SUMO-Based Traffic Simulation for Emergency Evacuation Optimization

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๐ŸšฆSUMO-Based Traffic Simulation for Emergency Evacuation Optimization

๐ŸŒŸ Key Highlights

  • ๐Ÿšจ 21% reduction in emergency vehicle travel time with Hybrid strategy
  • ๐Ÿš— 98.7% success rate for EV passage in critical scenarios
  • โš–๏ธ Balanced trade-off between emergency response and social traffic impact
  • ๐Ÿ–ฅ๏ธ High-performance simulation framework (SUMO + TraCI + Python)

๐Ÿ“Œ Introduction

๐Ÿ™๏ธ Urban Emergency Challenges

Threat TypeExamplesImpact
Natural DisastersEarthquakes, FloodsInfrastructure damage
Human-RelatedAccidents, Security threatsTraffic gridlock

๐Ÿ”ฌ Research Objectives

  1. Develop multi-modal evacuation platform
  2. Optimize emergency vehicle routing
  3. Enable data-driven decision making

๐ŸŽฏ Expected Outcomes
โœ” Reduced emergency response time
โœ” Improved evacuation efficiency
โœ” Enhanced urban resilience

๐Ÿ“Š Comparative Analysis

๐Ÿš‘ Emergency Vehicle Performance

โฑ๏ธ Performance Metrics Comparison

MetricBaselineDynamicHybridImprovement
Travel Time (s)139.8120.1110.3โ†“ 21%
Success Rate (%)84.695.298.7โ†‘ 14.1%
Social Delay (s)27.630.934.2โ†‘ 24%

๐Ÿ› ๏ธ Technical Implementation

๐Ÿ’ป System Architecture

graph TD
    A[SUMO Core] --> B[TraCI Interface]
    B --> C[Python Controller]
    C --> D[V2I Logic]
    D --> E[Signal Control]

โš™๏ธ Simulation Parameters

  • Hardware: i9-13900K, 64GB RAM
  • Software: SUMO 1.18.0, Python 3.11.6
  • Duration: 3,600s (1 hour)
  • Runs: 10 random seeds (101-110)

๐ŸŽฏ Key Findings

๐Ÿ† Optimal Strategy

{
  "mark": "point",
  "encoding": {
    "x": {"field": "EV Efficiency", "type": "quantitative"},
    "y": {"field": "Social Impact", "type": "quantitative"},
    "size": {"field": "Priority", "type": "quantitative"},
    "color": {"field": "Strategy", "type": "nominal"}
  }
}

Recommendation Hierarchy:

  1. Hybrid Strategy (High emergency priority)
  2. Dynamic V2I (Balanced approach)
  3. Baseline (Reference only)

๐Ÿ“ Conclusion

๐Ÿš€ Future Enhancements

  • ๐ŸŒ Multi-modal integration (pedestrians + vehicles)
  • ๐Ÿง  Enhanced human behavior modeling
  • ๐Ÿ“ฑ Real-time data streaming capability

Impact Statement:
"This framework can reduce emergency response time by up to 21%, potentially saving hundreds of lives in major urban disasters."

๐Ÿ›ก๏ธ Emergency Traffic Simulation System | ยฉ 2023 Urban Resilience Research Group

๐ŸŒŸ Key Highlights

Visual Enhancement Notes:

  1. Replace Vega-Lite JSON with actual charts in implementation
  2. Use consistent color scheme (#3498db blue, #2ecc71 green, #e74c3c red)
  3. Add institutional logo in footer if available
  4. Consider animated transitions between sections for presentation
  5. For printed version, use higher contrast colors

Recommended Font Pairing:

  • Headers: Montserrat Bold
  • Body: Open Sans Regular
  • Code: Fira Code
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