Graduate student and Trailnet map pedestrian danger around Metrolink and bus stops

A Washington University graduate student and Trailnet representatives presented a GIS study to the Public Infrastructure and Utilities Committee mapping pedestrian and cyclist crashes near Metrolink stations and Metro bus stops.

The presenter, Griffin Lovato, described using Missouri State Highway Patrol STARS crash data and local transit stop locations to map crashes from two one‑year windows (Nov. 1, 2018–Nov. 1, 2019, and Nov. 1, 2023–Nov. 1, 2024). He said the analysis used kernel‑density mapping to highlight areas with higher crash concentrations and then measured an “accident per square mile” hazard for each transit node.

Why it matters: the study gives city planners a geographically specific view of where pedestrians and cyclists are being struck near public transit and highlights corridors and stops that could be prioritized for safety engineering, lighting upgrades or enforcement.

What the study found - Crash dates and method: Lovato used STARS crash records and applied kernel density to show where pedestrian and cyclist crashes concentrate. He compared the two one‑year windows to show trends and potential effects of interventions. - Lighting conditions: the STARS data include a “light condition” field. Lovato grouped crashes as daylight, dark but lit (artificial lighting present) and dark unlit. He said dark unlit crashes were the least common category in the dataset; most crashes near Metrolink stations were in daylight or at night with artificial lighting rather than in truly unlit, blackout conditions. - Geography of risk: Lovato identified higher concentrations of pedestrian/cyclist crashes in central city corridors (downtown and central south), Chippewa Street, Grand Boulevard, and the central West End. He also showed higher hazard ratings for bus stops in north St. Louis City and parts of north St. Louis County (Delwood, Ferguson, Jennings and nearby unincorporated areas).

Methodology and limits Lovato said STARS records do not include a lat/long for the crash; the dataset contains the recorded “AT” and “ON” street fields and other descriptive fields. For this project he used the nearest intersection/street location and kernel‑density smoothing rather than field‑level determinations of whether a crash occurred inside a crosswalk or on a sidewalk. He cautioned that the project was a capstone mapping and identification exercise, not a final engineering study with on‑the‑ground counts or design recommendations.

Presenters and roles - Charles Bryson of Trailnet introduced the presenters and said Trailnet and Washington University have a multi‑year partnership using GIS classes for real‑world projects. - Professor Doris Scott (WashU Continuing & Professional Studies) said the project was a collaboration with her GIS capstone students. - Lovato said his role was to identify locations for further study rather than prescribe engineering repairs.

What the committee heard from members Committee members praised the maps and asked for the presentation materials and underlying data. Lovato said the full project file is large (about 30 GB) and offered to make the project available via a hard drive or cloud link; he said he would provide a PowerPoint and could supply the dataset to the committee for review.

Next steps and caveats Lovato and Trailnet said the analysis is a starting point for targeted follow‑up: engineers or transit agencies could examine specific nodes, check crosswalks and lighting and consider targeted engineering, enforcement or pedestrian‑scale lighting changes. The STARS data do not include whether a pedestrian was in a marked crosswalk or on a sidewalk; that would require site visits or additional reporting details. Lovato and Trailnet encouraged city and transit staff to consider the mapped hotspots as candidates for further study.