Mobile-based GIS network analysis for the identification of the best route : A case study in traffic system of the Great Cairo /
Sayed Ahmed Sayed Ahmed
Mobile-based GIS network analysis for the identification of the best route : A case study in traffic system of the Great Cairo / استخدام التليفون المحمول في تحليل شبكة نظم المعلومات الجغرافية لتحديد أفضل مسار : حالة دراسة على نظام المرور في القاهرة الكبري Sayed Ahmed Sayed Ahmed ; Supervised Hesham Ahmed Hefny , Romani Farid Ibrahim - Cairo : Sayed Ahmed Sayed Ahmed , 2019 - 185 Leaves : charts , maps ; 25cm
Thesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Computer and Information Sciences
Rapid emergency response to the scene of a traffic accident and transportation of the injured to a medical facility is critical for saving lives. Traffic congestion is a major problem in urban areas, especially in an overcrowded city like the Great Cairo (GC). Traffic congestion can disrupt emergency response, but dynamic network routing can offer solutions. Geographic Information system (GIS) can be a useful tool for determining emergency vehicle response routing, and the application of dynamic variables like historical traffic data can help emergency response vehicles avoid traffic congestion and improve response times. This study proposes a methodology where route solvers based on Dijkstras shortest path algorithm in ArcGIS Network Analyst were utilized to identify the closest ground emergency response unit (e.g., healthcare services providers) to each incident and then solving the shortest path problem centered around emergency response routing scenarios. Cost attributes or impedances, namely distance and Time-Varying Travel Time (TVTT) originating from historical traffic data, were applied to each routing scenario to determine the shortest and the best (optimal) routes from an origin to a destination. It also proposes an enhanced routing technique based on Dijkstras algorithm and the Analytic Hierarchy Process (AHP) to be used in emergency cases
Geographic Information Systems Great Cairo Network Analysis
Mobile-based GIS network analysis for the identification of the best route : A case study in traffic system of the Great Cairo / استخدام التليفون المحمول في تحليل شبكة نظم المعلومات الجغرافية لتحديد أفضل مسار : حالة دراسة على نظام المرور في القاهرة الكبري Sayed Ahmed Sayed Ahmed ; Supervised Hesham Ahmed Hefny , Romani Farid Ibrahim - Cairo : Sayed Ahmed Sayed Ahmed , 2019 - 185 Leaves : charts , maps ; 25cm
Thesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Computer and Information Sciences
Rapid emergency response to the scene of a traffic accident and transportation of the injured to a medical facility is critical for saving lives. Traffic congestion is a major problem in urban areas, especially in an overcrowded city like the Great Cairo (GC). Traffic congestion can disrupt emergency response, but dynamic network routing can offer solutions. Geographic Information system (GIS) can be a useful tool for determining emergency vehicle response routing, and the application of dynamic variables like historical traffic data can help emergency response vehicles avoid traffic congestion and improve response times. This study proposes a methodology where route solvers based on Dijkstras shortest path algorithm in ArcGIS Network Analyst were utilized to identify the closest ground emergency response unit (e.g., healthcare services providers) to each incident and then solving the shortest path problem centered around emergency response routing scenarios. Cost attributes or impedances, namely distance and Time-Varying Travel Time (TVTT) originating from historical traffic data, were applied to each routing scenario to determine the shortest and the best (optimal) routes from an origin to a destination. It also proposes an enhanced routing technique based on Dijkstras algorithm and the Analytic Hierarchy Process (AHP) to be used in emergency cases
Geographic Information Systems Great Cairo Network Analysis