Traffic accident research
at the TU Dresden GmbH

Master driving scenarios - with safety!

How can highly automated driving be made safe in the future? And which scenarios do drivers and highly and fully automated vehicles need to be able to master so that the road traffic of tomorrow harbours fewer dangers?

A consortium of Saxon project partners has been working on these and other questions over the past three years as part of the SePIA joint research and development project. The starting point was the fact that there are still no suitable and generally recognised test and inspection concepts for both the approval and field testing, including the regular technical inspection of motor vehicles with highly automated driving functions. Measures to ensure a correspondingly high level of performance must extend over the development period and, in particular, over the entire life cycle of automated vehicles.

As part of SePIA, a complex manufacturer-neutral data platform with a large number of different traffic situations in road traffic was designed and implemented as a functional model. The data basis is formed by real driving and accident data, so that both "normal driving scenarios" and critical scenarios and accidents can be depicted. The scenario-based platform lays the foundation for measurably mapping human driving behaviour and using it as a reference point for highly automated driving. Based on this, requirements for automated driving functions can be derived, which are used both in the approval process and in field testing, including the general inspection of motor vehicles. With the publicly available prototype platform, SePIA has contributed to making highly automated driving safe in the future.

The SePIA research project was supported by the European Union with funding from the European Regional Development Fund as part of the Saxon state initiative "Synchronised Mobility 2023". This initiative involves pooling the core competences of Saxon industrial and research companies and establishing innovative research results (e.g. on new vehicle concepts, assistance functions or IT networks). SePIA has made it possible to put this goal into practice and at the same time strengthen Dresden as a centre of science.

Project partner: Fahrzeugsystemdaten GmbH, TraceTronic GmbH, Fraunhofer Institute for Transportation and Infrastructure Systems IVI, TU Dresden - Chair of Computer Graphics and Visualisation, TU Dresden - Chair of Automotive Engineering

Project durationJune 2017 until November 2020

The project is part of the state initiative "Synchronised Mobility" and runs from June 2017 to November 2020. The European Union is supporting the project with funding from the European Regional Development Fund (ERDF).

Increase in safety margins

MeBeSafe is an EU-funded research project that aims to develop and test solutions to encourage car drivers and cyclists to adopt safer behaviour in common high-risk traffic situations. The project will also compare different types of coaching.

The aim is to reduce the number of "near misses", also known as risky situations. The increase in safety margins will lead to high-risk situations being avoided - which in turn will lead to fewer accidents in general.

Traffic behaviour is mainly habitual

Navigating in traffic is an everyday activity for most people, and their behaviour is largely determined by automatic
Reactions controlled. Automated behaviour in itself is not dangerous. It can be anywhere on the scale of high safety margins
up to very risky.

Many safety measures in traffic do not fulfil their potential because they appeal to conscious decisions. The ordinary
However, road users will primarily regard traffic as a habitual task and give it little thought.

By using so-called nudging approaches, road users are instead encouraged to make a safe choice without even thinking about it. All options, even the unsafe ones, are still open, so nudging is less intrusive than outright bans.

MeBeSafe goals

The road accident statistics clearly show a number of high-level causal factors, which can be summarised in three categories
leave.

MeBeSafe aims to address these risk factors through seven specific objectives:

• Reduce lack of attention

• Prevent excessive speed for the current circumstances

• encourage more road users to focus their attention on potential dangers

• encourage more road users to choose an appropriate speed in potentially dangerous situations

• Help road users to follow a suitable trajectory in potentially dangerous situations

• Raising drivers' awareness of potential dangers in parallel traffic and increasing the distance between vehicles through increased use of adaptive cruise control (ACC)

• encourage tired/sleepy drivers to take a break

MeBeSafe tested and developed 8 soft measures to make traffic safer, including roadside lights, novel markings on cycle lanes, moving balls and an app that helps lorry drivers coach each other.

The use of automated assistance and driving functions is increasingly helping to increase road safety in everyday life, but also requires a cross-vehicle model examination with regard to the design, condition, function and effect over the entire vehicle service life. How can an efficient testing technology be developed and which testing tools are used? 

Coordinated by FSD Fahrzeugsystemdaten GmbH, the BMVI-funded project "ErVast" is working with other partners to develop a test procedure for assistance systems and automated driving functions in vehicles, which is to be used during regular general inspections. Existing test protocols and analysed accident scenarios serve as the basis for comprehensive testing of the functions. 

VUFO works within the framework of of this traffic accident research project the derivation of test scenarios based on real accident data. In a first step, various accident scenarios are analysed and grouped on the basis of the GIDAS database from all traffic events. Within the scope of the project, the focus is on urban accidents involving passenger cars. Further dynamic and environmental analyses are carried out for these accidents in order to subsequently identify relevant parameters (e.g. position, speed, accelerations of those involved) for a test scenario. Based on the relevant parameters, exemplary test scenarios are transferred to CarMaker as well as OpenDRIVE and OpenSCENARIO. Based on the resulting prototypical test scenario pool, vehicle model-specific tests with the necessary test setups can be selected.

LEONARDO is a European H2020 project researching the safety, use and cost reduction of small electric vehicles in public road transport.

The aim is to develop a new vehicle concept in the field of micromobility with improved energy efficiency, increased safety and new solutions for system integration, such as a modular battery pack, and to test it as a prototype in various European cities.

VUFO is involved in creating a basis for safety-related and technical-legal requirements for the vehicle concept to be developed in LEONARDO and in presenting information on the user and accident situation in various countries.

In addition, the requirements of vehicle users are derived.

The project started in January 2021 and will run for three years. Further information on the LEONARDO project can be found at here.