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Analysis of Traffic Congestion in North Campus, Delhi University Using Continuous Time Models

Siddhartha Mahajan, Harsh Raj, Sonam Tanwar

TL;DR

This paper analyzes traffic congestion on North Campus, Delhi University, where mixed vehicle, pedestrian, and event-driven surges create delays and emissions. It adopts a continuous-time, event-driven simulation framework implemented in UXSim, calibrated with field survey data, to capture transient queue dynamics more accurately than discrete-time approaches. The study identifies key bottlenecks at Ramjas–St. Stephen's, GTB Road Bridge, and Mall Road, and demonstrates that signal timing optimization and modest intersection reconfiguration can meaningfully reduce delays. Five realistic scenarios, including post-class surges, festivals, and examination days, reveal how cumulative and sequential events affect network performance and where interventions are most effective. The work provides practical guidance for campus traffic management, illustrating the value of continuous-time simulations for planning short-term interventions and long-term infrastructure considerations.

Abstract

This project investigates traffic congestion within North Campus, Delhi University (DU), using continuous time simulations implemented in UXSim to model vehicle movement and interaction. The study focuses on several key intersections, identifies recurring congestion points, and evaluates the effectiveness of conventional traffic management measures. Implementing signal timing optimization and modest intersection reconfiguration resulted in measurable improvements in simulated traffic flow. The results provide practical insights for local traffic management and illustrate the value of continuous time simulation methods for informing short-term interventions and longer-term planning.

Analysis of Traffic Congestion in North Campus, Delhi University Using Continuous Time Models

TL;DR

This paper analyzes traffic congestion on North Campus, Delhi University, where mixed vehicle, pedestrian, and event-driven surges create delays and emissions. It adopts a continuous-time, event-driven simulation framework implemented in UXSim, calibrated with field survey data, to capture transient queue dynamics more accurately than discrete-time approaches. The study identifies key bottlenecks at Ramjas–St. Stephen's, GTB Road Bridge, and Mall Road, and demonstrates that signal timing optimization and modest intersection reconfiguration can meaningfully reduce delays. Five realistic scenarios, including post-class surges, festivals, and examination days, reveal how cumulative and sequential events affect network performance and where interventions are most effective. The work provides practical guidance for campus traffic management, illustrating the value of continuous-time simulations for planning short-term interventions and long-term infrastructure considerations.

Abstract

This project investigates traffic congestion within North Campus, Delhi University (DU), using continuous time simulations implemented in UXSim to model vehicle movement and interaction. The study focuses on several key intersections, identifies recurring congestion points, and evaluates the effectiveness of conventional traffic management measures. Implementing signal timing optimization and modest intersection reconfiguration resulted in measurable improvements in simulated traffic flow. The results provide practical insights for local traffic management and illustrate the value of continuous time simulation methods for informing short-term interventions and longer-term planning.

Paper Structure

This paper contains 15 sections, 3 figures.

Table of Contents

  1. Introduction
  2. Methodology
  3. Data collection
  4. Map selection and building
  5. Data preprocessing
  6. Continuous time simulation
  7. Application using UXSim
  8. Application using UXSim
  9. Traffic scenarios
  10. Results and Discussion
  11. Key congestion points
  12. Detailed simulation outcomes
  13. Effectiveness of traffic management strategies
  14. Limitations and future work
  15. Conclusion

Figures (3)

  • Figure 1: Final cleaned map of the North Campus road network used in the simulation.
  • Figure 2: Simulation snapshot of the combined traffic surge at Ramjas and Miranda House.
  • Figure 3: Simulation snapshot for the Malkaganj to Vishvavidyalaya Station corridor.