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Understanding and Using New Data Sources to Address Urban and Metropolitan Freight Challenges

National Cooperative Freight Research Program (NCFRP) Project 49

  • Urban and Metropolitan Challenges
    • Congestion
    • Last-Mile Access
    • Final 50-feet Access
    • Land Use
    • Truck Parking
    • Case Studies
  • Emerging Data Sources
    • GNSS/GPS
    • Radar
    • Wireless Address Matching
    • Administrative Records
    • Cellular/GSM
    • Induction Loops
    • LIDAR
    • Computer Vision
  • Analytical Approaches
    • Speed
    • Location
    • Re-identification
    • Classification
  • Stewardship Principles
    • Transparency and Openness
    • Purpose Specification
    • Data Minimization
    • Data Quality and Accuracy
    • Accountability
    • Security
    • Data Management
  • Resources
    • Source Use Concept Map
    • Case Studies
    • Previous NCFRP Projects
    • Glossary
    • Sources Cited
Home » Analytical Approaches » Classification

Classification

Classification refers to the act of categorizing vehicles (such as cars versus trucks) based on their physical characteristics such as shape, size, weight, and the number of axles. Understanding the distribution of different vehicle types on road networks can help planners design a transportation system based on users’ needs. Land use planning, traffic signal design, emission analysis, traffic regulations, and infrastructure performance analysis are some of the topics that can be informed by vehicle classification information, and these topics are relevant to the urban and metropolitan freight challenges of last-mile access, last 50-feet access, land use conflicts, and congestion.

The methodology used for vehicle classification depends on the objective of a study and the desired level of details. For instance, while regulatory agencies classify the vehicles based on their body type, engine, type of fuel, and environmental emission, traffic signal design and infrastructure performance studies mostly categorize the traffic based on the number of axles, weight, length, and other similar unique characteristics.

The following is a list of data sources used for obtaining commercial vehicle classification information. Each link provides a brief introduction to the data source and its relevant vehicle classification methodologies.

Inductive Loop Detectors
RADAR
LiDAR
Computer Vision

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  • Location
  • Re-identification
  • Classification

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