Application of artificial neural networks for operating speed prediction at horizontal curves: a case study in Egypt

Semeida, Ahmed Mohamed

doi:10.1007/s40534-014-0033-3

Cited by 17 publications

(11 citation statements)

References 10 publications

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“…The architecture of the ANN model is shown in Figure 2. The use of the learning rule of momentum and the suitable number of iterations = 5000, is appropriate for quick convergence of the problem, as shown by Semeida [19] and [20]. In the present study, many trials have been made to reach the percentage between the training and testing data that gives the best model performance.…”

Section: Ann Model Resultsmentioning

confidence: 96%

Utjecaj stanja višetračnih kolnika na promet osobnih vozila

Lakušić¹

2016

JCE

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Impact of pavement condition on passenger car trafficThe present paper explores the influence of pavement condition, roughness, and longitudinal grade on the operating speed (V 85 ) of passenger car traffic at multi-lane roads. The pavement condition is described as a pavement condition index, while pavement roughness is expressed as an international roughness index. The necessary data are collected at 67 tangent sections and the following three modelling approaches are adopted for analysis: linear regression, multiple regression analysis, and artificial neural network. The obtained results show that the artificial neural network modelling approach is the best one for estimating the operating speed V 85 in terms of main statistical parameters. Utjecaj stanja višetračnih kolnika na promet osobnih vozila U ovom radu istražen je utjecaj stanja kolnika, ravnosti kolnika i uzdužnog nagiba na iznos operativne brzine osobnih vozila (V 85 ) na višetračnim cestama. Stanje kolnika opisano je pomoću indeksa stanja kolnika, dok je ravnost kolnika opisana međunarodnim indeksom ravnosti. Podaci za ispitivanje prikupljeni su na 67 dionica ceste u pravcu, a u analizi tih dionica primijenjena su tri različita postupka modeliranja: linearna regresija, generalizirano linearno modeliranje te umjetna neuronska mreža. Rezultati istraživanja su pokazali da je primjena umjetne neuronske mreže najbolja za procjenu operativne brzine V 85 s obzirom na glavne statističke parametre.

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Section: Ann Model Resultsmentioning

confidence: 96%

Utjecaj stanja višetračnih kolnika na promet osobnih vozila

Lakušić¹

2016

JCE

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“…Using of learning rule of (momentum) and the suitable number of epochs (iterations) is 5000. The previous conditions are suitable for quick convergence of the problem as executed by Semeida [13,22,23]. So many trials are done to reach the percentage between training and testing data which gives the best model performance in the present case of research.…”

Section: Analysis and Results Of Anns Proceduresmentioning

confidence: 99%

“…When a satisfactory level of performance is reached the training is ended and the network uses these weights to make a decision (Singh et al, 2011) [21]. The experience in this field is extracted from Semeida [13,22,23]. In his researches, the multi-layer perceptron (MLP) neural network models give the best performance of all models.…”

Section: Anns Proceduresmentioning

confidence: 99%

Derivation of level of service by artificial neural networks at horizontal curves: a case study in Egypt

Semeida

2015

Eur. Transp. Res. Rev.

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Purpose Multi-lane highways represent the majority of the total length of highway network at many countries. The geometric design of such facilities and the traffic volume which includes heavy vehicles percentage (HV) are considered the most important factors affecting the level of service (LOS), especially on the horizontal curves. Methods This paper aims to explore the relationship between the road geometric characteristics including horizontal curve properties and traffic volume including average annual daily traffic (AADT) and HV in one hand and LOS in the other hand by two methods. First is generalized linear modeling (GLM) procedure and second is the artificial neural networks (ANNs) procedure. In this research, the traffic and road geometric data are collected on 78 horizontal curves that are distributed on four multi-lane highways in Egypt. Two of them are located in desert area and the others in agricultural area.

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“…This model also presented the clear explanation for the restriction factors to improve the accuracy of prediction. Moreover, artificial neural network and simulation technique were introduced to estimate operating speed [26,27].…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach for Operating Speed Continuous Predication Based on Alignment Space Comprehensive Index

Yan

Tang

et al. 2017

Journal of Advanced Transportation

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Operating speed is a critical indicator for road alignment consistency design and safety evaluation. Although extensive studies have been conducted on operating speed prediction, few models can finish practical continuous prediction at each point along alignment on multilane highways. This study proposes a novel method to estimate the operating speed for multilane highways in China from the aspect of the three-dimensional alignment combination. Operating speed data collected in field experiments on 304 different alignment combination sections are detected by means of Global Positioning System. First, the alignment comprehensive index (ACI) is designed and introduced to describe the function accounting for alignment continuity and driving safety. The variables used in ACI include horizontal curve radius, change rate of curvature, deflection angle of curve, grade, and lane width. Second, the influence range of front and rear alignment on speed is determined on the basis of drivers' fixation range and dynamical properties of vehicles. Furthermore, a prediction model based on exponential relationships between road alignment and speeds is designed to predict the speed of passenger cars and trucks. Finally, three common criteria are utilized to evaluate the effectiveness of the prediction models. The results indicate that the prediction models outperform the other two operating speed models for their higher prediction accuracy.

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Application of artificial neural networks for operating speed prediction at horizontal curves: a case study in Egypt

Cited by 17 publications

References 10 publications

Utjecaj stanja višetračnih kolnika na promet osobnih vozila

Utjecaj stanja višetračnih kolnika na promet osobnih vozila

Derivation of level of service by artificial neural networks at horizontal curves: a case study in Egypt

A Novel Approach for Operating Speed Continuous Predication Based on Alignment Space Comprehensive Index

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