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Automated and Connected Driving

Automated and connected driving can improve road safety, help avoid traffic jams and reduce fuel consumption and consequently CO2 emissions. Automated or autonomous vehicles can thus make a decisive contribution to ensuring sustainable mobility. For example in passenger transport with the help of self-driven minibuses in rural areas or with truck platooning, dynamic ramp control or delivery robots in logistics.

We question the supposed advantages, examining and evaluating the necessary conditions for autonomous driving and the effects of automated vehicles. Within the scope of our research projects, we develop and optimize software solutions for modelling and simulation of autonomous mobility and transport.

Our fields of action

Already today, we offer solutions with which municipalities and companies, urban and traffic planners, fleet and ramp operators as well as end users can prepare themselves for the new requirements. We develop suitable concepts and contribute to the improvement of existing products and the development of new offers.

Our product portfolio supports you on this and many other topics.

  • Analysis and forecast of the development of automated vehicles, their market penetration and their consequences
  • Simulation of automated driving functions, also under consideration of mixed traffic
  • Model calculations for the use of automated vehicles and fleets in passenger transport
  • Planning and control of future fleets in freight transport

Selected projects

How does automated and connected driving affect people's traffic behaviour or the transport system, and what impact do these changes have on emissions and energy consumption? Based on an analysis of potential, the study Energy and Greenhouse Gas Effects of Automated and Networked Driving in Road Traffic provides answers to these questions, which was carried out as part of the Federal Ministry of transport and digital infrastructure's (BMVI) scientific advice on mobility and fuel strategy (MKS)

Automation allows transport operators to offer more flexible, cost-effective services and organise their operations. Combined with a denser range of services and greater transport comfort (door-to-door operation), it also offers clear advantages for public transport users.

The project Manual for Municipalities on Automated and Connected Driving provides guidance on the integration of automated transport in urban public spaces. The LEA(Small)Bus research project, commissioned by the BMVI, analysed the prerequisites and possible consequences of using automated passenger cars, small and standard buses. Various fields of application and use were modelled and evaluated. The EasyRide project used the example of Munich to show goals and realistic development paths for automated, connected and demand-oriented mobility offers with the help of scenarios and impact analyses. 

The driving behaviour and interaction of self-driving cars, both among themselves and with other road users, can be depicted worldwide and in all conceivable scenarios using simulation software. The resulting network-wide effects can be quantified in traffic demand models. In the EU project CoEXist and in the BMVI-funded project ACCorD, micro- and macroscopic traffic simulation and modelling tools for automated vehicles were further developed and applied, and evaluation procedures based on them were developed.  The project R4R - Ready for Smart City Robots? funded by the BMDV as part of the mFUND programme,  focusses on autonomously operating micromobiles and the simulation of their operation.

The EU-funded lighthouse project efeuCampus served as an innovation centre for autonomous urban goods logistics; among other things, autonomous transport robots bring goods in the neighborhood. To this end, PTV analysed and planned the transport processes, extending and detailing maps, contributing to the development of the infrastructure and developing components for order and data management. 

Further projects: Augmented CCAM, FAME.

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