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Traffic Modeling

  • Tags:
  • Rail
  • Rail Safety
  • Traffic delay
  • Traffic Modeling

The Data Let’s start with the data. For this blog, I’m using 91 days of train and traffic data collected by TRAINFO at the Waverley St rail crossing in Winnipeg, Manitoba. We recorded the start and end time of every rail crossing blockage using our trackside, train detection sensors and measured the unique travel time […]

  • Tags:
  • Traffic
  • Traffic delay
  • Traffic Modeling

Similarity #1: Relatively small, isolated issues within a much larger system. Kidney stones are small compared to the entire body and isolated to a specific part within the body; the kidney. Traffic issues at rail crossings are small compared to issues across the entire road network and isolated to specific areas around rail crossings. Similarity […]

  • Tags:
  • Rail Safety
  • Traffic congestion
  • Traffic delay
  • Traffic Modeling

First, it’s important to understand that traffic delay at rail crossings comprises two periods: (1) delays that occur while the train is occupying the crossing (the blockage period) and (2) delays that occur after the train has cleared the crossing (the recovery period). It turns out that 1/3 of traffic delay occurs during the blockage […]

  • Tags:
  • Delay
  • Rail
  • Traffic
  • Traffic delay
  • Traffic Modeling

In 2017, the City of Winnipeg wanted to get some solid numbers about how much traffic was actually delayed at this crossing. The City approached TRAINFO and asked for our help. We happily agreed and used it as an opportunity to compare the conventional modeling method and TRAINFO’s new measurement method for estimating traffic delay […]

  • Tags:
  • Delay
  • Rail
  • Traffic
  • Traffic delay
  • Traffic Modeling

Modeling Traffic Delay at Rail Crossings How traffic models work The modeling approach applies traffic engineering theories to estimate traffic delays at rail crossings. Due to insufficient rail crossing blockage data and travel speed data, this approach relies on many incorrect assumptions [2]. Basically, models assume traffic volumes, hourly distribution, speed (and other traffic characteristics), vehicle […]