Green Street

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Inspiration

Built for the Jane Street Hoppers Challenge, Green Street was inspired by a classic economic problem: traditional corporate sustainability initiatives rely on weak moral nudges or empty pledges that fail to drive systemic behavior change. Inspired by quantitative market-making and game theory, we wanted to build an automated, data-driven incentive structure that treats carbon emissions like a dynamic market commodity—making sustainable choices economically rewarding and high-carbon commuting self-regulating.

What it does

Green Street is a gamified employee commute rewards bank and automated incentive-pricing web application.

Multi-Modal Route Planner: Employees search their home origin and compare live multi-modal routes (driving, bus, rail, subway, cycling, walking) to the office.
Transparent Carbon Accounting: Every route displays precise distance, travel time, estimated greenhouse gas emissions using official UK Government 2026 factors, and an expected credit change clearly highlighting Earn vs. Deduct.
Automated Market Maker (AMM): A firm-wide demand signal monitors yesterday's driving share and automatically scales driving penalties and active-travel bonuses for the following day.
Monthly Settlement & Perk Store: At month-end, positive credit surpluses sweep into a redeemable wallet where employees can spend their earned credits on high-value workplace perks like priority meeting room bookings or compute cluster priority tokens.

How we built it

Frontend & Architecture: Built as a blazing-fast single-page application using Vite and React 19 (JavaScript), styled with Tailwind CSS v4 for a sleek, quant-terminal aesthetic. Integrated the Google Maps JavaScript API and Routes API for live geocoding, autocomplete search, and dynamic route polylines.
The Scoring Engine: Developed a rigorous, isolated calculation engine backed strictly by official UK Government 2026 GHG conversion factors (e.g., average car = $0.16591\text{ kg CO}_2\text{e/km}$, London bus = $0.06360\text{ kg CO}_2\text{e/km}$).
$$\text{emissionsCharge} = K \times (M_{\text{car}} \cdot E_{\text{car}} + E_{\text{other}})$$$$\text{creditDelta} = \text{activeBonus} - \text{emissionsCharge}$$
Testing & Reliability: Protected calculation integrity with a robust test suite of 28 unit tests running via Vitest.

Challenges we ran into

API Data Normalization: Parsing deeply nested multi-modal transit responses from the Google Maps API (such as mixed walking, subway, and bus segments) and mapping them cleanly into our strict engine schema without losing distance precision or double-counting legs.
State & Transactional Boundaries: Maintaining an instantaneous, zero-backend in-memory React state that preserves strict ledger invariants, immutability on trip completion receipts, and seamless real-time recalculation when dynamic rate toggles are flipped.

Accomplishments that we're proud of

Successfully translating complex quantitative market-making concepts into an intuitive, gamified behavioral product that looks and feels like institutional software.
Achieving 100% test pass rates across our core scoring engine using official government emissions datasets.
Delivering a fully functional, end-to-end product loop—from live map routing and carbon ledger accounting to month-end wallet settlement and perk redemption—within a high-pressure hackathon timeframe.

What we learned

The immense power of combining rigorous regulatory data (UK Gov GHG factors) with responsive, game-theory-inspired user interfaces.
How dynamic pricing feedback loops can effectively alter human behavior when incentives are transparent, predictable, and automatically adjusted based on collective network data.

What's next for Green Street

Expanding pilot deployments to additional corporate office regions with localized conversion factor sets.
Integrating secure, automated first-party mobile background verification to transition from simulated trip completion to passive, reliable tracking.
Adding optional department-level leaderboards and automated corporate ESG reporting dashboards.