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SUMO-TraCI is an important tool to utilize the V2X communication simulation system. Some helpful content to understand TraCI are provided below (both for Matlab and Python solutions).

The beginning steps of SUMO TRACI programming with Matlab

The beginning steps of SUMO TRACI programming with Python

Simple example code with MatlabSimple example code with Python

Manual for SUMO/MATLAB/VEINS/INET/OMNET++ programming and interfacing with example codes

OMNeT++, Veins, INET, and other system components are complex and hard to understand. This technical report provides basic help to start the V2X simulation utilizing the mentioned frameworks. The document also provides example codes.


Tutorial for SUMO – VEINS programming (Open Source vehicular network simulation framework)

A basic tutorial for setting up a Veins simulation in OMNeT++.


Simulation of V2X (Vehicle-to-Everything) communication

Highly automated vehicles and their smart functions are getting into our everyday. Artificial intelligence, sensors, and the functions themselves are rapidly developing daily towards the primary goal of reaching the level of fully autonomous vehicles. Making vehicles communicate adds a new level of safety and opens the way towards collective information sharing.

Sharing essential information (e.g., speed, position, sensor information) between vehicles and the infrastructure (V2I, Vehicle-to-Infrastructure) creates various traffic-level control possibilities. However, it can also help individual vehicles in their decisions.

Creating a control algorithm for vehicles moving with high velocity is challenging, as safety must stand before anything else. An intensely detailed simulation of the communication itself is inevitable to test these complex algorithms exhaustingly. For this purpose, a Vehicle-In-the-Loop and Mixed reality capable framework was extended to simulate wireless communication technologies, considering every aspect of communication (e.g., signal propagation, signal attenuation, shadowing, routing, interference).

The system can simulate all communication layers of 802.11p and 5G technologies in such remarkable detail that even messages are considered bit by bit. The system provides fundamental models and elements for 5G network simulations, such as 5G RAN (Radio Access Networks), core network, Frequency Division Duplexing (FDD) and Time Division Duplexing (TDD) modes, heterogeneous gNBs (macro, micro, pico base stations), 3GPP compliant protocol layers, realistic channel models and resource scheduling in both up-and downlink directions. It allows engineers to analyze the control algorithm’s performance in any scenario, including possible faults or attacks on the communication itself.

Architecture and system components

The created system has an implemented signal shadowing model realized in Unity 3D. The implemented model calculates signal attenuation losses when obstacles are in the way, creating a NOS (Non-line-of-Sight) scenario. Any objects (e.g., house walls, furniture, electronic equipment, vehicles) can be simulated with any materials in a three-dimensional environment considering the assigned material’s dielectric properties.

Simulation of building walls causing attenuation loss.

The system’s flexibility allows simulating from vehicles, RSUs (Road-Side Units) to whole communication networks through V2N (Vehicle-to-Network) communication, including 5G base stations and the whole network infrastructure behind it (e.g., wired connections, routers, servers).

The created system was tested with a simplistic decentralized intersection control based on Cooperative AwarenessMessages (CAM) as a proof of concept.

Read the related publication:

T. Ormándi, B. Varga, T. Tettamanti: Distributed intersection control based on Cooperative Awareness Messages. In: 2021 5th International Conference on Control and Fault-Tolerant Systems (SysTol), pp. 323–328, 2021.
Written by: BME Traffic Lab | Date: 07/02/2023 3:49 PM