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  1. Salt Stockpile Inventory – May 1st -10th 2023 – INDOT Lebanon Salt Facility Post-Winter Refill

    2023-07-25 18:58:57 | Datasets | Contributor(s): Haydn a Malackowski, Mina Joesph, Christopher Gartner, Justin Mahlberg, Raja Manish, Yerassyl Koshan, Ayman F Habib, Darcy M. Bullock | doi:10.4231/CBH3-3019

    This visualization shows RGB images, LiDAR point clouds, and estimated volumes of the salt stockpile at the INDOT Lebanon Salt Facility as salt was delivered to refill the facility after the winter season.

    https://purr.purdue.edu/publications/4334

  2. Salt Stockpile Inventory - January 24 to 27, 2023- INDOT Lebanon Salt Facility

    2023-05-15 13:22:56 | Datasets | Contributor(s): Haydn A Malackowski, Mina Joesph, Greg Brinster, Justin Mahlberg, Raja Manish, Yerassyl Koshan, Ayman F Habib, Darcy M. Bullock | doi:10.4231/4MAG-JN90

    This visualization shows RGB images, LiDAR images and estimated volume of the salt stockpile at the INDOT Lebanon Salt Facility throughout a winter storm.

    https://purr.purdue.edu/publications/4266

  3. Heavy Fleet and Facilities Optimization: Electronic Tool for Generating Optimal Snow Routes (Python Version)

    2022-10-03 15:33:32 | Datasets | Contributor(s): Runjia Du, Richard Ajagu, Ramanujam Ramaswamy, Sam Labi | doi:10.4231/VCTK-A223

    The Snow Route Generation tool helps INDOT’s winter operations personnel to generate snow removal routes in an optimal manner and minimize the deadhead miles of the trucks deployed in snow removal. The manual explains how to use the SRG tool.

    https://purr.purdue.edu/publications/4005

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

    2022-10-03 15:46:15 | Datasets | Contributor(s): Jon D. Fricker, Yunchang Zhang | doi:10.4231/KMQX-R785

    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.

    https://purr.purdue.edu/publications/4137

  5. Origin-Destination (O-D) Matrix from Indianapolis

    2022-08-16 12:52:40 | Datasets | Contributor(s): Christos Gkartzonikas, Lisa Lorena Losada-Rojas, zimozhang1996@gmail.com, nadia@purdue.edu | doi:10.4231/543K-FR90

    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.

    https://purr.purdue.edu/publications/4123

  6. Multinomial Logit models raw data for Chicago and Indianapolis

    2022-08-15 16:04:25 | Datasets | Contributor(s): Lisa Lorena Losada-Rojas, Konstantina Gkritza | doi:10.4231/4SXF-5N11

    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.

    https://purr.purdue.edu/publications/4127

  7. In-vehicle Alerts for Conditionally Automated Vehicles

    2022-08-10 19:44:25 | Datasets | Contributor(s): Dustin J Souders, Shubham Agrawal, Irina Benedyk, Yuntao Guo, Srinivas Peeta | doi:10.4231/JGHH-F716

    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.

    https://purr.purdue.edu/publications/4118

  8. Highly Transportation Disadvantaged Areas Indianapolis

    2022-08-10 19:53:47 | Datasets | Contributor(s): Lisa Lorena Losada-Rojas, Christos Gkartzonikas, Raul F. Elizondo Candanedo, Konstantina Gkritza | doi:10.4231/12HS-8G97

    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.

    https://purr.purdue.edu/publications/4126

  9. Highly Transportation Disadvantaged Area Chicago

    2022-08-10 19:51:13 | Datasets | Contributor(s): Lisa Lorena Losada-Rojas, Christos Gkartzonikas, Raul F. Elizondo Candanedo, Konstantina Gkritza | doi:10.4231/HYGW-T670

    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.

    https://purr.purdue.edu/publications/4125

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

    2022-07-18 19:44:59 | Datasets | Contributor(s): Shubham Agrawal, Irina Benedyk, Srinivas Peeta | doi:10.4231/QVDH-1124

    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.

    https://purr.purdue.edu/publications/4104

  11. Pedestrian-Vehicle Interaction in a CAV Environment: Explanatory Metrics

    2022-07-05 19:17:09 | Datasets | Contributor(s): Yunchang Zhang, Jon Fricker | doi:10.4231/0YGE-HT33

    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.

    https://purr.purdue.edu/publications/4081

  12. Historical shorelines and imagery for Indiana's Lake Michigan coast

    2022-05-11 15:45:33 | Datasets | Contributor(s): Benjamin Theron Nelson-Mercer, Hannah R Tomkins, Cary David Troy | doi:10.4231/YX3X-C082

    Historical aerial and satellite imagery is provided for the Indiana Lake Michigan coastline, from 1965-present. Additionally, shorelines traced from the imagery are available for most dates provided.

    https://purr.purdue.edu/publications/3993

  13. SpeedCore Design Examples

    2022-03-21 13:17:25 | Datasets | Contributor(s): Amit H. Varma, Morgan Broberg, Soheil Shafaei, Ataollah Taghipour Anvari | doi:10.4231/ZVN1-4Q26

    Mathcad sheets for the design examples in AISC Design Guide on SpeedCore Design.

    https://purr.purdue.edu/publications/3753

  14. Electric and Hybrid Vehicle Miles Travelled Dataset

    2022-01-31 21:04:00 | Datasets | Contributor(s): Jairaj Desai, Jijo K. Mathew, Howell Li, Darcy M. Bullock | doi:10.4231/MTDC-3C27

    Total electric and hybrid vehicle miles travelled across 11 states and 1014 counties in the United States during the month of August 2021

    https://purr.purdue.edu/publications/3956

  15. Calibration Data Set for Damage Mechanics Challenge on Brittle-Ductile Material

    2022-01-19 16:43:50 | Datasets | Contributor(s): Liyang Jiang, Hongkyu Yoon, Laura J Pyrak-Nolte, Antonio Bobet, Joseph Morris | doi:10.4231/QF39-Q924

    Here, we provide a benchmark laboratory data set from 3 point bending experiments for a damage mechanics challenge to compare computational approaches on damage evolution in brittle-ductile material.

    https://purr.purdue.edu/publications/3905

  16. Winter Road Operations: Development of an Intelligent Snow Plow

    2021-06-11 15:16:02 | Series/Dataset | Contributor(s): Justin Mahlberg, Jijo K. Mathew, Darcy M. Bullock | doi:10.4231/HB7W-S331

    Guidance and resources associated with the intelligent snowplow database maintained by Purdue's Joint Transportation Research Program (JTRP).

    https://purr.purdue.edu/publications/3794

  17. Intelligent Snow Plow: Integrated Connected Vehicle Data and INDOT Traffic Camera Feed from February 15-16, 2021, Winter Storm

    2021-06-09 20:51:36 | Datasets | Contributor(s): Justin Mahlberg, Jairaj Desai, Woosung Kim, Howell Li, Darcy M. Bullock | doi:10.4231/SFMN-R881

    This video explains and illustrates the integration of an INDOT traffic camera with floating car data obtained from connected vehicles.

    https://purr.purdue.edu/publications/3810

  18. Intelligent Snow Plow: Integrated Connected Vehicle Data and INDOT Snowplow 63550 Telematics Feed from February 15-16, 2021, Winter Storm

    2021-06-09 20:54:23 | Datasets | Contributor(s): Justin Mahlberg, Jairaj Desai, Woosung Kim, Howell Li, Darcy M. Bullock | doi:10.4231/V572-YX70

    This video explains and illustrates the integration of an INDOT plow truck dashboard camera with floating car data obtained from connected vehicles.

    https://purr.purdue.edu/publications/3809

  19. Intelligent Snow Plow: Integrated Connected Vehicle Data and INDOT Snowplow 63678 Telematics Feed from February 15-16, 2021, Winter Storm

    2021-06-09 20:55:33 | Datasets | Contributor(s): Justin Mahlberg, Jairaj Desai, Howell Li, Woosung Kim, Darcy M. Bullock | doi:10.4231/D8XT-JS45

    This video explains and illustrates the integration of an INDOT plow truck dashboard camera with floating car data obtained from connected vehicles.

    https://purr.purdue.edu/publications/3808

  20. Intelligent Snow Plow: December 16, 2020 Winter Storm Activity

    2021-05-28 20:35:39 | Datasets | Contributor(s): Justin Mahlberg, Jairaj Desai, Woosung Kim, Howell Li, Darcy M. Bullock | doi:10.4231/7DSJ-1475

    This visualization shows snow plow deployment in response to winter storm activity.

    https://purr.purdue.edu/publications/3804

The Purdue University Research Repository (PURR) is a university core research facility provided by the Purdue University Libraries and the Office of the Executive Vice President for Research and Partnerships, with support from additional campus partners.