8 citations · 8 across the 4 of their papers we have counts for
4 papers
Pricing is All You Need to Improve Traffic Routing
Yu Tang, Kaan Ozbay, Li Jin
We investigate the design of pricing policies that enhance driver adherence to route guidance, ensuring effective routing control. The major novelty lies in that we adopt a Markov…
Physics-informed Machine Learning for Calibrating Macroscopic Traffic Flow Models
Yu Tang, Li Jin, Kaan Ozbay
Well-calibrated traffic flow models are fundamental to understanding traffic phenomena and designing control strategies. Traditional calibration has been developed base on optimiza…
How Does Driver Non-compliance Destroy Traffic Routing Control?
Yu Tang, Li Jin, Kaan Ozbay
Routing control is one of important traffic management strategies against urban congestion. However, it could be compromised by heterogeneous driver non-compliance with routing ins…
Dynamic Origin-Destination Matrix Prediction with Line Graph Neural Networks and Kalman Filter
Xi Xiong, Kaan Ozbay, Li Jin +1
Modern intelligent transportation systems provide data that allow real-time dynamic demand prediction, which is essential for planning and operations. The main challenge of predict…