Pedestrian Facilities

Increase number of crosswalks enhanced annually

This indicator measures crosswalks enhanced by fiscal year.Explore the data
crosswalks enhanced since 2013
Current
556crosswalks enhanced since 2013
Dec 2020 Target
Goal Period ended December 2020
Show chart
    Added on August 23 2019, after the goal ended.

            What is this indicator?

            This indicator measures the number of crosswalks enhanced(re-striped) each fiscal year.

            Why is it important?

            The City of Santa Monica is committed to promoting a safe and walkable community that meets the needs of its residents and visitors.Making conditions safer for walking will encourage a greater number of people to utilize healthy, sustainable modes of transportation. Walkable communities are a key component of the Santa Monica Land Use and Circulation Element (LUCE). LUCE is part of the Santa Monica General Plan, which establishes the City’s land use, urban design, and transportation vision.

            Pedestrian trips have been on an upward trajectory, with a spike in peak PM trips from 33,412 in 2011 to 41,088 in 2013. This increase is beneficial for the community and calls for enhanced commitments to pedestrian safety.

            Re-striping crosswalks enhances visibility, thus reducing the number of pedestrian collisions and fatalities.

            How are we doing?

            As part of a multi-phase Crosswalk Renewal Program, 556 crosswalks have been enhanced since 2012. Phase 3 of the program (FY2014-2015)allocated $300,000 to upgrade crosswalks, primarily focusing on school-zone/yellow crosswalks. Phase 4 (FY 2015-2016) includes an additional$300,000, with a future goal of upgrading 100 crosswalk segments per year. The 2020 target is an annual increase in crosswalk enhancements.

            How can we help?

      Data Governance

      describes the quality of the data itself. Governance issues generally indicate that the data source is considered incomplete or unreliable.

      Model Health

      describes the quality of the predictive model. If the model health is poor, the trend prediction should not be trusted.

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