The Experts below are selected from a list of 146655 Experts worldwide ranked by ideXlab platform
Tarek Sayed - One of the best experts on this subject based on the ideXlab platform.
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evaluating the impact of bike network indicators on cyclist safety using Macro Level collision prediction models
Accident Analysis & Prevention, 2016Co-Authors: Ahmed Osama, Tarek SayedAbstract:Abstract Many cities worldwide are recognizing the important role that cycling plays in creating green and livable communities. However, vulnerable road users such as cyclists are usually subjected to an elevated Level of injury risk which discourages many road users to cycle. This paper studies cyclist-vehicle collisions at 134 traffic analysis zones in the city of Vancouver to assess the impact of bike network structure on cyclist safety. Several network indicators were developed using Graph theory and their effect on cyclist safety was investigated. The indicators included measures of connectivity, directness, and topography of the bike network. The study developed several Macro-Level (zonal) collision prediction models that explicitly incorporated bike network indicators as explanatory variables. As well, the models incorporated the actual cyclist exposure (bike kilometers travelled) as opposed to relying on proxies such as population or bike network length. The Macro-Level collision prediction models were developed using generalized linear regression and full Bayesian techniques, with and without spatial effects. The models showed that cyclist collisions were positively associated with bike and vehicle exposure. The exponents of the exposure variables were less than one which supports the “safety in numbers” hypothesis. Moreover, the models showed positive associations between cyclist collisions and the bike network connectivity and linearity indicators. In contrast, negative associations were found between cyclist collisions and the bike network continuity and topography indicators. The spatial effects were statistically significant in all of the developed models.
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Macro-Level collision prediction models for evaluating neighbourhood traffic safety
Canadian Journal of Civil Engineering, 2006Co-Authors: Gordon Lovegrove, Tarek SayedAbstract:This study describes the development of Macro-Level (i.e., neighbourhood or traffic zone Level) collision prediction models using data from 577 neighbourhoods across the Greater Vancouver Regional District. The objective is to provide a safety planning decision-support tool that facilitates a proactive approach to community planning which addresses road safety before problems emerge. The models are developed using the generalized linear regression modelling (GLM) technique assuming a negative binomial error structure. The resulting models relate traffic collisions to neighbourhood characteristics such as traffic volume, demographics, network shape, and transportation demand management. Several models are presented for total or severe collisions in rural or urban zones using measured and (or) modelled data. It is hoped that quantifying a predictive traffic safety - neighbourhood planning relationship will facilitate improved decisions by community planners and engineers and, ultimately, facilitate improved neighbourhood traffic safety for residents and other road users. Language: en
Patricia M. Dardati - One of the best experts on this subject based on the ideXlab platform.
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A simple procedure to evaluate Cauchy stress tensor at the Macro Level based on computational micromechanics under general finite strain states
Mechanics of Materials, 2018Co-Authors: Néstor Darío Barulich, Luis A. Godoy, Patricia M. DardatiAbstract:Abstract This paper presents a new methodology to evaluate the Cauchy stress tensor at the Macro Level in computational micromechanics models. The use of control nodes to specify boundary conditions of a Representative Volume Element (RVE) allows deriving equations for the Cauchy stress components, with the consequence that numerical integration in the RVE is not performed. The proposed method allows use of computational micromechanics in commercial Finite Element software for a RVE subjected to general infinitesimal or finite strains. Because this methodology is obtained from the equivalence of power in the microscopic and Macroscopic scales (Hill–Mandel principle) in a quasi-static problem, it is capable of dealing with micro-constituents under several constitutive laws. Numerical examples presented include simulations of elastic, hyper-elastic, and elasto-plastic fiber composite materials and a honeycomb microstructure. The present methodology can be used in multi-scale models to analyze non-linear structures made of heterogeneous materials.
Gordon Lovegrove - One of the best experts on this subject based on the ideXlab platform.
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an empirical tool to evaluate the safety of cyclists community based Macro Level collision prediction models using negative binomial regression
Accident Analysis & Prevention, 2013Co-Authors: Gordon LovegroveAbstract:Today, North American governments are more willing to consider compact neighborhoods with increased use of sustainable transportation modes. Bicycling, one of the most effective modes for short trips with distances less than 5km is being encouraged. However, as vulnerable road users (VRUs), cyclists are more likely to be injured when involved in collisions. In order to create a safe road environment for them, evaluating cyclists' road safety at a Macro Level in a proactive way is necessary. In this paper, different generalized linear regression methods for collision prediction model (CPM) development are reviewed and previous studies on micro-Level and Macro-Level bicycle-related CPMs are summarized. On the basis of insights gained in the exploration stage, this paper also reports on efforts to develop negative binomial models for bicycle-auto collisions at a community-based, Macro-Level. Data came from the Central Okanagan Regional District (CORD), of British Columbia, Canada. The model results revealed two types of statistical associations between collisions and each explanatory variable: (1) An increase in bicycle-auto collisions is associated with an increase in total lane kilometers (TLKM), bicycle lane kilometers (BLKM), bus stops (BS), traffic signals (SIG), intersection density (INTD), and arterial-local intersection percentage (IALP). (2) A decrease in bicycle collisions was found to be associated with an increase in the number of drive commuters (DRIVE), and in the percentage of drive commuters (DRP). These results support our hypothesis that in North America, with its current low Levels of bicycle use ( Language: en
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Macro-Level collision prediction models for evaluating neighbourhood traffic safety
Canadian Journal of Civil Engineering, 2006Co-Authors: Gordon Lovegrove, Tarek SayedAbstract:This study describes the development of Macro-Level (i.e., neighbourhood or traffic zone Level) collision prediction models using data from 577 neighbourhoods across the Greater Vancouver Regional District. The objective is to provide a safety planning decision-support tool that facilitates a proactive approach to community planning which addresses road safety before problems emerge. The models are developed using the generalized linear regression modelling (GLM) technique assuming a negative binomial error structure. The resulting models relate traffic collisions to neighbourhood characteristics such as traffic volume, demographics, network shape, and transportation demand management. Several models are presented for total or severe collisions in rural or urban zones using measured and (or) modelled data. It is hoped that quantifying a predictive traffic safety - neighbourhood planning relationship will facilitate improved decisions by community planners and engineers and, ultimately, facilitate improved neighbourhood traffic safety for residents and other road users. Language: en
Xuesong Wang - One of the best experts on this subject based on the ideXlab platform.
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Macro Level safety analysis of pedestrian crashes in shanghai china
Accident Analysis & Prevention, 2016Co-Authors: Xuesong Wang, Junguang Yang, Chris Lee, Shikai YouAbstract:Pedestrian safety has become one of the most important issues in the field of traffic safety. This study aims at investigating the association between pedestrian crash frequency and various predictor variables including roadway, socio-economic, and land-use features. The relationships were modeled using the data from 263 Traffic Analysis Zones (TAZs) within the urban area of Shanghai - the largest city in China. Since spatial correlation exists among the zonal-Level data, Bayesian Conditional Autoregressive (CAR) models with seven different spatial weight features (i.e. (a) 0-1 first order, adjacency-based, (b) common boundary-length-based, (c) geometric centroid-distance-based, (d) crash-weighted centroid-distance-based, (e) land use type, adjacency-based, (f) land use intensity, adjacency-based, and (g) geometric centroid-distance-order) were developed to characterize the spatial correlations among TAZs. Model results indicated that the geometric centroid-distance-order spatial weight feature, which was introduced in Macro-Level safety analysis for the first time, outperformed all the other spatial weight features. Population was used as the surrogate for pedestrian exposure, and had a positive effect on pedestrian crashes. Other significant factors included length of major arterials, length of minor arterials, road density, average intersection spacing, percentage of 3-legged intersections, and area of TAZ. Pedestrian crashes were higher in TAZs with medium land use intensity than in TAZs with low and high land use intensity. Thus, higher priority should be given to TAZs with medium land use intensity to improve pedestrian safety. Overall, these findings can help transportation planners and managers understand the characteristics of pedestrian crashes and improve pedestrian safety.
Néstor Darío Barulich - One of the best experts on this subject based on the ideXlab platform.
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A simple procedure to evaluate Cauchy stress tensor at the Macro Level based on computational micromechanics under general finite strain states
Mechanics of Materials, 2018Co-Authors: Néstor Darío Barulich, Luis A. Godoy, Patricia M. DardatiAbstract:Abstract This paper presents a new methodology to evaluate the Cauchy stress tensor at the Macro Level in computational micromechanics models. The use of control nodes to specify boundary conditions of a Representative Volume Element (RVE) allows deriving equations for the Cauchy stress components, with the consequence that numerical integration in the RVE is not performed. The proposed method allows use of computational micromechanics in commercial Finite Element software for a RVE subjected to general infinitesimal or finite strains. Because this methodology is obtained from the equivalence of power in the microscopic and Macroscopic scales (Hill–Mandel principle) in a quasi-static problem, it is capable of dealing with micro-constituents under several constitutive laws. Numerical examples presented include simulations of elastic, hyper-elastic, and elasto-plastic fiber composite materials and a honeycomb microstructure. The present methodology can be used in multi-scale models to analyze non-linear structures made of heterogeneous materials.
