2 citations · 2 across the 7 of their papers we have counts for
9 papers
Controllable Road Marking Generation
Zhiyu, Cai, Yufan Zhang +3
Lane and road markings provide critical guidance for vehicle navigation and multi-agent coordination, yet authoring them at scale remains a manual workflow that limits quantitative…
Worst-Case Hidden-Vehicle Trajectory Search in Spatiotemporal Occlusion Regions
Ruichen Tan, Zengxiang Lei, Satish Ukkusuri
Occlusion creates fundamental uncertainty in autonomous driving. Existing methods often propagate frame-wise hypotheses or optimize ego behavior against prescribed hidden-agent pre…
Observation-Aligned Two-Stage Domain Decomposition for Physics-Informed Traffic State Estimation with Sparse Fixed Sensors
Eunhan Ka, Ludovic Leclercq, Satish V. Ukkusuri
Traffic state estimation from sparse fixed sensors is challenging because physics-informed neural networks (PINNs) tend to over-smooth sharp transitions admitted by the Lighthill-W…
Stable GFlowNets with TV Monitoring and Probabilistic Guarantees
Zengxiang Lei, Ananth Shreekumar, Jonathan Rosenthal +6
Generative Flow Networks (GFlowNets) sample diverse structured objects in proportion to reward and have been applied to molecular discovery and biological-sequence design, where fi…
MoE-TransMov: A Transformer-based Model for Next POI Prediction in Familiar & Unfamiliar Movements
Ruichen Tan, Jiawei Xue, Kota Tsubouchi +2
Accurate prediction of the next point of interest (POI) within human mobility trajectories is essential for location-based services, as it enables more timely and personalized reco…
D4+: Emergent Adversarial Driving Maneuvers with Approximate Functional Optimization
Diego Ortiz Barbosa, Luis Burbano, Carlos Hernandez +4
Intelligent mechanisms implemented in autonomous vehicles, such as proactive driving assist and collision alerts, reduce traffic accidents. However, verifying their correct functio…
Data Mining in Transportation Networks with Graph Neural Networks: A Review and Outlook
Jiawei Xue, Ruichen Tan, Jianzhu Ma +1
Data mining in transportation networks (DMTNs) refers to using diverse types of spatio-temporal data for various transportation tasks, including pattern analysis, traffic predictio…
Long-term forecasts of statewide travel demand patterns using large-scale mobile phone GPS data: A case study of Indiana
Rajat Verma, Eunhan Ka, Satish V. Ukkusuri
The growth in availability of large-scale GPS mobility data from mobile devices has the potential to aid traditional travel demand models (TDMs) such as the four-step planning mode…
Towards a generalized accessibility measure for transportation equity and efficiency
Rajat Verma, Mithun Debnath, Shagun Mittal +1
Locational measures of accessibility are widely used in urban and transportation planning to understand the impact of the transportation system on influencing people's access to pl…