The OptiModal project develops digital tools for planning, simulation, and optimization of intermodal transport systems to create sustainable and time-efficient mobility solutions in rural areas.
• Modeling the combination of on-demand and fixed-route services to optimize travel times and resources.
• Digital twin with flexible visualization and simulation interface.
• Data-driven planning of traditional and flexible public transport in urban and regional contexts.
The OptiModal project, funded by the Federal Ministry for Digital and Transport (mFUND initiative), addresses the challenge of creating comprehensive and time-efficient mobility solutions in rural areas. The focus lies on the development and optimization of demand-responsive transport systems that are integrated in classical public transport. These concepts are being tested and refined in the Hof county, which serves as the pilot region. By utilizing structural, movement, and usage data, as well as innovative techniques such as neural networks, digital tools are being developed to realistically simulate and optimize supply and demand. This effort leverages existing open-source agent-based traffic models, simulation libraries, and WebGIS applications. The use of a digital twin enables data-driven evaluation and improvement of transport systems.
The project is led by Hof University of Applied Sciences. Additional partners include:
• Technical University of Munich (TUM): Chair of Traffic Engineering and Control
• Plan4Better GmbH: Developer of GOAT and expert in data-driven planning
• Fluxguide Exhibition Systems GmbH: Specialists in visualization and interactive applications
• Match Rider GmbH: Provider of ridesharing solutions
• Hof District: Pilot region and associated partner
Plan4Better is part of the consortium and focuses on specific work packages within the project. Our key topics include:
• Deployment and Extension of GOAT: GOAT is enhanced to model on-demand transport systems, which are becoming increasingly important in rural areas. This facilitates seamless planning of intermodal mobility chains.
• Agent-Based Traffic Models: Plan4Better supports the exploration and implementation of new approaches such as agent-based traffic models, enabling the simulation and optimization of on-demand transport.
• Application Demonstrator: GOAT serves as the basis for a demonstrator that integrates previous work on GIS interfaces, routing functions, and user interfaces. This demonstrator enables interactive planning and evaluation for transportation planners.
• Accessibility Analyses: Creation of dynamic, spatially high-resolution accessibility analyses to optimize the integration of fixed-route and demand-responsive transport systems.
• Development of suitable tools for planning and optimizing mobility offerings, aligned with private vehicle travel times.
• Realization of a digital twin for simulating and evaluating mobility solutions.
• Use of optimization tools to continuously improve mobility systems and re-evaluate them through simulations.
• Promotion of sustainable mobility through resource-efficient and time-saving solutions as alternatives to private motorized transport.
Plan4Better leads the development of the application demonstrator and brings its expertise in interactive accessibility calculations and geodata processing. Through the enhancement of GOAT, the project demonstrates how open-source technologies and data-driven approaches can shape the future of transport planning.
For more information, visit the project profile here.
.png)
.jpg)
.jpg)
Whether you need state-of-the-art GIS technology, extensive datasets or expert advice – we are ready to help you shape a sustainable and liveable future for our community.
