عمرو حنفى أحمد على
أستاذ متفرغ
MLRS and Dynamic Segmentation for Traffic Congestion Management
American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) • 2017
معلومات البحث
المؤلفون
Amr H. Ali
الكلمات المفتاحية
Multi-linear referencing systems; dynamic segmentation; GIS; congestion management; and
dynamic network.
المجلة العلمية
American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS)
الناشر
Scientific Academic Publisher
المجلد
29
العدد
1
الصفحات
213-227
publication.type
International
رابط البحث
Open Link
المواد المرفقة
Not Available
الملخص
Geomatics techniques is applied in many directions as a decision support tool, one of them is the organization
and management of transportation. Traffic congestion is a serious problem, where the road behavior is
influencing on people economically as well as intellectually/ Transportation networks are a specialized type of
graph that models the logical and topological information in the real world. The road network includes multilinear
reference system (MLRS) based model that focuses on network topological analysis. It involves the
collection of traffic data that describe the characteristics and geometry of road network, vehicle counts, speed,
flow rates, density in order to define the congestion situation. The objective of this research is to integrate the
rules of graph theory MLRS and dynamic segmentation (DS) to examine the significance of historical traffic
information gathered through Geographic Information Systems (GIS) for solving the dynamic path analysis.
This guides vehicles through the urban road network using the optimal path taking into account the traffic
conditions on the roads that change over the time.
and management of transportation. Traffic congestion is a serious problem, where the road behavior is
influencing on people economically as well as intellectually/ Transportation networks are a specialized type of
graph that models the logical and topological information in the real world. The road network includes multilinear
reference system (MLRS) based model that focuses on network topological analysis. It involves the
collection of traffic data that describe the characteristics and geometry of road network, vehicle counts, speed,
flow rates, density in order to define the congestion situation. The objective of this research is to integrate the
rules of graph theory MLRS and dynamic segmentation (DS) to examine the significance of historical traffic
information gathered through Geographic Information Systems (GIS) for solving the dynamic path analysis.
This guides vehicles through the urban road network using the optimal path taking into account the traffic
conditions on the roads that change over the time.
