Road Traffic Accident Data Analysis and Its Visualization

Abstract Due to increasing human population and the number of vehicles, road traffic accident has significant influence on human life and economic development. In the present study, road traffic accident data of three years (2015-2017) were obtained from Hosanna Town Traffic Police Department, and Hosanna Town Transport Authority in Ethiopia. The Global Position System was used to know X, Y coordinates of the accident locations. Global Position System point data and accident data were added to road network data using the ‘Joins and relates’ function in ArcGIS. The results of the study showed a total of 241 Road traffic accidents (RTAs) were occurred in the town from which about 208 victims occurred on people and 33 damaged properties. Based on severity and frequencies of RTAs top nine hot spot areas were identified which requires high attention to protect people and property from damage and loss. Thus, the government and other concerned stakeholders should provide public education and awareness creation to reduce risk of fatalities and property damage due to RTAs in Hosanna town.

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O36: DEVELOPING A TRAUMA REGISTRY IN A MIDDLE INCOME COUNTRY – BOTSWANA

British Journal of Surgery ◽

10.1093/bjs/znab117.036 ◽

2021 ◽

Vol 108 (Supplement_1) ◽

Author(s):

Mpapho Joseph Motsumi ◽

Yohana Mashalla ◽

Miriam Sebego ◽

Ari Ho-Foster ◽

Paul Motshome ◽

...

Keyword(s):

Data Collection ◽

Phase I ◽

Road Traffic Accident ◽

Traffic Accident ◽

Trauma Registry ◽

Road Traffic ◽

Completion Rate ◽

Hard Copy ◽

Accident Data ◽

Existing Data

Abstract Background Botswana has a large burden of disease from injury, but no trauma registry. This study sought to design and pilot test a trauma registry at two hospitals. Methods A cross sectional study was piloted at a tertiary hospital and a secondary level hospital in Botswana. The study consisted of two stages: stage 1 mainly involved stakeholder consultations on existing data collection tools. Stage 2 consisted of two phases: Phase I involved retrospective collection of existing data from existing data collection tools and Phase II collected data prospectively using the proposed trauma registry prototype. Results The pre-hospital road traffic accident data is collected using hard copy forms and some of this data is transferred to a stand-alone electronic registry. The hospital phase of road traffic accident data all goes into hard copy files then stored in institutional registry departments. The post-hospital data is also partially stored as hard copies and some data is stored in a stand-alone electronic registry. The demographics, pre-hospital, triage, diagnosis, management and disposition had a high percent variable completion rate with no significant difference between phases I and II. However, the primary survey variables in Phase I had a low percent variable completion rate which was significantly different from the high completion rates in phase II at both hospitals. A similar picture was observed for the secondary survey at both hospitals. Conclusion Electronic trauma registries are feasible and data completion rate is high when using the electronic data registry as opposed to data collected using the existing paper-based data collection tools. Keywords Trauma registry, Injury registry, Road Traffic Accident Trauma Registry, Road Traffic Crushes Registry, Road Accident Registry. SYSTEMATIC REVIEWS

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A Hybrid Algorithm of Traffic Accident Data Mining on Cause Analysis

Mathematical Problems in Engineering ◽

10.1155/2013/302627 ◽

2013 ◽

Vol 2013 ◽

pp. 1-8 ◽

Cited By ~ 4

Author(s):

Jianfeng Xi ◽

Zhenhai Gao ◽

Shifeng Niu ◽

Tongqiang Ding ◽

Guobao Ning

Keyword(s):

Data Mining ◽

Association Rules ◽

Road Traffic Accident ◽

Traffic Accident ◽

Road Traffic ◽

Multilayered Structure ◽

Test Model ◽

Data Sampling ◽

Accident Data ◽

Improved Algorithm

Road traffic accident databases provide the basis for road traffic accident analysis, the data inside which usually has a radial, multidimensional, and multilayered structure. Traditional data mining algorithms such as association rules, when applied alone, often yield uncertain and unreliable results. An improved association rule algorithm based on Particle Swarm Optimization (PSO) put forward by this paper can be used to analyze the correlation between accident attributes and causes. The new algorithm focuses on characteristics of the hyperstereo structure of road traffic accident data, and the association rules of accident causes can be calculated more accurately and in higher rates. A new concept of Association Entropy is also defined to help compare the importance between different accident attributes. T-test model and Delphi method were deployed to test and verify the accuracy of the improved algorithm, the result of which was a ten times faster speed for random traffic accident data sampling analyses on average. In the paper, the algorithms were tested on a sample database of more than twenty thousand items, each with 56 accident attributes. And the final result proves that the improved algorithm was accurate and stable.

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