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8 results for “rideshare”
Large-scale Ridesharing DARP Instances Based on Real Travel Demand
<p>This repository presents a set of large-scale Dial-a-Ride Problem (DARP) instances. The instances were created as a standardized set of ridesharing DARP problems for the purpose of benchmarking and comparing different solution methods.</p><p>The instances are based on real demand and realistic travel time data from 3 different US cities, Chicago, New York City and Washington, DC. The instances consist of real travel requests from the selected period, positions of vehicles with their capacities and realistic shortest travel times between all pairs of locations in each city.</p><p>The instances and results of two solution methods, the Insertion Heuristic, and the optimal Vehicle-group Assignment method, can be found in the dataset. The dataset and methodology used to create it are described in the paper <a href="https://arxiv.org/abs/2305.18859">Large-scale Ridesharing DARP Instances Based on Real Travel Demand</a>.</p>
Rideshare Dataset without Missing Values
<p>This dataset contains various hourly time series representations of attributes related to Uber and Lyft rideshare services for various locations in New York between 26/11/2018 and 18/12/2018. </p> <p>For a given starting location, provider and service, the following types are represented: 'price_min', 'price_mean', 'price_max', 'distance_min', 'distance_mean', 'distance_max', 'surge_min', 'surge_mean', 'surge_max', 'api_calls', 'temp', 'rain', 'humidity', 'clouds' and 'wind'.</p> <p>The original dataset contains missing values and they have been simply replaced by zeros. </p>
Rideshare Dataset with Missing Values
<p>This dataset contains various hourly time series representations of attributes related to Uber and Lyft rideshare services for various locations in New York between 26/11/2018 and 18/12/2018. </p> <p>For a given starting location, provider and service, the following types are represented: 'price_min', 'price_mean', 'price_max', 'distance_min', 'distance_mean', 'distance_max', 'surge_min', 'surge_mean', 'surge_max', 'api_calls', 'temp', 'rain', 'humidity', 'clouds' and 'wind'.<br> </p>
The Impact of Rideshare Transportation Services on Appointment Adherence
ClinicalTrials.gov study NCT02955433. IPD Sharing: NO. Countries: 1. Publications: 2.
Impacts of Subsidized Ridesharing on Drunk Driving, Alcohol Consumption, and Mobility
ClinicalTrials.gov study NCT04949711. IPD Sharing: YES. Countries: 1. Publications: 0.
Door-Through-Door Companion Rideshare Technology for Individuals With Alzheimer's Disease and Related Dementias (AD/ADRD)
ClinicalTrials.gov study NCT06850870. IPD Sharing: YES. Countries: 1. Publications: 0.
Improving Access to Community-Based Occupations Via a Rideshare Training Program
ClinicalTrials.gov study NCT06323850. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Self-leadership in ridesharing
<p>Data on self-leadership in rideshare drivers</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.