Integration of Automated Vehicle Sensing with Adaptive Signal Control for Enhanced Mobility [supporting datasets]

Smith, Stephen F.; Hawkes, Allen; Mobility21, Carnegie Mellon University

doi:10.5281/zenodo.4500187

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Integration of Automated Vehicle Sensing with Adaptive Signal Control for Enhanced Mobility [supporting datasets]

[PDF-118.93 KB]

English

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Details:

Creators:

Smith, Stephen F. ; Hawkes, Allen

Smith, Stephen F. ; Hawkes, Allen Less -
Corporate Creators:

Mobility21, Carnegie Mellon University
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology Less -
Subject/TRT Terms:

[+]

Autonomous Vehicles Data Sharing Field Tests Optimization Routes And Routing Traffic Delays Traffic Signal Control Systems Traffic Simulation Vehicle To Infrastructure Communications
DOI:

https://doi.org/10.5281/zenodo.4500187
Resource Type:

Dataset
Geographical Coverage:

United States
Corporate Publisher:

Mobility21, Carnegie Mellon University
Abstract:

This repository contains the results produced by CMU-UTC Project 294, titled "Integration of Autonomous Vehicles with Adaptive Signal Control to Enhance Mobility." The data contains comparative results of a pilot experiment designed to demonstrate the traffic flow efficiency can be improved by vehicle-to-infrastructure communication and use of vehicle route information by a real-time adaptive traffic signal control system.
Format:

XLSX
Funding:

69A3551747111
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:191d0b3193a1178892e63c13cb266bc1cdcbd2f9d5c4cbf3581eff1ff6316e60
Download URL:

https://rosap.ntl.bts.gov/view/dot/60287/dot_60287_DS1.pdf
File Type:

Metadata File

json

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