Tagged / BCP Council

BU PhD Candidate Shares Transportation Expertise at Dorset COP 24

conferences, Knowledge Exchange

🌍🚗 Thrilled to Have Participated in Dorset COP 24! 🚗🌍

Today, I had the incredible opportunity to contribute to the “Future Transport System in Dorset” workshop at Dorset COP 24. As an expert speaker, I joined Dorset and BCP Council representatives, local Transport Action Groups, the General Manager of More Bus, the Lead Director of Great British Railways and engaged community members to reimagine what Dorset’s transport landscape could look like over the next decade—and how we can achieve these changes sustainably.

During the session, I presented my research on complex urban road networks and traffic congestion spread, sparking insightful conversations on innovative, eco-friendly strategies that could reshape our local transport systems. After a dynamic Q&A with experts, I was invited to share my findings with the BCP Council’s Transportation Team and the Dorchester Transport Action Group in their upcoming meetings—a fantastic opportunity to see these ideas reach even wider audiences!

I’m feeling inspired and energized by the collaboration, insights, and shared commitment to a greener future for Dorset. Thank you, Lois Betts (BU Sustainability Manager), Joseph McMullen (BU Lecturer) for the invitation and support. Let’s keep pushing for sustainable progress! 🌱

Assemgul, PhD candidate, SciTech, Computing Department. Research title: “Complex Urban Road Networks: Static Structures and Dynamic Processes.”

BU collaborates with BCP Council and Cambridge University on congestion modelling

open access

Bournemouth University (BU) collaborates with the Bournemouth Christchurch Poole (BCP) Council and Cambridge University on modeling traffic congestion propagation. The work, conducted by Dr. Wei Koong Chai and Ph.D. Candidate Assemgul Kozhabek from BU advocates the use of epidemic theory to model the spreading of traffic congestion in cities.

The team proposes a modified Susceptible-Infected-Recovered (SIR) model that considers the road network structure for a more accurate representation of congestion spreading. Through an N-intertwined modeling framework and analysis using real-world traffic datasets from California and Los Angeles, the study demonstrates improved agreement with actual congestion conditions. The findings offer valuable insights for developing effective traffic congestion mitigation strategies.

Reference:

A. Kozhabek, W. K. Chai and G. Zheng, “Modeling Traffic Congestion Spreading Using a Topology-Based SIR Epidemic Model,” in IEEE Access, vol. 12, pp. 35813-35826, 2024, doi: 10.1109/ACCESS.2024.3370474.