59 citations · 120 across the 10 of their papers we have counts for
10 papers
Estimating and Mitigating the Congestion Effect of Curbside Pick-ups and Drop-offs: A Causal Inference Approach
Xiaohui Liu, Sean Qian, Hock-Hai Teo +1
Curb space is one of the busiest areas in urban road networks. Especially in recent years, the rapid increase of ride-hailing trips and commercial deliveries has induced massive pi…
Statistical inference of travelers' route choice preferences with system-level data
Pablo Guarda, Sean Qian
Traditional network models encapsulate travel behavior among all origin-destination pairs based on a simplified and generic utility function. Typically, the utility function consis…
Estimating probabilistic dynamic origin-destination demands using multi-day traffic data on computational graphs
Wei Ma, Sean Qian
System-level decision making in transportation needs to understand day-to-day variation of network flows, which calls for accurate modeling and estimation of probabilistic dynamic…
From Twitter to Traffic Predictor: Next-Day Morning Traffic Prediction Using Social Media Data
Weiran Yao, Sean Qian
The effectiveness of traditional traffic prediction methods is often extremely limited when forecasting traffic dynamics in early morning. The reason is that traffic can break down…
Learning to Recommend Signal Plans under Incidents with Real-Time Traffic Prediction
Weiran Yao, Sean Qian
The main question to address in this paper is to recommend optimal signal timing plans in real time under incidents by incorporating domain knowledge developed with the traffic sig…
High-Resolution Traffic Sensing with Autonomous Vehicles
Wei Ma, Sean Qian
The last decades have witnessed the breakthrough of autonomous vehicles (AVs), and the perception capabilities of AVs have been dramatically improved. Various sensors installed on…
Measuring and reducing the disequilibrium levels of dynamic networks through ride-sourcing vehicle data
Wei Ma, Sean Qian
Transportation systems are being reshaped by ride-sourcing and shared mobility services in recent years. The transportation network companies (TNCs) have been collecting high-granu…
Estimating multi-class dynamic origin-destination demand through a forward-backward algorithm on computational graphs
Wei Ma, Xidong Pi, Sean Qian
Transportation networks are unprecedentedly complex with heterogeneous vehicular flow. Conventionally, vehicle classes are considered by vehicle classifications (such as standard p…
Understanding and predicting travel time with spatio-temporal features of network traffic flow, weather and incidents
Shuguan Yang, Sean Qian
Travel time on a route varies substantially by time of day and from day to day. It is critical to understand to what extent this variation is correlated with various factors, such…
A deep learning approach to real-time parking occupancy prediction in spatio-temporal networks incorporating multiple spatio-temporal data sources
Shuguan Yang, Wei Ma, Xidong Pi +1
A deep learning model is applied for predicting block-level parking occupancy in real time. The model leverages Graph-Convolutional Neural Networks (GCNN) to extract the spatial re…