Datasets

subject: ccat

Total is 22 Results
Highly Transportation Disadvantaged Areas Indianapolis

10.4231/12HS-8G97

Christos Gkartzonikas ORCID logo , Konstantina Gkritza ORCID logo , Lisa Lorena Losada-Rojas ORCID logo , Raul F. Elizondo Candanedo

08/10/2022

This file contains areas designated as highly transportation disadvantaged in Indianapolis. These two areas were outlined using three different measures and publicly available data. The methodology is replicable and can be used in other cities.

Autonomous Vehicles ccat Civil Engineering disadvantaged population GIS

Pedestrian-Vehicle Interaction in a CAV Environment: Explanatory Metrics

10.4231/0YGE-HT33

Jon Fricker , Yunchang Zhang ORCID logo

07/05/2022

3 journal articles and 3 conference articles were produced from this project. The research from this advanced research project was disseminated to over 200 people from industry, government, and academia.

ccat Civil Engineering crosswalks Pedestrian Behavior Pedestrian-Vehicle Interactions

Multinomial Logit models raw data for Chicago and Indianapolis

10.4231/4SXF-5N11

Konstantina Gkritza ORCID logo , Lisa Lorena Losada-Rojas ORCID logo

08/15/2022

These two files contain information regarding a travel survey when respondents share travel habits and opinions regarding travel easiness. It is also the first NHTS effort to include health-related data with travel data.

Autonomous Vehicles ccat Civil Engineering NHTS substitution patterns

Cooperative Control Mechanism for Platoon Formation of Connected and Autonomous Vehicles

10.4231/S6JE-ME83

Anye Zhou , Chaojie Wang , Jian Wang , Samuel Labi ORCID logo , Srinivas Peeta , Yu Wang

07/08/2022

The dataset of CCAT project "Cooperative Control Mechanism for Platoon Formation of Connected and Autonomous Vehicles"

Acceleration autonomous and connected vehicles ccat congestion

Development of In-vehicle Information Dissemination Mechanisms to Reduce Cognitive Burden in the Information-rich Driving Environment

10.4231/QVDH-1124

Irina Benedyk ORCID logo , Shubham Agrawal ORCID logo , Srinivas Peeta

07/18/2022

Processed driving simulator data collected at NEXTRANS Center, Purdue University. Data features synchronized EEG band powers around an instance of auditory travel information and contains demographic, information scenario, and trip details.

ccat Civil Engineering driver cognition driving simulator EEG travel information

In-vehicle Alerts for Conditionally Automated Vehicles

10.4231/JGHH-F716

Dustin J Souders ORCID logo , Irina Benedyk ORCID logo , Shubham Agrawal ORCID logo , Srinivas Peeta , Yuntao Guo

08/10/2022

Driving simulator study data collected at Purdue University from 2018-2019. Participants came in to the lab and completed the 2.5 hour long study that investigated the effects of different introductory information on take-over performance.

ccat Civil Engineering Conditionally automated driving graded warnings introductory materials SAE L3 take-over vehicle automation

Origin-Destination (O-D) Matrix from Indianapolis

10.4231/543K-FR90

Christos Gkartzonikas ORCID logo , Konstantina Gkritza ORCID logo , Lisa Lorena Losada-Rojas ORCID logo , Zimo Zhang

08/16/2022

The Origin-Destination matrix for Indy contains the flows of the 42 Transportation Analysis Zones surrounding the Indianapolis area. It also presents the total amount of travel within each region.

ccat Civil Engineering environmental impacts Shared autonomous vehicles

Highly Transportation Disadvantaged Area Chicago

10.4231/HYGW-T670

Christos Gkartzonikas ORCID logo , Konstantina Gkritza ORCID logo , Lisa Lorena Losada-Rojas ORCID logo , Raul F. Elizondo Candanedo

08/10/2022

This file contains areas designated as highly transportation disadvantaged in Chicago. This areas were outlined using three different measures and publicly available data. The methodology is replicable and can be used in different areas.

Autonomous Vehicles ccat Civil Engineering disadvantaged population GIS

Trajectory Dataset for translation of driver-pedestrian behavioral models at semi- controlled crosswalks into a quantitative framework.

10.4231/KMQX-R785

Jon D. Fricker , Yunchang Zhang ORCID logo

10/03/2022

On-site cameras provided a bird-eye view of an unsignalized crosswalk. Computer Vision algorithms generate a large-scale spatial-temporal trajectory dataset from more than three hours of videos.

ccat Civil Engineering Pedestrian Behavior Pedestrian-Vehicle Interactions

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