Ridesharing built on
trust, not just proximity.

The Problem

Low-income workers face a transportation gap that existing ridesharing platforms weren't designed to close. Uber and Lyft are priced for discretionary trips. Transit is underfunded and unreliable in the corridors that matter most. The gap: a commuter-to-commuter model where neighbors share the same daily route — and have reason to trust each other.

Design Approach

Contextual inquiry with low-income commuters surfaced trust and price transparency as the two non-negotiable constraints. People were willing to share rides with neighbors they didn't know well — but only with enough visible verification to feel safe.

The information architecture was structured around route-matching rather than on-demand pickup: users set their regular commute, and the system surfaces compatible neighbors. This reduced cognitive load on both sides and made the recurring relationship — rather than the one-time trip — the product.

Key Design Decisions

Community verification was the trust layer: workplace affiliation, route history, and mutual connections all contributed to a trust score that felt earned rather than algorithmic. Pricing was a flat contribution model — no surge, no ambiguity. Driver and rider were peers, not service provider and customer.

Skills Applied

Contextual Inquiry · Affinity Mapping · Information Architecture · Interaction Design · Prototyping · Trust UX