Method establishes fair audit of urban transit station plans with shared data
Freeze, Validate, Report: Auditing Urban Station Plans with Common Evidence
Computers and Society
Summary
Comparing different plans for urban transit stations is tricky when each plan uses different data or ways to measure success. The authors offer a method to fix these differences by agreeing on a common way to pick trips, groups, and locations before scoring the plans. This approach helps ensure that when plans are evaluated, the differences really come from the plans themselves and not from how the comparison is done. They tested this method on plans in Porto and Chicago and showed how changing inputs can affect which plan looks best. Their method also provides tools and logs to keep the audit clear and repeatable.
What this means in practice
- •For transport planning teams: Evaluate competing urban transit station designs using a consistent and auditable comparison method to ensure fair and comparable scoring across plans.
- •For city infrastructure analysts: Use a standardized metric and validation approach to audit proposed station locations and access outcomes for better decision support under varying conditions.
Authors
Julian Teusch, Oliver Keszöcze
Abstract
Transport authorities comparing urban station plans need to distinguish plan differences from differences in evaluation inputs. Reconstructing spatial units, included trips, or candidate blocks from each plan's access outcomes can make scores incomparable. Freeze--Validate--Report fixes an evaluation contract: target trips, proxy groups, reporting cells, candidate pools, and a lexicographic selection rule. A two-point example shows that plan-specific observation selection can reverse the target mean ordering. We compare seven generators spanning clustering, facility location, fairness-oriented adaptations, and a grid control. All plans are scored on common validation evidence using endpoint distance: the sum of origin and destination distances to their nearest stations. A five-metric rule selects one plan for a single test report. In Porto, it selects IFkCO, an adaptation of individually fair $k$-center with outliers; test overall and worst-group 90th percentiles are 805 m and 872 m. In Chicago, it selects Grid; values in a later test window on the same day are 1404 m and 1656 m. Post hoc checks show input sensitivity: expanding candidates from 300 to 600 changes selection in both cities, while holding the hour fixed across three Chicago dates selects Priority. A proportional mean fairlet diagnostic shows that plan-specific proposal pools can change diagnostic ranks; admissibility and solver bounds apply only to the sampled pool. The package supplies code, hashes, decision logs, and proposal pools. We establish auditability within a declared contract, not stable performance after deployment; proxy definitions and metric priorities remain the authority's choices.