A SCOOT adaptive traffic signal control system provided a 12 to 21 percent savings in end-to-end travel times across a two-mile corridor in Ann Arbor, Michigan.

Evaluation of Split Cycle Offset Optimisation Technique (SCOOT) using big data sources before and after installation.

Date Posted
08/31/2017
Identifier
2017-B01178
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Ann Arbor SCOOT Mobility Study: Evaluating the SCOOT Adaptive Signal Control Technology Through the Use of Big Data

Summary Information

Adaptive traffic signal control systems offer cities and local governments a cost-effective and dynamic means to optimize traffic flow. These systems work alongside existing traffic control, incorporating real-time traffic movement data to continually optimize signal timing. Despite more than 200 system installations worldwide, there are few studies published about the effectiveness of these adaptive traffic control systems, such as SCOOT. The advent of "Big Data" technologies and methods makes possible a cost-effective way to study the effectiveness of traffic control systems. In Ann Arbor, Michigan, Siemens and its mobile data analytics partner, StreetLight Data, completed a test of the Siemens SCOOT adaptive traffic signal control system using these new techniques.



The Ann Arbor study took place along the city's Ellsworth Corridor, a two-mile stretch just a few miles south of the University of Michigan South Campus and Michigan Stadium. In November 2015, Ann Arbor extended its use of SCOOT to include this corridor. This corridor was well-timed and re-timed prior to the expansion of SCOOT. It experiences high volumes of traffic, is only a single lane in each direction, and is frequently used as a bypass by many drivers looking to avoid congestion on nearby Interstate 94.

METHODOLOGY

The study team used big data sources of detailed traffic information from aggregators like StreetLight Data to conduct a before-after study that used data as far back as a year before SCOOT installation. The team used a web application to generate custom mobility analytics and metrics. These metrics were derived from anonymous, archival GPS data that was originally recorded by smart phone apps and connected cars. More than 11,000 trips that traveled the entire length of the Ellsworth Corridor and an additional 30,000 trips that traveled on the corridor but did not go the full length were analyzed from the period of December 2014 through May 2016. Data were classified by five different time periods for both weekday and weekend traffic, including early morning and late night time periods.

FINDINGS

The results demonstrate the overall effectiveness of the adaptive traffic control system (SCOOT).

  • SCOOT reduced overall travel times by about 10 to 20 percent on the corridor (21 percent reduction on weekends, and a 12 percent reduction on average weekdays.)
  • SCOOT significantly increased the likelihood of meeting target times on a specific trip (such as, 3 minutes).
Goal Areas
Results Type
Deployment Locations