Data Collection of Odometer Images via WhatsApp to Measure Vehicle Miles Traveled [supporting dataset]

Details

• Creators:
  Gulhare, Siddhartha ; Makino, Keita ; Roshan, Ranbir
• Corporate Creators:
  National Center for Sustainable Transportation (NCST) ; University of California, Davis, Institute of Transportation Studies
• 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
• Subject/TRT Terms:
  Data Collection Data Files App-based Data Collection Hardware In The Loop Simulation Machine Learning Mobile Applications Odometers Software Vehicle Miles Of Travel WhatsApp
• DOI:
  https://doi.org/10.5061/dryad.g79cnp62m
• Resource Type:
  Dataset
• Right Statement:
  Open Access; https://creativecommons.org/publicdomain/zero/1.0/
• Geographical Coverage:
  United States;California
• Corporate Publisher:
  National Center for Sustainable Transportation (NCST) (UTC)
• Abstract:
  California sets ambitious climate goals that demand a sharp reduction in the per-capita vehicle miles traveled (VMT). Traditionally, researchers have relied on three types of VMT data collection methods – travel surveys, passively collected data, and simulated data – to estimate VMT or understand factors affecting VMT. However, each of these methods has disadvantages for obtaining a reliable VMT dataset. Although travel surveys are an inexpensive way to collect VMT data with rich traveler attributes, they often suffer from bias and errors in reporting or recalling. Passively collected VMT data, such as traffic count data, can provide precise VMT data, yet they often lack information about “who” and “why” of travel. Lastly, simulated VMT data is useful when making counterfactual testing, but they are after all not real data. In this study, to fulfill the gap between current data collection strategies, we introduce a WhatsApp-based VMT data collection framework. The framework deployed on the Azure cloud platform automatically lets study participants submit photos of their odometer, communicates with them for administrative events, manages submitted images and other information of the participants, and displays that data on the web UI for the study administrator. With a pilot study with 77 participants, we successfully collected 173 photos of the odometer. Although only 3 photos out of 173 were unusable, demonstrating the capability of our framework, a couple of potential improvements, such as an interface that aligns the photo timestamps over the days or better recruitment approaches, should be addressed in future work.
  
  The total size of the ZIP file is 389 KB.
  
  
• Content Notes:
  This dataset additional data and software in a GitHub repository. This repository is accessible online: https://github.com/3rfm-its-davis/odometer-reading
  
  National Transportation Library (NTL) Curation Note: As this dataset is preserved in a repository outside U.S. DOT control, as allowed by the U.S. DOT’s Public Access Plan (https://doi.org/10.21949/1503647) Section 7.4.2 Data, the NTL staff has performed NO additional curation actions on this dataset. This dataset has been curated to CoreTrustSeal's curation level "C. Initial Curation." To find out more information on CoreTrustSeal's curation levels, please consult their "Curation & Preservation Levels" CoreTrustSeal Discussion Paper" (https://doi.org/10.5281/zenodo.11476980). NTL staff last accessed this dataset at its repository URL on 2024-08-28. If, in the future, you have trouble accessing this dataset at the host repository, please email NTLDigitalSubmissions@dot.gov describing your problem. NTL staff will do its best to assist you at that time.
  
  
• Format:
  ZIP
• Funding:
  69A3551747114, 69A3552344814
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:a566e3e2b2474fc997a930615c6bef1f915698cf18e193dc912b31521311e63c2802212bf5aba81853fa43d7adea2555e18de66cc36cd85f5bc375bf938bd091
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/86199/dot_86199_DS1.zip
• File Type:
  [ZIP - 388.81 KB ]