We present a data-driven framework for mitigating bus bunching and gapping using real-time transit data, machine learning, and optimization models. The system supports proactive headway management by evaluating and recommending operational control strategies that improve service regularity and network performance.
Speakers
Ghazaleh mohseni
Ghazaleh Mohseni is the R&D Director at the Interactive-OR, where she leads the design and development of decision-support systems for urban mobility and transportation operations. Her work combines optimization, machine learning, and large-scale data to build practical tools that help cities improve network design, reliability, and operational efficiency.