Woke up this morning and wrote myself some code

The dataset did not specify whether the moving violation was assessed through an automated process by traffic camera. In DC this is called Automated Traffic Enforcement (ATE). According to Open Data DC, 138 cameras are managed by the District Department of Transportation (DDOT). The cameras, which are scattered throughout the city, are used as a traffic calming measure and to “reduce traffic violations and, as a result, decrease the number of crashes, prevent injuries, and save lives.”

The camera-location dataset provides a column with the ATE Location which contains a mixed-case (and in some cases abbreviated) location of all 138 cameras reported by DDOT. Some features of most of these include:

Sample data from camera-location dataset
  • Block Number
  • Street Name
  • Quadrant
  • Direction (e.g. nw/b for ‘northwest bound’)

Another column contains the ATE Type of which there are three: Red Light Safety Camera Enforcement Sites, Speed Safety Camera Enforcement Sites, Stop Sign Safety Camera Enforcement Sites. All ATEs are active as of 7/8/2022.

The main dataset with tickets issued from 1/1/17-5/30/22 has a LOCATION column. A matching algorithm assigned the ATE Type to matching LOCATION strings in the data. Some minor data manipulation included making sure every entry was UPPERCASE. The algorithm assigned an ATE status to 4,807,080 out of 7,392,736 observed violations, or about 65%. The breakdown by ATE Type:

  • Speed Safety Camera Enforcement Sites: 4,175,335 (56% of total violations, 87% of ATE)
  • Red Light Safety Camera Enforcement Sites: 395,218 (5% of total violations, 8% of ATE)
  • Stop Sign Safety Camera Enforcement Sites: 236,527 (3% of total violations, 5% of ATE)

This assignment also revealed a pattern in ticket numbers, all of which began with either an ‘F’ or a ‘D.’ This was verified by spot checking recent ticket numbers on DC’s Pay Tickets website (https://dmv.dc.gov/service/pay-tickets).