Highway Capacity Manual改訂の動向--テイラ-教授の講演より

In this Chapter, we imagine a decision maker (or a group of experts) trying to establish or examine fair procedures to combine opinions about alternatives related to different points of view.

Multiple criteria decision making

Understanding railway operational accidents using network theory

Walking outdoors can be used by many individuals to meet public health guidelines for moderate-to-vigorous-intensity physical activity. The speed at which adults walk may be a proxy for intensity. Traditional estimates of indoor walking speed are unlikely to reflect self-selected usual or other instructed paces of outdoor walking speed. To inform estimates of pace-based walking speed of apparently healthy adults in outdoor settings. We searched four electronic databases for articles published in English between January 1970 and March 2019. Studies that reported walking speed (m/s), cadence (steps/min), or intensity (mL/kg/min) of ambulatory, apparently healthy, and community-dwelling adults (> 18 years) were included. Walking speed categories were defined according to the description provided in each study. Meta-analysis was used to synthesise speed, cadence, and intensity data by slow, usual, medium, fast, and maximal pace (where reported). Thirty-five studies, representing 14,015 participants (6808 women, 5135 men, and 2072 sex not specified), were identified. The mean (95% CI) walking speed for slow, usual, medium, fast, and maximal pace was 0.82 (0.77–0.86), 1.31 (1.27–1.35), 1.47 (1.44–1.49), 1.72 (1.64–1.81), and 1.62 (1.45–1.79) m/s, respectively. Mean cadence (95% CI) for usual and fast paces were 116.65 (114.95–118.35) and 126.75 (121.87–131.63) steps/min, respectively. The mean oxygen consumption (95% CI) for the usual and medium paces was 11.97 (11.69–12.25) and 13.34 (12.94–13.73) mL/kg/min, respectively. These findings provide greater clarity with regard to how various indicators of enacted walking pace, speed, and intensity overlap and how each can be best communicated in the real-world setting to optimise health-related outcomes. Pace-based instructions can be used to support walking in outdoor settings within public health guidelines.

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Outdoor Walking Speeds of Apparently Healthy Adults: A Systematic Review and Meta-analysis

제93회 Transportation Research Board Annual Meeting 참관기

Delay is one of the primary variables of efficiency of intersections and roundabouts. There are not extensive experiences about delay in roundabouts in comparison with delay at intersections, and there haven’t been many studies in Iran particularly about un-signalized roundabouts. The main goal in traffic designs is to have a safe and efficient flow. In order to achieve this goal, a video has been prepared about traffic conditions of three un-signalized roundabouts in Rasht. Data related to geometric designs such as nearside legs width, turning width, far-side legs width and central roundabout diameter were measured by field observation. Data related to traffic volume such as nearside legs volume, turning volume and far-side legs volume were observed by already prepared videos. Eventually, analyses about right turning movements at un-signalized roundabouts were carried out by linear and nonlinear regression models. The best delay model of direct movements has linear relation, and left turning and direct movements has logarithmic linear relation. Because of many variables and the high accuracy of neural network, it was decided to model the data using this method, and the authors obtained the best model for the prediction of un-signalized roundabouts’ delay.

http://www.crpase.com/archive/CRPASE-2016-VOL 02-ISSUE 01-06.pdf

Delay Modeling of Un-signalized Roundabouts Using Neural Network and Regression

Accurate and computationally efficient means of classifying electrocardiography arrhythmias has been the subject of considerable research effort in recent years. This paper presents a hybrid method for automated diagnostic systems of electrocardiography arrhythmias. The proposed method includes three main modules including the denoising module, the classifier module and the optimization module. In the denoising module, the stationary wavelet transform is proposed for noise reduction of the electrocardiogram signals. In the classifier module, the adaptive neuro-fuzzy inference system is investigated. In adaptive neuro-fuzzy inference system (ANFIS) training, the vector of radius has an important role for its recognition accuracy. Furthermore, in the optimization module, the cuckoo optimization algorithm is proposed for finding optimum vector of radius. In the test stage, 3-fold cross validation method has been applied to the MIT-BIH arrhythmia database for evaluating the capability of the proposed method. The simulation results show that the proposed method has high recognition accuracy.

http://www.crpase.com/archive/CRPASE-2015-VOL 01-ISSUE 04-06.pdf

Timing Optimization of Signalized Intersections Using Shockwave Theory by Genetic Algorithm

Travels within the city are done in different ways, by vehicle or on foot. Thus, inevitably, a part of the travel is always done on foot. Since intersections as traffic nodes are determinant factor in transportation network capacity, any disruption in them leads to severe reduction in network capacity. Unfortunately, pedestrian behavior has received little attention in Iran. While this is a very important and effective part of traffic engineering. In some cases, pedestrians are the main cause of increasing road users’ delay, therefore, the most important action before anything, is identifying the characteristics of pedestrians. Identifying issues such as speed, volume and density of pedestrians are necessary to control the traffic flow and delay, and can lead to better design of facilities associated with pedestrians. Cases that are studied in this study are: the relationship between speed, density and pedestrians’ flow rate while crossing the street. In this study, the data was collected by filming four intersections in Rasht Metropolis for 15 hours, and the number of pedestrians crossing that were studied was 8489. Two intersections had traffic lights and the other ones had no traffic lights. Then, the relationship between speed, density and volume of pedestrians were obtained by determining the variables of speed, density and volume of pedestrians and using linear and nonlinear regression method and finding the correlation coefficient between the variables. The results showed that for pedestrians, there is a relationship between the flow rate and density with a high correlation coefficient in crossing through crosswalk (R2=0.99) and outside the crosswalk (R2=0.99). But the relationship between speed and flow rate was not significant (crossing through crosswalk, R2=0.29 and outside the crosswalk, R2=0.24); furthermore, speed and density had no significant relationship (crossing through crosswalk, R2=0.36 and outside the crosswalk, R2=0.28).

https://www.ije.ir/article_73070_1e3a573ad76fc3f65b3548a254bec3f0.pdf

Relationship between Pedestrians’ Speed, Density and Flow Rate of Crossings through Urban Intersections (Case Study: Rasht Metropolis) (RESEARCH NOTE)

The purpose of this study is to investigate and determine the factors affecting vehicle and pedestrian accidents taking place in the busiest suburban highway of Guilan Province located in the north of Iran and provide the most accurate prediction model. Therefore, the effective principal variables and the probability of occurrence of each category of crashes are analyzed and computed utilizing the factor analysis, logit, and Machine Learning approaches simultaneously. This method not only could contribute to achieving the most comprehensive and efficient model to specify the major contributing factor, but also it can provide officials with suggestions to take effective measures with higher precision to lessen accident impacts and improve road safety. Both the factor analysis and logit model show the significant roles of exceeding lawful speed, rainy weather and driver age (30–50) variables in the severity of vehicle accidents. On the other hand, the rainy weather and lighting condition variables as the most contributing factors in pedestrian accidents severity, underline the dominant role of environmental factors in the severity of all vehicle-pedestrian accidents. Moreover, considering both utilized methods, the machine-learning model has higher predictive power in all cases, especially in pedestrian accidents, with 41.6% increase in the predictive power of fatal accidents and 12.4% in whole accidents. Thus, the Artificial Neural Network model is chosen as the superior approach in predicting the number and severity of crashes. Besides, the good performance and validation of the machine learning is proved through performance and sensitivity analysis.

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Prediction and Analysis of the Severity and Number of Suburban Accidents Using Logit Model, Factor Analysis and Machine Learning: A case study in a developing country

https://cyberleninka.org/article/n/715488.pdf

Iraj Bargegol

Papers

Delay Modeling of Un-signalized Roundabouts Using Neural Network and Regression

Timing Optimization of Signalized Intersections Using Shockwave Theory by Genetic Algorithm

Relationship between Pedestrians’ Speed, Density and Flow Rate of Crossings through Urban Intersections (Case Study: Rasht Metropolis) (RESEARCH NOTE)

Prediction and Analysis of the Severity and Number of Suburban Accidents Using Logit Model, Factor Analysis and Machine Learning: A case study in a developing country

Estimation the Saturation Flow Rate at Far-side and Nearside Legs of Signalized Intersections – Case Study: Rasht City☆