CTA Bus Queue Jump Signal Pilot

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Each capital project is measured on 15 evaluation metrics to better understand its impact on the region. Learn more about the metrics and see a legend for all measures here.

Click the circled (i) information button to read a definition of each metric and hover over the image to see more about each measure.

The degree to which a project improves regional access to the region’s key destinations. Including jobs, retail, healthcare, recreation, and education.

The project improvements to existing assets to make them partially or fully accessible. Including station/stop and area improvements, vehicle accessibility, and accessible communications.

The project impact to ratings from the FTA Transit Economic Requirements Model (TERM).

The project’s minor or major benefits to riders and what proportion of the agency’s riders will benefit from it.

The project impact on overall capacity, reflecting current and planned levels of utilization.

The project impact on reductions or offsets to greenhouse gas (GHG) emissions generated from transit operations.

Project impacts on land use and development, construction, and long-term jobs.

The distribution of project benefits to location(s) identified under the USDOT Justice40 Program.

The project impact to maintenance or improvement of exposure to risk for riders/employees and the project impact to security enhancement.

The project impact on operating costs.

The project impact to maintenance or improvement of exposure to risk for riders/employees and the project impact to security enhancement.

Project impact on maintenance or improvement of service speed and reliability, considering both direct and indirect impacts.

If required, whether or not the project complies with federal, state, local, or other regulatory mandates.

The project impact to climate benefits, such as a reduction in emissions, generated from mode shift to transit and away from private auto-use.

The project impact to average vehicle ages, compared with Service board benchmarks to prioritize replacing vehicles that are beyond their useful life.

Evaluation Metric Measure
Access to Key Destinations i
One green up arrow

Moderately improves Access to Key Destinations

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Accessibility Improvement(s) i
Not applicable symbol

Project is not related to accessibility

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Asset Condition (FTA TERM Rating) i
Not applicable symbol

Project does not have an asset rating

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Benefit to Riders i
Two green up arrows

Significant benefit to riders

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Capacity Benefit and Need i
Not applicable symbol

Not related to capacity of transit operations or facilities

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Climate Agency Operating Impacts i
Red line with arrows on each end

No reduction in emission

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Economic Impact i
Not applicable symbol

No economic impact

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Equity Based on Residential Geography i
Three green up arrows

Scores 6-8 in Justice40 metric 'Sum of Disadvantage Indicators'

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Impact on Customer and Employee Safety i
Not applicable symbol

Project has no impact on safety

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Impact on Operating Cost i
Not applicable symbol

No effect on operating cost or cost change undetermined

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Impact on System Security i
Not applicable symbol

Project does not impact security

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Impact to Service Speed/Reliability i
One green up arrow

Moderately improves current speed/reliability

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Regulatory Requirements i
Black x mark

No regulatory requirements met for this project

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Ridership/Mode Shift Impacts i
One green up arrow

Moderately improves transit ridership

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Vehicle Useful Life i
Not applicable symbol

Asset is not a vehicle with a useful life

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Project Description

The Bus Queue Jump Signal pilot proposal includes the design and installation of a pilot set of queue jump signals. This innovative project will expand on existing “smart intersection” technology to grant CTA buses early signal priority, allowing them to safely bypass traffic at intersections. Partnering with CTA on this project is the Chicago Department of Transportation (CDOT) and they have been implementing smart intersection technology throughout the city, which utilizes video detection to assess roadway usage and provide traffic counts, among other uses. This existing technology will be built upon, using components of machine learning, to identify CTA buses and communicate with the signal controller to provide a bus queue jump signal on a separate signal head. Through precisely targeting CTA buses, priority signals will only be granted when needed, ensuring an efficient use of signal time at the intersection.