Abstract
In today’s world, the traffic volume on urban road networks is multiplying rapidly due to the heavy usage of vehicles and mobility on demand services. Migration of people towards urban areas result in increasing size and complexity of urban road networks. When handling such complex traffic systems, partitioning the road network into multiple sub-regions and managing the identified sub regions is a popular approach. In this paper, we propose an algorithm to identify sub-regions of a road network that exhibit homogeneous traffic flow patterns. In a stage wise manner, we model the road network graph by using taxi-trip data obtained on the selected region. Then, we apply the proposed modified multilevel kway partitioning algorithm to obtain optimal number of partitions from the developed road graph. An interesting feature of this algorithm is, resulting partitions are geographically connected and consists minimal interpartition trip flow. Our results show that the proposed algorithm outperforms state-of-the-art multilevel partitioning algorithms for tripbased road networks. By this research, we demonstrate the ability of road network partitioning using trip data while preserving the partition homogeneity and connectivity.
Highlights
Road traffic networks are rapidly growing in size with increasing population and urbanization
The increased usage of motor vehicles worsens the problem of traffic congestion and creates a more challenging environment for the traffic management. These road traffic networks can be recognized as distinct sub-networks or partitions which exhibit homogeneous traffic flow patterns within the partitions
We presented a modified multilevel k-way partitioning process for large urban road networks based on taxi trip data
Summary
Road traffic networks are rapidly growing in size with increasing population and urbanization. The increased usage of motor vehicles worsens the problem of traffic congestion and creates a more challenging environment for the traffic management. In managing, these road traffic networks can be recognized as distinct sub-networks or partitions which exhibit homogeneous traffic flow patterns within the partitions. These road traffic networks can be recognized as distinct sub-networks or partitions which exhibit homogeneous traffic flow patterns within the partitions By identifying such traffic flow patterns, partition specific traffic flow management strategies can be implemented. Road network partitioning helps in identifying the traffic flow patterns and partition
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
