Road Traffic Safety Status Evaluation Model Based on Matter Element Extension Method

CICTP 2018 ◽  
2018 ◽  
Author(s):  
Feng Lu ◽  
Hongliang Wang
Keyword(s):  
Traffic Safety ◽  
Road Traffic ◽  
Evaluation Model ◽  
Extension Method ◽  
Road Traffic Safety ◽  
Model Based

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.

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.

Research on construction and application of an evaluation system for regional road traffic safety

2018 ◽  
Vol 8 (4) ◽  
pp. 527-538 ◽  
Author(s):  
Bing-ru Cao ◽  
Hui-Hui Cao ◽  
Yong Liu
Keyword(s):  
Traffic Safety ◽  
Evaluation System ◽  
Feature Vector ◽  
Road Traffic ◽  
Evaluation Model ◽  
Ideal Point ◽  
Vector Method ◽  
Content Type ◽  
Road Traffic Safety ◽  
Proposed Model

Purpose The purpose of this paper is to construct a novel grey incidence evaluation model to investigate a scientific and effective evaluation system of regional road traffic safety. Design/methodology/approach To provide a method for the evaluation of regional road traffic safety, the grey incidence feature vector method is employed to construct the evaluation index system for regional road traffic safety and then the index weights are calculated with Shannon entropy method. In this paper, the grey incidence feature vector method and grey incidence analysis are utilised to construct evaluation index systems for regional road traffic safety and determine the index weights. Then a grey incidence-ideal point method is used to establish a novel evaluation model for regional road traffic safety. To thoroughly investigate the road traffic safety in one region, the data of 13 cities in Jiangsu province is gathered, using the grey clustering and grey incidence-ideal point method to obtain the ranking results of the 13 cities. Findings The results provide a basic analysis of the present situation and show the differences for these regions based on the proposed model, according to which several solutions are proposed, aiming to improve regional road traffic safety situation. Practical implications The method exposed in the paper can be used to deal with the problems of the evaluation of regional road traffic safety. Originality/value The paper succeeds in understanding the status quo and implementing effective road traffic safety management based on the proposed model.

Safety Enhancement by Automated Driving: What are the Relevant Scenarios?

2020 ◽  
Vol 64 (1) ◽  
pp. 1686-1690
Author(s):  
Niklas Grabbe ◽  
Michael Höcher ◽  
Alexander Thanos ◽  
Klaus Bengler
Keyword(s):  
Traffic Safety ◽  
Road Traffic ◽  
Test Cases ◽  
Automated Driving ◽  
Road Traffic Safety ◽  
Human Driver ◽  
Driving Task ◽  
Promising Solution ◽  
Vehicle Automation ◽  
Safety Enhancement

Automated driving offers great possibilities in traffic safety advancement. However, evidence of safety cannot be provided by current validation methods. One promising solution to overcome the approval trap (Winner, 2015) could be the scenario-based approach. Unfortunately, this approach still results in a huge number of test cases. One possible way out is to show the current, incorrect path in the argumentation and strategy of vehicle automation, and focus on the systemic mechanisms of road traffic safety. This paper therefore argues the case for defining relevant scenarios and analysing them systemically in order to ultimately reduce the test cases. The relevant scenarios are based on the strengths and weaknesses, in terms of the driving task, for both the human driver and automation. Finally, scenarios as criteria for exclusion are being proposed in order to systemically assess the contribution of the human driver and automation to road safety.

scholarly journals Assessing inequality, irregularity, and severity regarding road traffic safety during COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lei Lin ◽  
Feng Shi ◽  
Weizi Li
Keyword(s):  
New York ◽  
Los Angeles ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Human Mobility ◽  
Critical Conditions ◽  
Road Traffic Safety ◽  
Accident Data ◽  
The Impact

AbstractCOVID-19 has affected every sector of our society, among which human mobility is taking a dramatic change due to quarantine and social distancing. We investigate the impact of the pandemic and subsequent mobility changes on road traffic safety. Using traffic accident data from the city of Los Angeles and New York City, we find that the impact is not merely a blunt reduction in traffic and accidents; rather, (1) the proportion of accidents unexpectedly increases for “Hispanic” and “Male” groups; (2) the “hot spots” of accidents have shifted in both time and space and are likely moved from higher-income areas (e.g., Hollywood and Lower Manhattan) to lower-income areas (e.g., southern LA and southern Brooklyn); (3) the severity level of accidents decreases with the number of accidents regardless of transportation modes. Understanding those variations of traffic accidents not only sheds a light on the heterogeneous impact of COVID-19 across demographic and geographic factors, but also helps policymakers and planners design more effective safety policies and interventions during critical conditions such as the pandemic.

Sign in / Sign up

Export Citation Format

Share Document