ملخص الدراسة:

Around the world, traffic accidents are considered as one of the most important causes of death. In Palestine, recorded traffic accidents increased twice in the period from 2007 to 2013. This situation reflects the dangerous situation on the roads. In this research, analysis of the traffic accidents in Palestine from 2000 to 2013 is carried out. It shows that accidents in Palestine have a non-stable behavior due to the continuous changing in the political situation. The databases and Gaza Aerial photo are collected from Ministry of Transportation, Land Authority and Gaza Police Department. A team consisting of 20 members, covering all Gaza strip governorates, worked to specify the location of the accidents from 2000 to 2005 using ArcGIS. They located 67% of the accidents. These data are used to identify black spots and to find the most dangerous locations in Gaza Strip. The black spot identification shows that Salah Aldeen Street has more than five black spots. Therefore, it is recommended to apply the Rout Action Approach in order to prepare an accident reduction plan. After that, an artificial neural network model is developed using spots factors and weighting. The main factors that are used in the model are the traffic volume, the number of the intersections in the spot, the existence of the median in the main road, the existence of one-way roads in the spot, the surface type, the design speed, the number of lanes and the road design width. In validation process, the model sensitivity value is (91%), model specificity value is (72%), and the coefficient of determination (R2) value is 0.55. These numbers indicate that the model could represent the real data.

توثيق المرجعي (APA)

ELAstal, Ibrahim M.A. (2014). Modeling Road Accident Black Spots in Gaza Strip Using Artificial Neural Network (ANN) 2000-2013. الجامعة الإسلامية - غزة. 19402