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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>MTA Data Analysis - Evidence-Based Transportation Policy</title>
<link rel="stylesheet" href="styles.css">
</head>
<body>
<!-- Navigation -->
<nav class="navbar">
<div class="nav-container">
<div class="nav-logo">
<h2>MTA Data Analysis</h2>
</div>
<ul class="nav-menu">
<li class="nav-item">
<a href="#home" class="nav-link">Home</a>
</li>
<li class="nav-item">
<a href="#work" class="nav-link">Our Work</a>
</li>
<li class="nav-item">
<a href="#about" class="nav-link">About Us</a>
</li>
<li class="nav-item">
<a href="#video" class="nav-link">Video</a>
</li>
</ul>
</div>
</nav>
<!-- Home Section -->
<section id="home" class="hero">
<div class="hero-content">
<h1>Evidence-Based Transportation Policy</h1>
<p class="hero-subtitle">Analyzing MTA performance through data-driven insights and machine learning</p>
</div>
</section>
<!-- ACE vs Non-ACE Animation Section -->
<section class="animation-section">
<div class="container">
<div class="anim-track">
<div class="label">ACE</div>
<div class="track blue" aria-label="ACE service track with stops">
<div class="stops">
<span class="stop"></span>
<span class="stop"></span>
<span class="stop"></span>
<span class="stop"></span>
<span class="stop"></span>
<span class="stop"></span>
</div>
<div class="indicator ace" aria-hidden="true"></div>
</div>
</div>
<div class="anim-track">
<div class="label">Non-ACE</div>
<div class="track gray" aria-label="Non-ACE service track with stops">
<div class="stops">
<span class="stop"></span>
<span class="stop"></span>
<span class="stop"></span>
<span class="stop"></span>
<span class="stop"></span>
<span class="stop"></span>
</div>
<div class="indicator nonace" aria-hidden="true"></div>
</div>
</div>
</div>
</section>
<!-- Our Work Section -->
<section id="work" class="work-section">
<div class="container">
<h2>Our Analysis</h2>
<p class="section-intro">
The graphs collectively tell a story of evidence-based policy implementation that worked, but wasn't scaled sufficiently.
The transportation authority correctly identified struggling routes, deployed a targeted intervention that showed measurable
results even after controlling for selection bias, and created a replicable model for future expansion.
</p>
<!-- ACE Route Selection Carousel -->
<div class="map-carousel ace-carousel">
<div class="carousel-header">
<h3>How Were the ACE Routes Chosen?</h3>
<p class="carousel-subtitle">Data-driven selection factors from 64 implemented routes (2019-2025)</p>
</div>
<div class="carousel-viewport">
<button class="carousel-btn prev" aria-label="Previous slide">❮</button>
<div class="carousel-track">
<!-- Slide 1 -->
<div class="carousel-slide" data-caption="Cost-benefit analysis of interventions">
<div class="slide-content">
<img src="images/image8.png" alt="Cost-benefit analysis of interventions">
<div class="slide-text">
<h4>Pre-ACE Speed Dominates Selection</h4>
<p>Pre-ACE speed is the strongest predictor of route selection with an importance score of 0.5294, showing that routes with lower speeds are prioritized for enforcement. This data-driven approach targets routes where speed enforcement would be most impactful.</p>
</div>
</div>
</div>
<!-- Slide 2 -->
<div class="carousel-slide" data-caption="Data preprocessing pipeline">
<div class="slide-content">
<img src="images/terminal1.png" alt="Data preprocessing pipeline">
<div class="slide-text">
<h4>Secondary Selection Factors</h4>
<p>Express service availability (0.1996) and route length (0.1315) are secondary factors in ACE selection. Geographic location has minimal influence, demonstrating that ACE deployment follows evidence-based criteria rather than political or demographic considerations.</p>
</div>
</div>
</div>
<!-- Slide 3 -->
<div class="carousel-slide" data-caption="Model comparison results">
<div class="slide-content">
<img src="images/terminal14.png" alt="Model comparison results">
<div class="slide-text">
<h4>Evidence-Based Deployment Strategy</h4>
<p>The analysis demonstrates that ACE deployment follows a systematic, data-driven approach targeting routes where speed enforcement would be most impactful. This validates the MTA's evidence-based policy implementation strategy.</p>
</div>
</div>
</div>
</div>
<button class="carousel-btn next" aria-label="Next slide">❯</button>
</div>
<div class="carousel-caption">
<span class="carousel-index">1 / 3</span>
<span class="carousel-text">Cost-benefit analysis of interventions</span>
</div>
<div class="carousel-dots" aria-label="Carousel Pagination"></div>
</div>
<!-- ACE Impact Analysis Carousel -->
<div class="map-carousel ace-carousel">
<div class="carousel-header">
<h3>How Do ACE Routes Impact the Speed of Bus Routes?</h3>
<p class="carousel-subtitle">Before-and-after analysis of ACE effectiveness on bus speeds</p>
</div>
<div class="carousel-viewport">
<button class="carousel-btn prev" aria-label="Previous slide">❮</button>
<div class="carousel-track">
<!-- Slide 1 -->
<div class="carousel-slide" data-caption="Geographic performance variations">
<div class="slide-content">
<img src="images/image6.png" alt="Geographic performance variations">
<div class="slide-text">
<h4>ACE Routes Show Consistent Speed Improvements</h4>
<p>ACE routes increased from 7.79 to 8.35 mph (+0.56 mph or +7.2%), demonstrating measurable speed improvements across different geographic areas and route types.</p>
</div>
</div>
</div>
<!-- Slide 2 -->
<div class="carousel-slide" data-caption="Predicted uplift ranking of candidate routes">
<div class="slide-content">
<img src="images/image7.png" alt="Predicted uplift ranking of candidate routes">
<div class="slide-text">
<h4>Non-ACE Routes Show Slight Decline</h4>
<p>Non-ACE routes decreased slightly (-0.27 mph or -2.7%), yielding a raw ACE effect of +0.83 mph when compared directly to ACE routes.</p>
</div>
</div>
</div>
<!-- Slide 3 -->
<div class="carousel-slide" data-caption="Statistical significance testing">
<div class="slide-content">
<img src="images/image9.png" alt="Statistical significance testing">
<div class="slide-text">
<h4>Bias Correction Reveals True Impact</h4>
<p>Propensity score matching was used to create comparable control groups, reducing the bias-corrected effect to +0.15 mph, providing a more accurate measure of ACE's true impact.</p>
</div>
</div>
</div>
<!-- Slide 4 -->
<div class="carousel-slide" data-caption="Model performance metrics">
<div class="slide-content">
<img src="images/terminal5.png" alt="Model performance metrics">
<div class="slide-text">
<h4>Varying Effectiveness Across Route Clusters</h4>
<p>The analysis reveals varying effectiveness across route clusters, with some groups showing substantial improvements (up to 18.84%) while faster routes showed minimal change.</p>
</div>
</div>
</div>
<!-- Slide 5 -->
<div class="carousel-slide" data-caption="Statistical significance testing">
<div class="slide-content">
<img src="images/terminal8.png" alt="Statistical significance testing">
<div class="slide-text">
<h4>Statistical Validation of Results</h4>
<p>Rigorous statistical testing confirms the significance of ACE effects, validating the evidence-based approach and supporting continued expansion of the program.</p>
</div>
</div>
</div>
<!-- Slide 6 -->
<div class="carousel-slide" data-caption="Final recommendations generation">
<div class="slide-content">
<img src="images/terminal19.png" alt="Final recommendations generation">
<div class="slide-text">
<h4>CUNY-Area Routes Excel Under ACE</h4>
<p>CUNY-area routes performed particularly well under ACE implementation, demonstrating the program's effectiveness in serving educational communities and supporting student transportation needs.</p>
</div>
</div>
</div>
</div>
<button class="carousel-btn next" aria-label="Next slide">❯</button>
</div>
<div class="carousel-caption">
<span class="carousel-index">1 / 6</span>
<span class="carousel-text">Geographic performance variations</span>
</div>
<div class="carousel-dots" aria-label="Carousel Pagination"></div>
</div>
<!-- Speed Prediction Analysis Carousel -->
<div class="map-carousel ace-carousel">
<div class="carousel-header">
<h3>What Predicts Bus Speed Performance?</h3>
<p class="carousel-subtitle">Random Forest analysis of speed prediction factors</p>
</div>
<div class="carousel-viewport">
<button class="carousel-btn prev" aria-label="Previous slide">❮</button>
<div class="carousel-track">
<!-- Slide 1 -->
<div class="carousel-slide" data-caption="Route clustering analysis">
<div class="slide-content">
<img src="images/image3.png" alt="Route clustering analysis">
<div class="slide-text">
<h4>Pre-ACE Speed Dominates All Predictions</h4>
<p>Pre-ACE speed overwhelmingly dominates predictions with an importance score of 0.9687, meaning baseline speed is the strongest predictor of future performance regardless of ACE implementation.</p>
</div>
</div>
</div>
<!-- Slide 2 -->
<div class="carousel-slide" data-caption="Performance baseline establishment">
<div class="slide-content">
<img src="images/terminal16.png" alt="Performance baseline establishment">
<div class="slide-text">
<h4>Other Factors Have Minimal Influence</h4>
<p>All other factors have minimal influence, with Staten Island location (0.0092), route length (0.0082), and various borough indicators showing only marginal predictive power. This indicates that bus speeds are highly persistent over time.</p>
</div>
</div>
</div>
</div>
<button class="carousel-btn next" aria-label="Next slide">❯</button>
</div>
<div class="carousel-caption">
<span class="carousel-index">1 / 2</span>
<span class="carousel-text">Route clustering analysis</span>
</div>
<div class="carousel-dots" aria-label="Carousel Pagination"></div>
</div>
<!-- CUNY Student Benefits Carousel -->
<div class="map-carousel ace-carousel">
<div class="carousel-header">
<h3>Why CUNY Students Need ACE Expansion</h3>
<p class="carousel-subtitle">Analysis of ACE benefits for student transportation</p>
</div>
<div class="carousel-viewport">
<button class="carousel-btn prev" aria-label="Previous slide">❮</button>
<div class="carousel-track">
<!-- Slide 1 -->
<div class="carousel-slide" data-caption="Time series performance trends">
<div class="slide-content">
<img src="images/image4.png" alt="Time series performance trends">
<div class="slide-text">
<h4>Low ACE Coverage on CUNY Routes</h4>
<p>Currently, only 16.7% of CUNY routes have ACE, while CUNY campuses are concentrated in slower-speed boroughs like Manhattan (7.1 mph average) compared to Staten Island (13.6 mph).</p>
</div>
</div>
</div>
<!-- Slide 2 -->
<div class="carousel-slide" data-caption="CUNY coverage and performance summary">
<div class="slide-content">
<img src="images/image10.png" alt="CUNY coverage and performance summary">
<div class="slide-text">
<h4>High-Potential Routes Identified</h4>
<p>Using predictive models, the analysis identifies high-potential routes including M9 (BMCC), B11 (Brooklyn College), and Q34 (Queens College), which could see 0.5-0.6 mph speed improvements with ACE implementation.</p>
</div>
</div>
</div>
<!-- Slide 3 -->
<div class="carousel-slide" data-caption="Impact measurement protocol and Quality assurance validation">
<div class="slide-content">
<div style="display: flex; gap: 1rem; max-width: 50%;">
<img src="images/terminal17.png" alt="Impact measurement protocol" style="max-width: 48%;">
<img src="images/terminal18.png" alt="Quality assurance validation" style="max-width: 48%;">
</div>
<div class="slide-text">
<h4>Sustained Improvements Confirmed</h4>
<p>Historical data shows some routes experienced COVID-related slowdowns but have recovered, while 2025 post-ACE data confirms sustained improvements, suggesting ACE expansion could provide consistent transportation benefits for students currently experiencing the city's slowest bus speeds.</p>
</div>
</div>
</div>
</div>
<button class="carousel-btn next" aria-label="Next slide">❯</button>
</div>
<div class="carousel-caption">
<span class="carousel-index">1 / 3</span>
<span class="carousel-text">Time series performance trends</span>
</div>
<div class="carousel-dots" aria-label="Carousel Pagination"></div>
</div>
<!-- Violations Analysis Carousel -->
<div class="map-carousel ace-carousel">
<div class="carousel-header">
<h3>What Else is Slowing Down MTA Buses?</h3>
<p class="carousel-subtitle">Analysis of violations among exempt vehicles</p>
</div>
<div class="carousel-viewport">
<button class="carousel-btn prev" aria-label="Previous slide">❮</button>
<div class="carousel-track">
<!-- Slide 1 -->
<div class="carousel-slide" data-caption="Long-term impact assessment">
<div class="slide-content">
<img src="images/terminal22.png" alt="Long-term impact assessment">
<div class="slide-text">
<h4>High Rate of Repeat Offenders</h4>
<p>The study found 46.9% of exempt vehicles are repeat offenders, with 6,107 chronic offenders (25+ violations), indicating widespread abuse of exempt privileges.</p>
</div>
</div>
</div>
<!-- Slide 2 -->
<div class="carousel-slide" data-caption="Implementation success metrics">
<div class="slide-content">
<img src="images/terminal24.png" alt="Implementation success metrics">
<div class="slide-text">
<h4>Geographic Hotspots Identified</h4>
<p>Violations concentrate in 5 geographic hotspots, primarily in the Bronx and Manhattan, creating systematic bottlenecks that slow down bus operations.</p>
</div>
</div>
</div>
<!-- Slide 3 -->
<div class="carousel-slide" data-caption="Future expansion planning">
<div class="slide-content">
<img src="images/terminal25.png" alt="Future expansion planning">
<div class="slide-text">
<h4>Emergency Vehicles Lead Violations</h4>
<p>Emergency vehicles lead in total violations (265,519) followed by commercial vehicles (257,374), suggesting need for better compliance monitoring.</p>
</div>
</div>
</div>
<!-- Slide 4 -->
<div class="carousel-slide" data-caption="Continuous improvement framework">
<div class="slide-content">
<img src="images/terminal26.png" alt="Continuous improvement framework">
<div class="slide-text">
<h4>CUNY Routes Heavily Impacted</h4>
<p>CUNY routes experienced 121,278 violations across 32,476 unique vehicles, with M101 showing the highest count, directly affecting student transportation.</p>
</div>
</div>
</div>
<!-- Slide 5 -->
<div class="carousel-slide" data-caption="Implementation roadmap">
<div class="slide-content">
<img src="images/image11.png" alt="Implementation roadmap">
<div class="slide-text">
<h4>Targeted Enforcement Strategy</h4>
<p>The analysis recommends reviewing exempt status for chronic offenders and targeting enforcement at identified hotspots to reduce systematic violations.</p>
</div>
</div>
</div>
<!-- Slide 6 -->
<div class="carousel-slide" data-caption="Performance monitoring dashboard">
<div class="slide-content">
<img src="images/image12.png" alt="Performance monitoring dashboard">
<div class="slide-text">
<h4>Progressive Penalty Systems</h4>
<p>Implementing progressive penalty systems can address widespread abuse of exempt privileges and improve overall bus speed performance.</p>
</div>
</div>
</div>
<!-- Slide 7 -->
<div class="carousel-slide" data-caption="Route selection criteria">
<div class="slide-content">
<img src="images/image13.png" alt="Route selection criteria">
<div class="slide-text">
<h4>Systematic Compliance Monitoring</h4>
<p>Enhanced monitoring and enforcement of exempt vehicle privileges can significantly improve bus speeds by reducing violations that cause delays.</p>
</div>
</div>
</div>
<!-- Slide 8 -->
<div class="carousel-slide" data-caption="Bias correction methodology">
<div class="slide-content">
<img src="images/image14.png" alt="Bias correction methodology">
<div class="slide-text">
<h4>Comprehensive Solution Approach</h4>
<p>Addressing exempt vehicle violations through targeted enforcement, hotspot monitoring, and progressive penalties can create a comprehensive solution to improve MTA bus speeds.</p>
</div>
</div>
</div>
</div>
<button class="carousel-btn next" aria-label="Next slide">❯</button>
</div>
<div class="carousel-caption">
<span class="carousel-index">1 / 8</span>
<span class="carousel-text">Long-term impact assessment</span>
</div>
<div class="carousel-dots" aria-label="Carousel Pagination"></div>
</div>
<!-- Machine Learning Validity Carousel -->
<div class="map-carousel ace-carousel">
<div class="carousel-header">
<h3>Machine Learning Validity</h3>
<p class="carousel-subtitle">ML models to predict bus speeds and evaluate ACE effectiveness</p>
</div>
<div class="carousel-viewport">
<button class="carousel-btn prev" aria-label="Previous slide">❮</button>
<div class="carousel-track">
<!-- Slide 1 -->
<div class="carousel-slide" data-caption="Pre-treatment speed distribution">
<div class="slide-content">
<img src="images/image1.png" alt="Pre-treatment speed distribution">
<div class="slide-text">
<h4>Comprehensive Model Training</h4>
<p>We trained four different types of models on data from 330 bus routes, using previous speeds, route characteristics, and location information to make predictions about bus performance.</p>
</div>
</div>
</div>
<!-- Slide 2 -->
<div class="carousel-slide" data-caption="Model performance summary">
<div class="slide-content">
<img src="images/image2.png" alt="Model performance summary">
<div class="slide-text">
<h4>Strong Model Performance</h4>
<p>All the models performed quite well, with the linear regression model coming out slightly ahead - it could predict speeds with about 85% accuracy and typical errors of less than 1 mph.</p>
</div>
</div>
</div>
<!-- Slide 3 -->
<div class="carousel-slide" data-caption="Route complexity and express designation features">
<div class="slide-content">
<img src="images/image5.png" alt="Route complexity and express designation features">
<div class="slide-text">
<h4>Feature Engineering Success</h4>
<p>The models successfully incorporated multiple data sources including route characteristics, geographic information, and historical performance to create reliable predictions.</p>
</div>
</div>
</div>
<!-- Slide 4 -->
<div class="carousel-slide" data-caption="Matched control group analysis">
<div class="slide-content">
<img src="images/terminal7.png" alt="Matched control group analysis">
<div class="slide-text">
<h4>Rigorous Validation Methods</h4>
<p>Using matched control group analysis, we ensured that our models could accurately evaluate whether ACE actually works by controlling for selection bias and other confounding factors.</p>
</div>
</div>
</div>
<!-- Slide 5 -->
<div class="carousel-slide" data-caption="Route ranking algorithm">
<div class="slide-content">
<img src="images/terminal9.png" alt="Route ranking algorithm">
<div class="slide-text">
<h4>Automated Route Ranking</h4>
<p>The machine learning models enable automated ranking of routes by improvement potential, providing data-driven recommendations for ACE implementation.</p>
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<div class="carousel-slide" data-caption="Deployment readiness check">
<div class="slide-content">
<img src="images/terminal15.png" alt="Deployment readiness check">
<div class="slide-text">
<h4>Deployment Readiness Validation</h4>
<p>Comprehensive deployment readiness checks ensure all systems are ready for ACE implementation, with models validated across different scenarios and route types.</p>
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<div class="carousel-slide" data-caption="Feature importance analysis">
<div class="slide-content">
<img src="images/terminal13.png" alt="Feature importance analysis">
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<h4>Feature Importance Insights</h4>
<p>Feature importance analysis reveals which factors most strongly predict bus speeds, helping identify the most effective strategies for improving transportation performance.</p>
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<span class="carousel-index">1 / 7</span>
<span class="carousel-text">Pre-treatment speed distribution</span>
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<div class="carousel-dots" aria-label="Carousel Pagination"></div>
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<!-- Solution Carousel -->
<div class="map-carousel ace-carousel">
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<h3>Solution</h3>
<p class="carousel-subtitle">Targeted ACE implementation and exempt vehicle monitoring</p>
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<button class="carousel-btn prev" aria-label="Previous slide">❮</button>
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<div class="carousel-slide" data-caption="Stakeholder reporting dashboard">
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<img src="images/terminal27.png" alt="Stakeholder reporting dashboard">
<div class="slide-text">
<h4>Targeted ACE Implementation</h4>
<p>Implement ACE to the M9, B11, and Q34 routes, as they had the greatest prediction of speed improvement. These high-potential routes will provide the most significant benefits for CUNY students.</p>
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<!-- Slide 2 -->
<div class="carousel-slide" data-caption="Final system validation">
<div class="slide-content">
<img src="images/terminal28.png" alt="Final system validation">
<div class="slide-text">
<h4>Exempt Vehicle Monitoring</h4>
<p>Review exempt status for chronic violation offenders and implement monitoring to ensure exempt vehicles are complying with regulations. By implementing both solutions, bus routes can be faster and more reliable for CUNY students.</p>
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<span class="carousel-text">Stakeholder reporting dashboard</span>
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<div class="carousel-dots" aria-label="Carousel Pagination"></div>
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<!-- Map Carousel (moved below graphs) -->
<div class="map-carousel">
<div class="carousel-header">
<h3>ACE Enforcement (Pre-ACE vs Post-ACE) Maps by Borough</h3>
<p class="carousel-subtitle">Use arrows or keyboard ← → to navigate</p>
</div>
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<button class="carousel-btn prev" aria-label="Previous slide">❮</button>
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<!-- Brooklyn slide -->
<div class="carousel-slide" data-caption="Brooklyn: ACE routes, speed scale, and school ACE routes">
<div class="slide-grid">
<div class="panel panel-main" data-label="Brooklyn ACE routes">
<img src="images/bklnacemap.png" alt="Brooklyn ACE Map">
<div class="overlay"><span>Brooklyn ACE routes</span></div>
</div>
<div class="panel-column">
<div class="panel panel-top" data-label="Brooklyn speed scale">
<img src="images/bklnscale.png" alt="Brooklyn Speed Scale">
<div class="overlay"><span>Brooklyn speed scale</span></div>
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<div class="panel panel-bottom" data-label="Brooklyn ACE routes near colleges">
<img src="images/bklnschoolacemap.png" alt="Brooklyn ACE School Map">
<div class="overlay"><span>Brooklyn ACE routes near colleges</span></div>
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</div>
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<!-- Bronx slide -->
<div class="carousel-slide" data-caption="Bronx: ACE routes, speed scale, and school ACE routes">
<div class="slide-grid">
<div class="panel panel-main" data-label="Bronx ACE routes">
<img src="images/bxacemap.png" alt="Bronx ACE Map">
<div class="overlay"><span>Bronx ACE routes</span></div>
</div>
<div class="panel-column">
<div class="panel panel-top" data-label="Bronx speed scale">
<img src="images/bxscale.png" alt="Bronx Speed Scale">
<div class="overlay"><span>Bronx speed scale</span></div>
</div>
<div class="panel panel-bottom" data-label="Bronx ACE routes near colleges">
<img src="images/bxschoolacemap.png" alt="Bronx ACE School Map">
<div class="overlay"><span>Bronx ACE routes near colleges</span></div>
</div>
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<!-- Manhattan slide -->
<div class="carousel-slide" data-caption="Manhattan: ACE routes, speed scale, and school ACE routes">
<div class="slide-grid">
<div class="panel panel-main" data-label="Manhattan ACE routes">
<img src="images/manacemap.png" alt="Manhattan ACE Map">
<div class="overlay"><span>Manhattan ACE routes</span></div>
</div>
<div class="panel-column">
<div class="panel panel-top" data-label="Manhattan speed scale">
<img src="images/manscale.png" alt="Manhattan Speed Scale">
<div class="overlay"><span>Manhattan speed scale</span></div>
</div>
<div class="panel panel-bottom" data-label="Manhattan ACE routes near colleges">
<img src="images/manschoolacemap.png" alt="Manhattan ACE School Map">
<div class="overlay"><span>Manhattan ACE routes near colleges</span></div>
</div>
</div>
</div>
</div>
<!-- Queens slide -->
<div class="carousel-slide" data-caption="Queens: ACE routes, speed scale, and school ACE routes">
<div class="slide-grid">
<div class="panel panel-main" data-label="Queens ACE routes">
<img src="images/qnsacemap.png" alt="Queens ACE Map">
<div class="overlay"><span>Queens ACE routes</span></div>
</div>
<div class="panel-column">
<div class="panel panel-top" data-label="Queens speed scale">
<img src="images/qnsscale.png" alt="Queens Speed Scale">
<div class="overlay"><span>Queens speed scale</span></div>
</div>
<div class="panel panel-bottom" data-label="Queens ACE routes near colleges">
<img src="images/qnsschoolacemap.png" alt="Queens ACE School Map">
<div class="overlay"><span>Queens ACE routes near colleges</span></div>
</div>
</div>
</div>
</div>
<!-- Staten Island slide -->
<div class="carousel-slide" data-caption="Staten Island: ACE routes and speed scale">
<div class="slide-grid">
<div class="panel panel-main" data-label="Staten Island ACE routes">
<img src="images/stnacemap.png" alt="Staten Island ACE Map">
<div class="overlay"><span>Staten Island ACE routes</span></div>
</div>
<div class="panel-column single-center">
<div class="panel panel-top" data-label="Staten Island speed scale">
<img src="images/stnscale.png" alt="Staten Island Speed Scale">
<div class="overlay"><span>Staten Island speed scale</span></div>
</div>
</div>
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<span class="carousel-index">1 / 5</span>
<span class="carousel-text">Brooklyn: ACE routes, speed scale, and school ACE routes</span>
</div>
<div class="carousel-dots" aria-label="Carousel Pagination"></div>
</div>
<!-- CUNY Route Performance Summary -->
<div class="performance-summary">
<h3>CUNY Route Performance Summary</h3>
<div class="stats-grid stats-grid-4">
<div class="stat-card">
<h4>ML Model Accuracy</h4>
<div class="stat-number">85%</div>
<p>Predicts successful ACE targets</p>
</div>
<div class="stat-card">
<h4>CUNY Route Coverage</h4>
<div class="stat-number">16.7%</div>
<p>ACE enforcement on CUNY routes</p>
</div>
<div class="stat-card">
<h4>ACE Routes</h4>
<div class="stat-number">+10.1%</div>
<p>Improved from 7.6 to 8.3 mph (+0.7 mph)</p>
</div>
<div class="stat-card">
<h4>Net Advantage</h4>
<div class="stat-number">+0.2 mph</div>
<p>ACE provides +0.2 mph absolute difference over Non-ACE</p>
</div>
</div>
</div>
</div>
</section>
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<section id="about" class="about-section">
<div class="container">
<h2>About Us</h2>
<div class="about-content">
<div class="mission">
<h3>Our Mission</h3>
<p>
We are dedicated to using data science and machine learning to improve public transportation,
and more specifically, the ACE program through evidence-based policy analysis. Our work
focuses on identifying opportunities for meaningful improvements in MTA service delivery,
particularly for CUNY students.
</p>
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<img src="images/mtalogo.png" alt="MTA Logo">
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<p>Furkan Ay, Maida Kucevic, Efe Aslanertik, Halil Akca for MTA</p>
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