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Name: BUILT@NYU
Type: Organization
Bio: Behavioral Urban Informatics, Logistics, and Transport Laboratory
Location: Brooklyn, New York
Name: BUILT@NYU
Type: Organization
Bio: Behavioral Urban Informatics, Logistics, and Transport Laboratory
Location: Brooklyn, New York
Extract the location data and monitor bus arrivals
Despite the ubiquity of transportation data, statistical inference methods alone are not able to explain mechanistic relations within a network. Inverse optimization methods that capture network structure fulfill this gap, but they are designed to take observations of the same model to learn the parameters of that model. New inverse optimization models and supporting algorithms are proposed to learn the parameters of heterogeneous travelers’ route optimization such that the value of shared network resources (e.g. link capacity dual prices) can be inferred. The inferred values are internally consistent with each agent’s optimization program. We prove that the method can obtain unique dual prices for a network shared by these agents, in polynomial time. Three experiments are conducted. The first one, conducted on a 4-node network, verifies the methodology to obtain heterogeneous link cost parameters even when a mixed logit model cannot provide meaningful results. The second is a parameter recovery test on the Nguyen-Dupuis network that shows that unique latent link capacity dual prices can be inferred using the proposed method. The last test on the same network demonstrates how a monitoring system in an online learning environment can be designed using this method.
Non-myopic relocation of idle mobility-on-demand vehicles as a dynamic location-allocation-queueing problem
GIS shp files for NYMTC TAZ 2010
Common purpose optimization algorithms
Prototype recommender system design for mobility systems to provide more reliable paratransit for elderly
This repository stores the data and scripts for the paper: A school bus routing problem with a mixed ride, mixed load, and heterogeneous fleet
SSTNDP: Sequential Segment-level Transit Network Design Problem
An implementation of Alonso-Mora et al. 's dynamic routing approach for ridesharing
This repository contains materials of our studies on transit data sharing games, including noncooperative and cooperative approaches.
Two tools (schedule-based, static) provided for transit flow estimation. Assignment algorithms can be used independently.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.