Large Scale Micro Simulator

Problem:
The technology aims to address the complexity and inefficiency of large-scale traffic management. Current traffic systems struggle with real-time decision-making, adaptive responses to dynamic conditions, and accurate simulations of human driving behavior and environmental impacts.

Our Solution:
LSMS (Large Scale Micro Simulation) is a micro simulation model designed for large-scale traffic simulations. It operates by processing agents (vehicles, traffic lights, signs, roads) in parallel on a GPU, enabling fast simulation of extensive road networks. Key features include:

• Agent-Based Modeling: Each object in the simulation acts as an independent agent, observing and reacting to its immediate surroundings.

• Flexible Movement: Vehicles can move freely within their physical limitations, not restricted to specific lanes or roads.

• Rule-Based Behavior: Actions are governed by a prioritized rule stack, ensuring realistic responses (e.g., emergency braking over speed limits).

• Integration with Open-Source Tools: Utilizes SUMO for network data and CARLA for visualization, and can connect to macro simulators like TNO's Digital Twinning Platform.

• Scenario Testing: Supports various scenarios such as adaptive cruise control, autonomous vehicles, mobility services, and shared vehicles.

Impact: LSMS has the potential to revolutionize traffic management and urban planning by:

• Improving Traffic Flow: Enhancing real-time adaptive responses to traffic conditions, reducing congestion, and improving efficiency.

• Safety Analysis: Studying human driving behavior and collision scenarios to develop safer traffic systems.

• Environmental Monitoring: High-resolution tracking of vehicle emissions to inform air quality models and environmental policies.

• Scalability and Speed: Offering significant speed improvements (up to 10 times faster) over existing simulation tools, enabling more extensive and detailed studies.