By: Grace Young and David Wasserman, AICP, Alta
In the not too distant past, collecting a detailed sidewalk inventory for a mid-sized city would have taken several days and a sturdy pair of walking shoes. With the emergence of data products like Ecopia and Mapillary, a computer can provide that same data collection in a fraction of the time, known as a digital twin, no sneakers required. The world of artificial intelligence (AI)-derived data products is vast and ever-growing, but understanding how to leverage this data into practical planning applications that benefit communities can be daunting.
As Alta continues to expand the ways in which advanced data inventories can deepen and enhance analysis findings, let’s take a look at some of the recent applications of data in different contexts, from a school safety program, to a city-wide mobility plan, and a vision for more scenario-oriented complete streets planning.
Safety & Vision Zero
In Modesto, CA, the project team used AI-derived sidewalk and crosswalk data to bring a strong understanding of the existing infrastructure and how it relates to safety conditions near schools. The team found a relationship between school study areas with relatively high collision rates and those with relatively low levels of sidewalk completeness and greater distances between marked crossing opportunities. A deeper analysis of collisions examined the location of pedestrians when struck and found that when crossing the street outside of a crosswalk, two-thirds of fatal or severe pedestrian collisions occurred on road segments with greater than 800 feet between crossing opportunities.
Though existing infrastructure conditions are not typically the flashiest section of a safety report, this data is critically important to identify patterns and deficiencies that begin to inform not only where future infrastructure improvements should be targeted, but also the types of recommendations that are appropriate for addressing the existing safety challenges.
As safety professionals continue to consider how to build safe systems, these contextual databases are key to inform the proactive approaches that anticipate human error and inform safer street and intersection design.
Networks & Connectivity
By incorporating sidewalk and roadbed width information from Ecopia and speed limit data from Mapillary, the project team enhanced the accuracy of the transportation network inventory to provide comprehensive walk and bike level of traffic stress analyses for the City of Mt. Shasta, CA. Alta has developed methods to incorporate these findings into a connectivity analysis to account for network quality and coverage to produce an adjusted metric more representative of the connectivity experience of vulnerable users. Simply put, the ability to integrate digital inventories into our network analysis methodologies enabled the community to have a better understanding of pedestrian and bicycle comfort’s impact on multimodal connectivity.
Modal Network Planning & Complete Streets
How transportation professionals change their planning and processes to meet the needs of multiple road users and expanding considerations for streets is a complex challenge. Many regions and states are exploring the use of innovative modal network planning approaches to manage the conflicts and needs of different modes as part of a broader network. Our recent experience with Tucson highlights the challenges and opportunities to help choose between different modes comprehensively. When we think of streets in the context of how they are represented in a database, what often comes to mind is the humble street centerline. However, more often than not these databases are focused on routing for automobiles rather than on other types of multimodal infrastructure and width data that could inform what can fit. However, with digital twins of street right-of-ways, we have the opportunity to evaluate design changes in more iterative and scenario oriented ways. Some regions are already starting to develop HD Vector Maps of their infrastructure, such as Contra Costa County.
Tools like CityEngine’s Complete Street Rule, StreetMix, Remix Streets, and Beyond Typicals identify how we can communicate preliminary concepts for more complete streets. Alta envisions a future where these types of databases power smart digital twins of our streets that can be tied to performance measures, visualization software, and interactive editing tools that enable dynamic visualization and evaluation. This animation illustrates how this vision could work in the context of parametric design, where dynamic performance metrics and reports react to changes in a street’s configuration.
Digital Twins of our streets have numerous applications we are excited about, with achieving Vision Zero goals, better multimodal connectivity, and modal scenario planning just being the tip of the iceberg.
Learn more about Alta’s Civic Analytics practice, and how the team brings a community-focused perspective to digital transformation. For regular updates, sign up for our most recent news.
