3 citations · 5 across the 5 of their papers we have counts for
5 papers
S2Vec: Self-Supervised Geospatial Embeddings for the Built Environment
Shushman Choudhury, Elad Aharoni, Chandrakumari Suvarna +4
Scalable general-purpose representations of the built environment are crucial for geospatial artificial intelligence applications. This paper introduces S2Vec, a novel self-supervi…
On the Use of Abundant Road Speed Data for Travel Demand Calibration of Urban Traffic Simulators
Suyash Vishnoi, Akhil Shetty, Iveel Tsogsuren +2
This work develops a compute-efficient algorithm to tackle a fundamental problem in transportation: that of urban travel demand estimation. It focuses on the calibration of origin-…
Scalable Learning of Segment-Level Traffic Congestion Functions
Shushman Choudhury, Abdul Rahman Kreidieh, Iveel Tsogsuren +3
We propose and study a data-driven framework for identifying traffic congestion functions (numerical relationships between observations of traffic variables) at global scale and se…
Quantifying the sustainability impact of Google Maps: A case study of Salt Lake City
Neha Arora, Theophile Cabannes, Sanjay Ganapathy +6
Google Maps uses current and historical traffic trends to provide routes to drivers. In this paper, we use microscopic traffic simulation to quantify the improvements to both trave…
An Efficient Simulation-Based Travel Demand Calibration Algorithm for Large-Scale Metropolitan Traffic Models
Neha Arora, Yi-fan Chen, Sanjay Ganapathy +5
Metropolitan scale vehicular traffic modeling is used by a variety of private and public sector urban mobility stakeholders to inform the design and operations of road networks. Hi…