Ongoing urbanization in Germany leads to an increase in the already high congestion rate and -intensity as well as to a deterioration of life quality in cities due to emissions and soil sealing. Simulation can be an important tool for identifying effective mobility solutions. Visualization, on the other hand, can foster a shared understanding of the underlying problems and increase the acceptance for proposed solutions among all stakeholders. While macroscopic tools are widely used in public service, their aggregated flow models cannot represent automated driving functions, adaptive signal control systems, or innovative traffic management concepts that require the management of individual traffic participants. Established microscopic tools offer these capabilities. However, their simulations are typically limited to small areas as driver models are highly detailed and computationally expensive. SUMO is an open-source alternative suited for large-scale microscopic simulation, yet its console-driven workflow, the fragmented toolchain and limited visualization options pose as a barrier against a widespread use in public service. This work describes the development of TraffIQ Lab, a SUMO Wrapper that automates the data flow in SUMO for the simulation of real-world traffic scenarios and provides a customizable user interface with enhanced visualization capabilities. By this, TraffIQ Lab enables users without programming experience to simulate and visualize the influence of novel technologies and traffic management concepts, even if the simulation requires microscopic road users. This supports users in finding efficient solutions to traffic-related problems. We developed TraffIQ Lab with the Game Engine Unity, harnessing its rendering and UI capabilities. The user interface is based on a real-world 2D map that is implemented as a slippy map. The map tiles are fetched from the OpenStreetMap API. When a user selects a map tile, the application loads infrastructure data for the tile from OpenStreetMap and overlays it graphically. During this process, all the infrastructure-related files are generated automatically that are required for running a SUMO simulation.  Users can manipulate the infrastructure via the CityEditor or select the origin and the destination zone for different types of road users in the ODEditor. Starting the simulation launches SUMO with the parameters to simulate the scenario created in TraffIQ Lab. The resulting output provides information on routes, emissions, and the timing of road users, which can then be visualized within TraffIQ Lab. We provide TraffIQ Lab as a service: Based on the requirements of a partner, our team can extend or customize the simulation on the SUMO-side and the visualization on the Unity-side. So far, we have developed a macroscopic simulation mode. The microscopic simulation is still under development.

The decarbonization of the transport sector often fails due to an overly narrow focus on the end product. A “green” vehicle operating within a fossil-based infrastructure is not a solution - it merely shifts the problem.

In this presentation, Ms. Yao Schultz-Zheng - founder of E-Mobility Sharing Economy Services - breaks down the silos between vehicle production, global supply chains, the expansion of renewable energy grids, and intermodal transport infrastructure. Learn how modern simulations (co-simulation & digital twins) act as a “conductor,” linking these complex sectors into a functioning, sustainable overall system. Sustainability must be simulated holistically - from the molecule to the driven kilometer.

The introduction of automated processes in logistics yards can contribute significantly to the optimization of yard management, but it also entails potential challenges. Smooth interaction between humans and automated systems requires careful planning and implementation in order to minimize possible risks, particularly at the interfaces between different systems. Problems can arise when humans and machines do not work together seamlessly or when automated processes are not sufficiently prepared for human involvement. By using state-of-the-art technologies such as 5G, not only logistical challenges are to be addressed, but also a safe and efficient collaboration between humans and machines on logistics yards is to be enabled.

Practical use case:

With Dysis (Dynamic, Sensor-Integrated Assistance System), the team at ITK Engineering has developed and patented an innovative assistance system for logistics operators that safely guides vehicles to the loading bays in container yards. Instead of equipping each individual vehicle with sensors, the loading bays in the logistics yard are fitted with sensors that communicate directly with the driver via a specially developed app. When a truck enters the logistics yard, the assistance system detects its position. As soon as the driver approaches the bay and starts maneuvering, the sensors report possible obstacles in the driving path—such as unexpected pedestrians—via audio and visual alerts in the app on the driver’s smartphone. The approach has also been implemented for teleoperation, i.e., the remote control of a transport vehicle from a control center. For the teleoperator, the app is integrated into the control station. An automated vehicle receives the information from the assistance system directly via 5G.

As physical road testing is insufficient for the safety validation of autonomous vehicles, simulation-based strategies are essential for homologation. This presentation examines the technical and methodological frameworks necessary for L4 type approval, focusing on the following core pillars:

• Data Pipeline: Building robust pipelines for heterogeneous data sources.
• Traceability: Ensuring consistency from ODD requirements to validation results.
• Simulation Credibility: Demonstrating model fidelity, scenario coverage, and statistical validity.
• Versatile Infrastructure: Developing flexible test environments that adapt to evolving software architectures and regulatory demands.

For the operation of autonomous bus fleets in public transport, control centers are indispensable. They serve as central entities for both technical supervision and decision-making. This requires qualified personnel in the control center who can act reliably and appropriately even in exceptional situations. Accordingly, the control center staff are subject to the qualification and training requirements defined in Section 14 of the AFGBV.

Fraunhofer IVI offers a training concept that realistically conveys the operation of the control center and prepares employees in a targeted manner for later operations. Since critical traffic situations cannot be deliberately created or reliably reproduced in real-world operation, training with real vehicles is only possible to a limited extent. For this reason, a simulation-based training environment is used.

Using OpenDRIVE and OpenStreetMap data, the real deployment area of the control center is recreated as a three-dimensional virtual world in the CARLA simulation environment. This creates a realistic training environment that has a direct connection to the later area of operation.

The virtual vehicles move within this environment, while the control center software displays camera and telemetry data exactly as it would in live operation.

For training purposes, test scenarios are developed, among other things, using the OpenSCENARIO standard. This makes it possible to deliberately simulate traffic obstacles, critical vehicle states, and passenger emergencies. In this way, decision-making and the operation of the control center can be trained and evaluated under near-realistic and safe conditions.

The result is a time- and cost-efficient training concept that can be used independently of real vehicles, weather conditions, or traffic situations. The simulation allows unrestricted repeatability and adaptability of training content and makes a significant contribution to expanding the competencies of control center staff in dealing with autonomous vehicles.

The increasing complexity of automated and intermodal mobility systems demands new approaches to system validation. Virtual methods such as simulation and virtualization offer significant efficiency gains, but only if they are credible.
This talk introduces the concept of Credible Simulation as a foundational requirement for virtual integration, verification, validation, and ultimately, virtual release. Key credibility aspects such as error management, organizational capability, verification, validation, and uncertainty quantification are discussed.
Bosch Engineering and ITK Engineering collaborate closely with a particular focus on Software-in-the-Loop (SiL) methods. A reference project on NCAP simulation for AEB systems illustrates the practical application of the Bosch framework for Credible Simulation.