Summary

The main objective of this project (a branch of AIVIA) is to develop an advanced 3D traffic simulation platform aimed at generating high-fidelity synthetic data for studying, analyzing, and making informed decisions regarding road infrastructures. The platform allows for the configuration and customization of various simulation parameters, including infrastructure models, weather conditions, vehicle flow, obstacles, and virtual sensors. The data generated by the simulations is subsequently sent to and analyzed on the Microsoft Azure cloud.

Key Features:

1. Customizable 3D Simulation: The platform provides a highly configurable simulation environment, allowing users to adjust road infrastructure, time of day, weather conditions, and other factors to create realistic and specific traffic scenarios.
2. Scene and Simulation Configuration: Users have the ability to create and modify simulation scenes through an intuitive interface or via a Content Management System (CMS-Backend). This includes real-time parameter adjustments and the capability to control ongoing simulations.
3. Real-time Data Integration: The application seamlessly connects to various APIs to gather real-time data, allowing for dynamic configuration of simulation scenes. Parameters such as weather conditions, road obstacles, road conditions, DMS messages, tolls prizes and more can be automatically adjusted based on live data feeds.
   By integrating real-time data from various APIs, the platform enhances the accuracy and realism of simulations, enabling users to study and analyze traffic scenarios under dynamically changing conditions.
4. User Engagement in Simulation: Users can actively participate in simulations by taking control of a vehicle, either through traditional interactions (keyboard, mouse, joystick, wheels) or via virtual reality devices. This interaction allows for evaluating user driving behavior and its influence on the simulated traffic.
5. Synthetic Data Generation: The platform generates highly realistic synthetic data that simulate traffic flow, vehicle interactions, driver behavior, and responses to various scenarios. This data is essential for problem analysis, informed decision-making, and optimization of road infrastructures.
6. Azure Cloud Analysis: The data generated by simulations is transferred to Microsoft Azure for comprehensive analysis. This enables the application of advanced data processing algorithms and detailed assessments of road infrastructure, identifying areas for improvement and optimization opportunities.
7. 5G Behavior Simulation and DMS Messages: The platform simulates 5G behavior and Dynamic Message Signs (DMS) using a point cloud representation of coverage. Intelligent vehicles receive messages from both the road infrastructure and other vehicles, influencing their actions within the simulation.
8. CCTV Camera Creation: Users can create CCTV cameras within the 3D environment, accessible via the internet to provide streaming from specific points within the environment or within vehicles.
9. Programmable Timeline: A programmable timeline, configurable via the CMS, allows users to schedule events such as weather changes, obstacle appearances, alterations in vehicle behavior, actuator adjustments, sensor creation or modification, and other actions.
10. Toll Study: The platform offers the ability to create tolls for in-depth analysis. Users can configure vehicle responses to tolls, including willingness to pay, take alternative routes without tolls, and more. Toll prices can be set through the interface, CMS, or programmatically based on variables such as vehicle count on the road.

Benefits and Applications:

• Cost Reduction: The project offers an efficient and cost-effective alternative to full infrastructure sensorization, enabling the generation of realistic data without incurring high expenses.
• Informed Decision-Making: Analyses based on generated synthetic data empower road authorities and urban planners to make informed decisions about infrastructure design, modification, and optimization.
• Impact Assessment: The project facilitates early assessment of future road constructions, identifying potential issues and optimizing designs before implementation.
• Training and Education: The ability to interact with simulations provides a valuable tool for driver training, assessing driving behaviors, and promoting road safety education.

Ultimately, the project aims to create an accurate and versatile digital twin of real road infrastructures, serving as a comprehensive platform for informed decision-making and continuous improvement of urban mobility.