scholarly journals A Study on Urban Road Traffic Safety Based on Matter Element Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Qizhou Hu ◽  
Zhuping Zhou ◽  
Xu Sun
Keyword(s):  
Traffic Safety ◽  
Road Traffic ◽  
Evaluation Model ◽  
Computational Procedure ◽  
Element Analysis ◽  
Urban Road ◽  
Road Traffic Safety ◽  
Analysis Theory ◽  
Matter Element Analysis ◽  
Element Matrix

This paper examines a new evaluation of urban road traffic safety based on a matter element analysis, avoiding the difficulties found in other traffic safety evaluations. The issue of urban road traffic safety has been investigated through the matter element analysis theory. The chief aim of the present work is to investigate the features of urban road traffic safety. Emphasis was placed on the construction of a criterion function by which traffic safety achieved a hierarchical system of objectives to be evaluated. The matter element analysis theory was used to create the comprehensive appraisal model of urban road traffic safety. The technique was used to employ a newly developed and versatile matter element analysis algorithm. The matter element matrix solves the uncertainty and incompatibility of the evaluated factors used to assess urban road traffic safety. The application results showed the superiority of the evaluation model and a didactic example was included to illustrate the computational procedure.

Assessment of Urban Road Traffic Safety Based on Bayes Discriminant Analysis Method

2013 ◽  
Vol 639-640 ◽  
pp. 544-547
Author(s):  
Chang Ping Wen ◽  
Qing Qing Tian
Keyword(s):  
Discriminant Analysis ◽  
Traffic Safety ◽  
Evaluation Method ◽  
Road Traffic ◽  
Urban Road ◽  
Discriminant Model ◽  
Road Traffic Safety ◽  
Normal Populations ◽  
Proposed Model ◽  
Bayes Discriminant Analysis

Bayes discriminant analysis theory (BDAT) is used to create an evaluation method to determine the condition of urban road traffic safety. The resulting Bayes discriminant model (BDM) is designed to strictly adhere to BDAT. Three indexes including death ratio per ten thousand vehicles, death ratio per hundred thousand bicycles and death ratio per hundred thousand citizens are selected as the factors in the analysis of urban road traffic safety. The grade of condition of urban road traffic safety is divided into three grades that are regarded as three normal populations in Bayes discriminant analysis. Bayes discriminant functions rigorously constructed through training a set of samples are employed to compute the Bayes function values of the evaluating samples, and the maximal function value is used to judge which population the evaluating sample belongs to. The optimality of the proposed model is verified by back-substitution method. The study shows that the prediction accuracy of the proposed model is 100% and could be used in practice.

Disassembly Analysis Based on Entropy and Extension Theory

2012 ◽  
Vol 569 ◽  
pp. 472-476
Author(s):  
Na Zhao ◽  
Rui Mu ◽  
Wei Huang ◽  
Wen Guang Lin
Keyword(s):  
Product Design ◽  
Evaluation Model ◽  
Evaluation Process ◽  
Extension Theory ◽  
Weight Matrix ◽  
Element Analysis ◽  
Matter Element Analysis ◽  
Element Matrix ◽  
Index Weight

In view of the fuzziness and uncertainty characteristics of the index and evaluation incompatibility in the disassembly evaluation process, the disassembly evaluation model of fuzzy matter-element analysis based on entropy was proposed. Firstly, the fuzzy matter-element matrix and weight matrix was established, based on the analysis of the factors having influences on disassemblability. Then the dependent degree of each scheme was calculated to rank disassemblability of the product design schemes. Additionally, the index weight was determined by the method of entropy, which can effectively avoid interference of subjective factors in the process of weight determination. Finally, an example of disassemblability evaluation was given to show the effectiveness of the method.

scholarly journals A Cask Evaluation Model to Assess Safety in Chinese Rural Roads

2018 ◽  
Vol 10 (11) ◽  
pp. 3864 ◽  
Author(s):  
Longyu Shi ◽  
Nigar Huseynova ◽  
Bin Yang ◽  
Chunming Li ◽  
Lijie Gao
Keyword(s):  
Traffic Safety ◽  
Traffic Accident ◽  
Road Traffic ◽  
Evaluation Model ◽  
Impact Factors ◽  
Rural Roads ◽  
Traffic Signs ◽  
Road Traffic Safety ◽  
Rural Road ◽  
Space Data

Suburban roads are an important part of China’s road network and essential infrastructure for rural development. Poorly designed road curves and scarcity of traffic signs have caused an excessively high traffic accident rate in plain topographical areas. In this study, an approach to evaluate and improve rural road traffic safety is introduced. Based on fuzzy and cask theory and weighted analysis, a cask evaluation model is built. It provides a quantitative instant method for analyzing road safety in the absence of traffic accident information or rigorous road space data, by identifying dangerous sections and key impact factors, and ultimately help to put forward traffic safety improvements. Based on the application to a specific section of Xiaodang Central Road in the Fengxian District of Shanghai, the result shows that the pavement conditions of cement-hardened dual-lane rural roads was good, but traffic safety was poor. Missing traffic signs, unreasonable road alignment, and poor roadside conditions were the main problems. Finally, improvements of the short-stave subsystem were proposed: the location of guide signs and roadside conditions should be improved, and the number and efficacy of the rural road traffic signs need to be increased, and markings should be and receive regular maintenance.

scholarly journals Highway safety influencing factors in cold regions based on attribute recognition theory

2018 ◽  
Vol 10 (12) ◽  
pp. 168781401881833
Author(s):  
Xue-jing Du ◽  
Yu-long Pei ◽  
Zhan-yu Wang ◽  
Zhan-li Chen ◽  
Hua-chen Zhou
Keyword(s):  
Influencing Factors ◽  
Traffic Safety ◽  
Road Traffic ◽  
Evaluation Model ◽  
Indicator System ◽  
Highway Traffic ◽  
Cold Regions ◽  
Road Traffic Safety ◽  
Recognition Theory ◽  
Attribute Recognition

To study the problem of highway traffic safety in cold regions, a thorough statistical analysis using traffic accident historical data is used to evaluate the influencing factors on highway traffic safety. A road traffic safety indicator system for cold regions is developed to evaluate the weight of these influence factors, such as driver performance, vehicle capacity, road condition, and general impact of the traffic environment. An index system of highway traffic safety influencing factors for cold regions is developed, and an evaluation model for traffic road safety influencing factors in cold regions based on attribute recognition theory is proposed. The weight of the model is determined using an analytic hierarchy process combined with expert scoring. The evaluation model is based on single-index attribute measure values and multi-index comprehensive attribute measurement values, using the confidence criterion to identify the influence of road traffic safety factors on road traffic safety in cold regions. In addition, the fuzzy comprehensive evaluation method is used for comparative evaluation, and the evaluation results were consistent and verified the correctness and feasibility of the attribute recognition model. Results showed that the evaluation system was in good agreement with actual traffic conditions in cold regions.

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