MLRS and Dynamic Segmentation for Traffic Congestion Management
American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) • 2017
Publication Information
Authors
Amr H. Ali
Keywords
Multi-linear referencing systems; dynamic segmentation; GIS; congestion management; and
dynamic network.
Journal
American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS)
Publisher
Scientific Academic Publisher
Volume
29
Issue
1
Pages
213-227
publication.type
International
Paper Link
Open Link
Supplementary Materials
Not Available
Abstract
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.
Staff Members - Benha University