes a busy telephone traffic prediction method that combines wavelet transformation and least square support vector machine (lssvm) model which is optimized by particle swarm optimization (pso) algorithm. Firstly, decompose the pretreatment of busy telephone traffic data with mallat algorithm and get low frequency component and high frequency component. Secondly, reconfigure each component and use pso_lssvm model predict each reconfigured one. Then the busy telephone traffic can be achieved. The experimental results show that the prediction model has higher prediction accuracy and stability.

APA, Harvard, Vancouver, ISO, and other styles

26

Nath, Tushar Deb. "IOT Based Road Traffic Control System for Bangladesh." International Journal of Recent Technology and Engineering 10, no. 1 (May 30, 2021): 60–66. http://dx.doi.org/10.35940/ijrte.e5232.0510121.

Full text

Abstract:

The existing traffic administration policy is not worthy enough to tackle the density of movement in Bangladesh. This study proposes an advanced Internet of Things (IoT) based road traffic administration system to resolve the problem. All the smart lamp posts of road crossings handle four factors, i.e., number of cars, activation time, waiting time, and emergency signal of each lane. This research uses an automatic video processing method to count the number of cars on the road. In order to process the video mask, R-CNN is used, which is a combination of the faster R-CNN that performs object detection (class + bounding box), and Fully Convolutional Network (FCN) results into a pixel border. Modern statistical methods are also used, such as multiple regression analysis, cluster analysis, and factor analysis. For handling emergency traffic situations, a new activation function was proposed and named the RT activation function. Factor analysis with principal component analysis (PCA) allowed in reducing the number of variables from elevens to five. The linear regression explains 90.2% of the variance in the data. This research considers R, R-square, adjusted R-square with 0.950, 0.902, and 0.409, values respectively. The results analysis ensures that the performance of the proposed schema is good enough to apply in the road of Bangladesh.

APA, Harvard, Vancouver, ISO, and other styles

27

Haghighat, Nasser, Mehdi Nouri, Mahrokh G. Shayesteh, and Hashem Kalbkhani. "Variable bit rate video traffic prediction based on kernel least mean square method." IET Image Processing 9, no. 9 (September 1, 2015): 777–94. http://dx.doi.org/10.1049/iet-ipr.2014.1035.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

Tian, Hui, Yingpeng Sang, Hong Shen, and Chunyue Zhou. "Probability-model based network traffic matrix estimation." Computer Science and Information Systems 11, no. 1 (2014): 309–20. http://dx.doi.org/10.2298/csis130212010t.

Full text

Abstract:

Traffic matrix is of great help in many network applications. However, it is very difficult to estimate the traffic matrix for a large-scale network. This is because the estimation problem from limited link measurements is highly underconstrained. We propose a simple probability model for a large-scale practical network. The probability model is then generalized to a general model by including random traffic data. Traffic matrix estimation is then conducted under these two models by two minimization methods. It is shown that the Normalized Root Mean Square Errors of these estimates under our model assumption are very small. For a large-scale network, the traffic matrix estimation methods also perform well. The comparison of two minimization methods shown in the simulation results complies with the analysis.

APA, Harvard, Vancouver, ISO, and other styles

29

Campbell, Craig. "Minor Marks and Modifications: Foot Traffic." TranscUlturAl: A Journal of Translation and Cultural Studies 6, no. 1 (November 3, 2014): 16. http://dx.doi.org/10.21992/t9xw6w.

Full text

Abstract:

This contribution is part of a larger project that explores graffiti and other non-official and often illicit acts of public marking outside of the usual juridicial frameworks. The project focuses on the phenomenology of looking, on the emplaced and embodied act of seeing in the world. This specific bit of writing is a companion piece to a long-term photo project on street art that occurs on the street itself (rather than walls). This project, called "Foot Traffic," is distinguished by a square format and the prominent inclusion of the photographer's feet. This playful use of what is typically read as an unintentional inclusion functions to draw attention to positionally and spectatorship. The feet tie the image of the subject (the graffiti) to the location of the pedestrian spectator.

APA, Harvard, Vancouver, ISO, and other styles

30

Çodur, Muhammed Yasin, and Ahmet Tortum. "An Artificial Neural Network Model for Highway Accident Prediction: A Case Study of Erzurum, Turkey." PROMET - Traffic&Transportation 27, no. 3 (June 28, 2015): 217–25. http://dx.doi.org/10.7307/ptt.v27i3.1551.

Full text

Abstract:

This study presents an accident prediction model of Erzurum’s Highways in Turkey using artificial neural network (ANN) approaches. There are many ANN models for predicting the number of accidents on highways that were developed using 8 years with 7,780 complete accident reports of historical data (2005-2012). The best ANN model was chosen for this task and the model parameters included years, highway sections, section length (km), annual average daily traffic (AADT), the degree of horizontal curvature, the degree of vertical curvature, traffic accidents with heavy vehicles (percentage), and traffic accidents that occurred in summer (percentage). In the ANN model development, the sigmoid activation function was employed with Levenberg-Marquardt algorithm. The performance of the developed ANN model was evaluated by mean square error (MSE), the root mean square error (RMSE), and the coefficient of determination (R2). The model results indicate that the degree of vertical curvature is the most important parameter that affects the number of accidents on highways.

APA, Harvard, Vancouver, ISO, and other styles

31

Wan, Ping, Chaozhong Wu, Yingzi Lin, and Xiaofeng Ma. "Driving Anger States Detection Based on Incremental Association Markov Blanket and Least Square Support Vector Machine." Discrete Dynamics in Nature and Society 2019 (March 26, 2019): 1–17. http://dx.doi.org/10.1155/2019/2745381.

Full text

Abstract:

Driving anger, known as “road rage”, has gradually become a serious traffic psychology issue. Although driving anger identification is solved in some studies, there is still a gap in driving anger grading which is helpful to take different intervening measures for different anger intensity, especially in real traffic environment. The main objectives of this study are: (1) explore a novel driving anger induction method based on various elicitation events, e.g., traffic congestion, vehicles weaving/cutting in line, jaywalking and red light waiting in real traffic environment; (2) apply incremental association Markov blanket (IAMB) algorithm to select typical features related to driving anger states; (3) employ least square support vector machine (LSSVM) to identify different driving anger states based on the selected features. Thirty private car drivers were enrolled to perform field experiments on a busy route selected in Wuhan, China, where drivers’ anger could be induced by the elicitation events within limited time. Meanwhile, three types of data sets including driver physiology, driving behaviors and vehicle motions, were collected by multiple sensors. The results indicate that 13 selected features including skin conductance, relative energy spectrum of β band of electroencephalogram, standard deviation (SD) of pedaling speed of gas pedal, SD of steering wheel angle rate, vehicle speed, SD of speed, SD of forward acceleration and SD of lateral acceleration have significant impact on driving anger states. The IAMB-LSSVM model achieves an accuracy with 82.20% which is 2.03%, 3.15%, 4.34%, 7.84% and 8.36% higher than IAMB using C4.5, NBC, SVM, KNN and BPNN, respectively. The results are beneficial to design driving anger detecting or intervening devices in intelligent human-machine systems.

APA, Harvard, Vancouver, ISO, and other styles

32

Wang, Yanpeng, Leina Zhao, Shuqing Li, Xinyu Wen, and Yang Xiong. "Short Term Traffic Flow Prediction of Urban Road Using Time Varying Filtering Based Empirical Mode Decomposition." Applied Sciences 10, no. 6 (March 17, 2020): 2038. http://dx.doi.org/10.3390/app10062038.

Full text

Abstract:

Short-term traffic flow prediction is important to realize real-time traffic instruction. However, due to the existing strong nonlinearity and non-stationarity in short-term traffic volume data, it is hard to obtain a satisfactory result through the traditional method. To this end, this paper develops an innovative hybrid method based on the time varying filtering based empirical mode decomposition (TVF-EMD) and least square support vector machine (LSSVM). Specifically, TVF-EMD is firstly used to deal with the implied non-stationarity in the original data by decomposing them into several different subseries. Then, the LSSVM models are established for each subseries to capture the linear and nonlinear characteristics embedded in the original data, and the corresponding prediction results are superimposed to obtain the final one. Finally, case studies based on two groups of data measured from an arterial road intersection are employed to evaluate the performance of the proposed method. The experimental results indicate it outperforms the other involved models. For example, compared with the LSSVM model, the average improvements by the proposed method in terms of the indexes of mean absolute error, mean relative percentage error, root mean square error and root mean square relative error are 7.397, 15.832%, 10.707 and 24.471%, respectively.

APA, Harvard, Vancouver, ISO, and other styles

33

Singh, Daljeet, Antonella B. Francavilla, Simona Mancini, and Claudio Guarnaccia. "Application of Machine Learning to Include Honking Effect in Vehicular Traffic Noise Prediction." Applied Sciences 11, no. 13 (June 29, 2021): 6030. http://dx.doi.org/10.3390/app11136030.

Full text

Abstract:

A vehicular road traffic noise prediction methodology based on machine learning techniques has been presented. The road traffic parameters that have been considered are traffic volume, percentage of heavy vehicles, honking occurrences and the equivalent continuous sound pressure level. Leq A method to include the honking effect in the traffic noise prediction has been illustrated. The techniques that have been used for the prediction of traffic noise are decision trees, random forests, generalized linear models and artificial neural networks. The results obtained by using these methods have been compared on the basis of mean square error, correlation coefficient, coefficient of determination and accuracy. It has been observed that honking is an important parameter and contributes to the overall traffic noise, especially in congested Indian road traffic conditions. The effects of honking noise on the human health cannot be ignored and it should be included as a parameter in the future traffic noise prediction models.

APA, Harvard, Vancouver, ISO, and other styles

34

Haviluddin, Haviluddin, and Imam Tahyudin. "Prediction of Daily Network Traffic based on Radial Basis Function Neural Network." IAES International Journal of Artificial Intelligence (IJ-AI) 3, no. 4 (August 20, 2016): 145. http://dx.doi.org/10.11591/ijai.v3.i4.pp145-149.

Full text

Abstract:

This paper presents an approach for predicting daily network traffic using artificial neural networks (ANN), namely radial basis function neural network (RBFNN) method. The data is gained from 21 – 24 June 2013 (192 samples series data) in ICT Unit Universitas Mulawarman, East Kalimantan, Indonesia. The results of measurement are using statistical analysis, e.g. sum of square error (SSE), mean of square error (MSE), mean of percentage error (MPE), mean of absolute percentage error (MAPE), and mean of absolute deviation (MAD). The results show that values are the same, with different goals that have been set are 0.001, 0.002, and 0.003, and spread 200. The smallest MSE value indicates a good method for accuracy. Therefore, the RBFNN model illustrates the proposed best model to predict daily network traffic.

APA, Harvard, Vancouver, ISO, and other styles

35

KRAWCZYK, MAŁGORZATA J., and KRZYSZTOF KUŁAKOWSKI. "COARSE-GRAINED CELLULAR AUTOMATON FOR TRAFFIC SYSTEMS." International Journal of Modern Physics C 24, no. 03 (March 2013): 1350011. http://dx.doi.org/10.1142/s0129183113500113.

Full text

Abstract:

A coarse-grained cellular automaton is proposed to simulate traffic systems. There, cells represent road sections. A cell can be in two states: jammed or passable. Numerical calculations are performed for a piece of square lattice with open boundary conditions, for the same piece with some cells removed and for a map of a small city. The results indicate the presence of a phase transition in the parameter space, between two macroscopic phases: passable and jammed. The results are supplemented by exact calculations of the stationary probabilities of states for the related Kripke structure constructed for the traffic system. There, the symmetry-based reduction of the state space allows to partially reduce the computational limitations of the numerical method.

APA, Harvard, Vancouver, ISO, and other styles

36

ANNUNZIATA, CASCONE, CIRO D'APICE, PICCOLI BENEDETTO, and RARITÀ LUIGI. "OPTIMIZATION OF TRAFFIC ON ROAD NETWORKS." Mathematical Models and Methods in Applied Sciences 17, no. 10 (October 2007): 1587–617. http://dx.doi.org/10.1142/s021820250700239x.

Full text

Abstract:

This paper focuses on the optimization of traffic flow on a road network, modeled by a fluid-dynamic approach. Three cost functionals that measure average velocity, average traveling time, and total flux of cars, are considered. First, such functionals are optimized for two simple networks that consist of a single junction: one with two incoming and one outgoing roads (junctions of 2 × 1 type), and the other with one incoming and two outgoing roads (junctions of 1 × 2 type). The optimization is made with respect to right of way parameters and traffic distribution coefficients, obtaining an explicit solution. Then, through simulations, the traffic behavior for complex networks is studied. The main result is that the local optimization ensures a very good result also for the complete network. This is shown by the case study of Re di Roma Square, a big traffic circle of the urban network of Rome.

APA, Harvard, Vancouver, ISO, and other styles

37

Haviluddin, Haviluddin, and Imam Tahyudin. "Time Series Prediction Using Radial Basis Function Neural Network." International Journal of Electrical and Computer Engineering (IJECE) 5, no. 4 (August 1, 2015): 765. http://dx.doi.org/10.11591/ijece.v5i4.pp765-771.

Full text

Abstract:

This paper presents an approach for predicting daily network traffic using artificial neural networks (ANN), namely radial basis function neural network (RBFNN) method. The data is gained from 21-24 June 2013 (192 samples series data) in ICT Unit of Mulawarman University, East Kalimantan, Indonesia. The results of measurement are using statistical analysis, e.g. sum of square error (SSE), mean of square error (MSE), mean of absolute percentage error (MAPE), and mean of absolute deviation (MAD). The results show that values are the same, with different goals that have been set are 0.001, 0.002, and 0.003, and spread 200. The smallest MSE value indicates a good method for accuracy. Therefore, the RBFNN model illustrates the proposed best model to predict daily network traffic.

APA, Harvard, Vancouver, ISO, and other styles

38

YUNIARTI, NI LUH WIWIN, I. GUSTI AYU MADE SRINADI, and MADE SUSILAWATI. "PEMODELAN ANGKA KEMATIAN KECELAKAAN LALU LINTAS DI KOTA DENPASAR." E-Jurnal Matematika 10, no. 2 (May 24, 2021): 111. http://dx.doi.org/10.24843/mtk.2021.v10.i02.p329.

Full text

Abstract:

Denpasar City is one of the most crowded areas on the island of Bali, this is due to the fast population growth rate. This fast population can cause problems, one of the problem is in the transportation sector. The increase in the volume of transportation can cause traffic congestion which can lead to a high number of traffic accidents, this can lead to death due to traffic accidents in Denpasar City. To determine the factors that influence traffic accident mortality, researchers used Poisson regression analysis. Based on data on traffic accidents in Denpasar City in 2018, the deviance value is smaller than the chi square value. Therefore Poisson regression analysis is sufficient to model traffic accident data in Denpasar City. The Poisson regression model obtained from this research is. Based on the Poisson regression model obtained, the independent variable that contributes significantly and has a high effect on the number of people who die in traffic accidents is the driver factor.

APA, Harvard, Vancouver, ISO, and other styles

39

Hassan, Salwa. "Particle-Bound Polycyclic Aromatic Hydrocarbon in the Atmosphere of Heavy Traffic Areas in Greater Cairo, Egypt: Status, Source, and Human Health Risk Assessment." Atmosphere 9, no. 10 (September 21, 2018): 368. http://dx.doi.org/10.3390/atmos9100368.

Full text

Abstract:

Airborne particulate samples were collected from three main squares (Ramsis, El Giza, and Sphinx) representing heavy traffic areas in Greater Cairo during the period of December 2015–February 2016, and analysed for polycyclic aromatic hydrocarbon (PAHs). The maximum concentrations of particle-bound PAHs were observed at El Giza, while the minimum levels were recorded at Sphinx. The levels of particle-bound PAHs in the square areas of Greater Cairo are higher than those found in many different locations in Egypt and around the world.The distribution of individual particle-bound PAHs as well as PAH categories, depending on the ring number in Ramsis, El Giza, and Sphinx, wasquite similar. This similarity implies similar emission sources of PAHs in the three square areas, with vehicle exhaust emissions being the dominant one. Benzo[b]fluoranthene (BbF), benzo[ghi]perylene (BGP), and indeno[1,2,3-cd]pyrene(IND) were the most abundant PAH compounds. Diagnostic concentration ratios of PAH compounds in the three square locations suggest that both petrogenic and pyrogenic sources emit these compounds. Moreover, they originate mainly from traffic emissions in the study areas. Based on the calculated benzo[a]pyrene equivalent (BaPeq) for the individual particle-bound PAH compounds, health risks associated with the inhalation of these compounds were assessed. Total carcinogenic activity (TCA) for all measured PAHs represented 20.03% (El Giza), 20.40% (Ramsis), and 20.60% (Sphinx) of the total PAH concentrations. Benzo[a]pyrene (BaP) and dibenz[a,h]anthracene (DBA) were the highest contributors to the total health risks; these accounted for 42.72% and 38.50% (El Giza), 41.79% and 39.17% (Ramsis), and 42.92% and 37.78% (Sphinx) of the TCA of all PAH compounds, respectively. These results indicate the importance of BaP and DBA as surrogate compounds for PAHs in the atmosphere of square areas of Greater Cairo.

APA, Harvard, Vancouver, ISO, and other styles

40

Bello, E. I., and C. I. Usifo. "A Study of Urban Traffic Management- A Case Study of Lagos State Traffic Management Authority." Advanced Materials Research 62-64 (February 2009): 599–605. http://dx.doi.org/10.4028/www.scientific.net/amr.62-64.599.

Full text

Abstract:

Lagos state is the commercial and financial capital of Nigeria. It is a coastal city with a population of 12 million and covers 2000 square kilometers. The road network extends over 2700 km with a vehicle density of 740 vehicles per kilometer. It consumes over 85% of petroleum products imported into the country. It has no rail or sea mass transit system and all movements of people and goods are by road. This has created a major traffic Management challenge and government intervention is the establishment of the Lagos State Traffic Management Authority( LASTMA). To understand the structure, strength, and weaknesses of the authority, the enabling law and accident statistics, were obtained from the Authority, the Nigerian Police, and the Federal Road Safety Commission. Questionnaires were administered to drivers unions and the general public. The results were analyzed and it was discovered that conflicts across agencies, corruption and high handedness exist. It was also established that the authority has to a great extent succeeded in improving orderliness on Lagos roads. LASTMA needs to pursue an aggressive public enlightenment to change driver’s behaviors.

APA, Harvard, Vancouver, ISO, and other styles

41

PARK, DONG-CHUL. "LONG-TERM PREDICTION OF ETHERNET TRAFFIC USING MULTISCALE-BILINEAR RECURRENT NEURAL NETWORK WITH ADAPTIVE LEARNING." Journal of Circuits, Systems and Computers 19, no. 01 (February 2010): 155–71. http://dx.doi.org/10.1142/s0218126610005986.

Full text

Abstract:

A prediction scheme for Ethernet traffic data using a Multiscale-Bilinear Recurrent Neural Network with Adaptive Learning (M-BRNN-AL) is proposed and presented in this paper. The proposed predictor integrates an M-BRNN and an AL algorithm. In M-BRNN, the wavelet transform is employed to decompose the original traffic signals into several simple traffic signals. A BRNN is then used to predict each decomposed traffic signal. An AL algorithm is also applied in order to improve the learning process at each resolution level in M-BRNN-AL. Experiments and results on a set of Ethernet network traffic predictions show that the proposed scheme converges faster and archives better prediction performance than the other conventional models such as the Multi-layer Perception Type Neural Network, BRNN, and the original M-BRNN in terms of the normalized mean square error.

APA, Harvard, Vancouver, ISO, and other styles

42

Flores, Geoferleen, Eduardo Jr Piedad, Anzeneth Figueroa, Romari Tumamak, and Nesrah Jane Marie Berdon. "A Sound-based Machine Learning to Predict Traffic Vehicle Density." Recoletos Multidisciplinary Research Journal 9, no. 1 (June 3, 2021): 55–62. http://dx.doi.org/10.32871/rmrj2109.01.05.

Full text

Abstract:

Traffic flow mismanagement is a significant challenge in all countries especially in crowded cities. An alternative solution is to utilize smart technologies to predict traffic flow. In this study, frequency spectrum describing traffic sound characteristics is used as an indicator to predict the next five-minute vehicle density. Sound frequency and vehicle intensity are collected during a thirteen-hour data gathering. The collected sound intensity and frequency are then used to learn three machine-learning models - support vector machine, artificial neural network, and random forest and to predict vehicle intensity. It was found out that the performances of the three models based on root-mean-square-error values are 12.97, 16.01, and 10.67, respectively. These initial and satisfactory results pave a new way to predict traffic flow based on traffic sound characteristics which may serve as a better alternative to conventional features.

APA, Harvard, Vancouver, ISO, and other styles

43

Prihatiningsih, Febriana, Sigit Pancahayani, and Subchan Subchan. "Estimasi Kelajuan dan Volume Kendaraan Berdasarkan Model Makroskopik Arus Lalu Lintas Jalan Tol dengan Metode Extended Kalman Filter." SPECTA Journal of Technology 2, no. 2 (November 27, 2019): 51–60. http://dx.doi.org/10.35718/specta.v2i2.105.

Full text

Abstract:

In this thesis, the analysis of vehicles' determination of speed and volume in the traffic flow will be discussed by approach time. The analyzation of vehicles' speed and volume done by estimated on macroscopic term of traffic flow in the traffic jam with Extended Kalman Filter (EKF) method. The term of macroscopic views with measured the traffic variable by density the flow rate the flow rate of vehicle and also the vehicle speed's average. In the estimating process, forward difference scheme is implemented to the model and error are measured by Root Mean Square Error. The result showed that the estimation the average of the vehicle’s relative speed in a segment decreased when its volume of vehicle is increased and vice versa.

APA, Harvard, Vancouver, ISO, and other styles

44

Shukla, Diwakar, Kapil Verma, and Sharad Gangele. "Least Square based Curve Fitting in Internet Access Traffic Sharing in Two Operator Environment." International Journal of Computer Applications 43, no. 12 (April 30, 2012): 26–32. http://dx.doi.org/10.5120/6157-8553.

Full text

APA, Harvard, Vancouver, ISO, and other styles

45

Karamitsos, Ioannis, and Chris Bowerman. "A Resource Reservation Protocol with Linear Traffic Prediction for OBS Networks." Advances in Optical Technologies 2013 (July 15, 2013): 1–6. http://dx.doi.org/10.1155/2013/425372.

Full text

Abstract:

This paper addresses the issue of providing resource reservation mechanism for OBS networks. We propose a linear prediction mechanism based on least mean square (LMS) method to reduce the burst delay at edge nodes. A reservation method is proposed to increase the reservation probability and to improve the delay reduction performance.

APA, Harvard, Vancouver, ISO, and other styles

46

Shabarek, Abdullah, Steven Chien, and Soubhi Hadri. "Deep Learning Framework for Freeway Speed Prediction in Adverse Weather." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 10 (August 27, 2020): 28–41. http://dx.doi.org/10.1177/0361198120947421.

Full text

Abstract:

The introduction of deep learning (DL) models and data analysis may significantly elevate the performance of traffic speed prediction. Adverse weather causes mobility and safety concerns because of varying traffic speeds with poor visibility and road conditions. Most previous modeling approaches have not considered the heterogeneity of temporal and spatial data, such as traffic and weather conditions. This paper presents a framework, consisting of two DL models, to predict traffic speed under normal conditions and during adverse weather, considering prevailing traffic speed, wind speed, traffic volume, road capacity, wind bearing, precipitation intensity, and visibility. To ensure the accuracy of speed prediction, different DL models were assessed. The results indicated that the proposed one-dimensional convolutional neural network model outperformed others in relation to the least root mean square error and the least mean absolute error. Considering real-time weather data feeds on a 15-min basis, a tool was also developed for displaying predicted traffic speeds on New Jersey freeways. Application of the proposed framework models for predicting spatio-temporal hot-spot congestion caused by adverse weather is discussed.

APA, Harvard, Vancouver, ISO, and other styles

47

Yang, Lei, and Wei Dong Dai. "An Approach for Short Term Traffic Flow Forecasting Based on Genetic Neural Network." Advanced Materials Research 671-674 (March 2013): 2866–69. http://dx.doi.org/10.4028/www.scientific.net/amr.671-674.2866.

Full text

Abstract:

In this paper, genetic neural network is applied to forecast the short-term traffic flow and traffic guidance. Because of the factors of time correlation and spatial correlation, we construct the short-term traffic flow forecasting model using back-propagation neural network that has the function of arbitrary nonlinear function approximation. In order to find proper initial values of the neural network weights and threshold quickly, a combination of neural network prediction method is presented. This method utilizes genetic algorithm to choose the initial weights and threshold, and uses L-M algorithm to train sample, which can enhance the global convergence rate. Trained network is used for short-term traffic flow prediction with mean square error as the forecast performance evaluation. The results show that the performance of genetic neural network is better than a separate BP neural network for short-term traffic flow prediction.

APA, Harvard, Vancouver, ISO, and other styles

48

Zhang, Chunbo, Zhaoguo Huang, and Yonggang Wang. "A TRAFFIC FUNDAMENTAL DIAGRAM CALIBRATING METHODOLOGY TO AVOID UNBALANCED SPEED–DENSITY OBSERVATIONS." Transport 36, no. 1 (February 24, 2021): 13–24. http://dx.doi.org/10.3846/transport.2021.14302.

Full text

Abstract:

Traffic fundamental diagram is extremely important to analyse traffic flow and traffic capacity, and the central part of traffic fundamental diagram is to calibrate speed–density relationship. However, because of unbalanced speed–density observations, calibrating results using Least Square Method (LSM) with all speed–density points always lead to inaccurate effect, so this paper proposed a selecting data sample method and then LSM was used to calibrate four well-known single-regime models. Comparisons were made among the results using LSM with all speed–density points and the selecting data sample. Results indicated that the selecting data sample method proposed by this paper can calibrate the singleregime models well, and the method overcomes the inaccurate effect caused by unbalanced speed–density observations. Data from different highways validated the results. The contribution of this paper is that the proposed method can help researchers to determine more precise traffic fundamental diagram.

APA, Harvard, Vancouver, ISO, and other styles

49

Kababulut, Fevzi Yasin, Damla Kuntalp, Olcay Akay, and Timur Düzenli. "Simple and Efficient Prediction of Near Future State of Traffic Using Only Past Speed Information." PROMET - Traffic&Transportation 30, no. 5 (November 9, 2018): 589–99. http://dx.doi.org/10.7307/ptt.v30i5.2757.

Full text

Abstract:

Intelligent traffic systems attempt to solve the problem of traffic congestion, which is one of the most important environmental and economic issues of urban life. In this study, we approach this problem via prediction of traffic status using past average traveler speed (ATS). Five different algorithms are proposed for predicting the traffic status. They are applied to real data provided by the Traffic Control Center of Istanbul Metropolitan Municipality. Algorithm 1 predicts future ATS on a highway section based on the past speed information obtained from the same road section. The other proposed algorithms, Algorithms 2 through 5, predict the traffic status as fluent, moderately congested, or congested, again using past traffic state information for the same road segment. Here, traffic states are assigned according to predetermined intervals of ATS values. In the proposed algorithms, ATS values belonging to past five consecutive 10-minute time intervals are used as input data. Performances of the proposed algorithms are evaluated in terms of root mean square error (RMSE), sample accuracy, balanced accuracy, and processing time. Although the proposed algorithms are relatively simple and require only past speed values, they provide fairly reliable results with noticeably low prediction errors.

APA, Harvard, Vancouver, ISO, and other styles

50

Cartenì, Armando, Maria Luisa De Guglielmo, and Nicola Pascale. "Congested Urban Areas with High Interactions Between Vehicular and Pedestrian Flows: A Cost-Benefit Analysis for a Sustainable Transport Policy in Naples, Italy." Open Transportation Journal 12, no. 1 (September 28, 2018): 273–88. http://dx.doi.org/10.2174/1874447801812010273.

Full text

Abstract:

Introduction/Methods:A significant application of the Sustainable Urban Mobility Plan of Naples, in southern Italy, will be described with specific reference to design a sustainable transport scenario for one of the highest density and congested area of the city: Municipio square, in the centre of Naples, where the homonymous station of the Metro Line 1 was under construction. The particularity of this case study is that Municipio Square is a high dense population area characterized by multimodal traffic flows (vehicles and pedestrians) and a thousand of travellers who embark/disembark every day from the marina to the islands of the Naples Gulf (e.g.Capri, Ischia) and cruises around the Mediterranean Sea. Thousands of vehicles and people pass through the square every day, often slowing the vehicular flows.Starting from these considerations, a multi-scale modelling architecture (estimatedad-hocfor the specific case study) was proposed to better evaluate policy impacts (e.g., transport, social, environmental), applying both macroscopic and microscopic simulation models simultaneously to design a sustainable transport scenario in term of both geometrical and traffic solutions.Results:Six different design scenario were compared and the main results of the most significant one are described and discussed. The best project solution reduces the average travel time and the long queues thanks to a better distribution of the flows (both vehicles and pedestrians) in the broader area around of Municipio square. The simulation results also underlined the benefits for pedestrians related to the presence of different size of sidewalks and paths.Conclusion:Because of the realization of the new metro station will increase the pedestrian flows, the external layout of the square was designed, regarding infrastructures and paths, to minimize the conflicts and reduce the overall travel time. The proposed sustainable transport scenario was conceived in term of best geometrical devices and traffic solutions.Finally, a cost-benefit analysis was also proposed, according to the European guidelines, aiming in improving transport, urbanistic, artistic/cultural, aesthetic, economic and environmental aspects as well as liveability for citizens, transport users (public and private) and tourists.

APA, Harvard, Vancouver, ISO, and other styles

Journal articles on the topic 'The traffic square'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles