Use Cases

About: As the city continued to see crashes resulting in severe outcomes, Madison Vision Zero, launched in 2020, strives to improve safety for everyone moving about the city, whether walking, biking, driving and riding transit; and to improve the identified high injury locations, all in an effort to prevent fatal crashes and severe injuries. Madison has the goal of making all its streets and intersections safer via ongoing improvements to infrastructure.

Challenge: Madison wanted to refine their data quality while being more proactive in their management of crash data, recommending specific investments, and monitoring progress.

Solution: CRASH reduces the time and cost needed for street safety analysis while deepening understanding of crash patterns and producing actionable insights for implementation. Gathering and analyzing accurate crash data using AI leads to improvements in city planning and safety outcomes on streets across the City. Citian successfully located 95% of crashes that were previously unmappable, and systematically corrected other issues with Madison’s crash data. The added digital layer allows Madison to work toward preventing more crashes by having complete crash data sets to analyze beforehand,data to make informed safety countermeasure decisions, and compelling visualizations to convey these insights. CRASH enables Madison staff to streamline safety analysis and planning, producing outputs to secure competitive grant funding.

About: Managing assets can be time consuming, but with ADAPT, cities are able to identify problem areas 20 times faster, operationalize their assets, and make immediate improvements to their infrastructure. Through sound infrastructure management and investment, cities can strengthen accessibility for pedestrians, maintain ADA compliance, and proactively make streets safer for all users

Challenge: Maintaining safe and accessible transportation infrastructure for vulnerable road users and those with impaired mobility can be resource and time intensive for cities. Collecting accurate and precise data remains a challenge for local transportation authorities.

Solution: Citian used a detailed LiDAR scan of approximately 300 miles of City streets and leveraged ADAPT’s artificial intelligence to automatically extract over 40,000 assets and their related measurements. Sidewalks, bike facilities, curb ramps, curbs, gutters, signage, road cross slopes, road striping, and more were captured, evaluated, and used to populate the comprehensive digital twin environment. City staff are able to leverage ADAPT to generate data-driven insights, prioritize budgets and capital planning, develop dashboards to monitor performance, visualize their system comprehensively, and process work orders. Helena uses insights generated in ADAPT to invest equitably across their pedestrian network, closing sidewalk gaps and addressing compliance challenges in priority areas.