The studies include the detailed analysis and evaluation of systems and the investigation of the effectiveness of various collision avoidance measures.
In order to further advance the development of Cooperative Intelligent Transport Systems (C-ITS), VUFO is currently working on models to represent and analyze connective technologies in specific individual accident scenarios.
A model for determining the received signal strength (RSSI – Received Signal Strength Indicator) was developed in cooperation with the TU Dresden, Chair of Information Technology for Traffic Systems (ITVS). The results of this model can be integrated into the PCM data. This allows analyses to be carried out to improve safety.
VUFO mainly works with accident data from the GIDAS PCM. An RSSI history can be calculated and analyzed for approximately 98% of all 12,000 GIDAS PCM cases.
In addition, the model can also be applied to other data sets (e.g. real driving data, international accident data, etc.) that are available in PCM format 5.0 and RSSI values can be calculated.
RSSI sequences can be made available for the GIDAS PCM. We will be happy to inform you about the current status of our developments and advise you on your research projects.
Using the PONR model of the VUFO, we simulatively identify the unavoidable time of an accident. Cases from the GIDAS database are systematically varied. By integrating different driving maneuvers at different points in time, we check whether one (or more) of these driving maneuvers lead to a collision avoidance at the respective point in time. The variation of the point in time to be tested (depending on the success or failure of the avoidance) ensures that the PONR is narrowed down.
The underlying limit values of the currently eight integrated driving maneuvers are based on the GIDAS database (e.g. maximum possible deceleration) and are based on Kamm’s circle. The driving maneuvers are:
The focus on different maneuvers can be determined in advance by the user by selecting the driving maneuvers to be investigated or by excluding certain driving maneuvers. By determining the last possible avoidance time, the limit is identified at which the probability of success of active safety systems is 0% and accordingly all measures to mitigate the consequences of an accident could / should be initiated.
For acceleration maneuvers, the maximum acceleration can either be selected individually or, in future, approximated based on the vehicle class and the initial speed.
The current model version (V1) allows a variation of the driving maneuvers for one participant (car), all other participants retain their movement. The party to be varied can be specified by the user. An extension to the cooperative model, in which both parties involved in the initial collision can be varied, is possible if required.
The methodology of the PONR model is illustrated in the following video. The initial collision of a GIDAS PCM case as well as two variations, on the one hand the full deceleration and on the other hand an avoidance manoeuvre to the left, are visualized using the PCM viewer. The last possible avoidance time of the respective maneuver is shown for both variations.
VUFO applies the model on the basis of the GIDAS database. If the cases are suitable, we calculate the times of unavoidability for the accidents and output these as well as the last possible avoidance maneuver. It is possible to integrate these values into the VUFO criticality dashboard.
In principle, this methodology can also be used for other data sources that are in PCM format and contain further information on the situation or accident.
We calculate the point of no return for you based on the GIDAS cases as well as the last possible avoidance maneuver for each case. This allows you to drive forward your developments in the field of active and passive vehicle safety in a data-driven manner and integrate the specific (time) requirements.
Here we present our methodology for calculating the time-to-collision and driving hose criticality. By considering both criticality models, statements can be made about the temporal as well as the spatial criticality.
The time-to-collision is defined as the duration after which a collision occurs between several road users while maintaining their current driving conditions. The basis for this is the rectilinear, uniform form of movement. This parameter is of great importance for the criticality assessment of both active and passive safety systems. Among other things, the TTC provides the necessary information for initiating or triggering various safety precautions, e.g. for the emergency brake assistant.
With the TTC model developed by us, we are able to calculate the temporal progression of the TTC of two road users based on the driving data in PCM format, regardless of the constellation.
The model of driving hose criticality developed by VUFO is to be understood as a spatial measure of criticality. It determines the space required by a road user in the longitudinal direction for the avoidance maneuvers of deceleration to a standstill and evasion by applying the necessary lateral offset.
The formation of the vehicle-specific movement options is represented in so-called driving hoses. The specified acceleration values can be individually adjusted. This allows the more suitable avoidance maneuver to be determined by calculating the required path in the longitudinal direction of the vehicle.
The maneuver with the shortest distance to avoid is therefore the one that determines the length of the driving hose of the respective participant. In addition, there is a third green (non-critical) driving hose, which represents normal driving (straight, uniform movement), analogous to the driving hose of the TTC model.
The criticality is then determined using the intersection points/intersection area of the driving hoses of both participants. Based on the criticality of each individual vehicle, which can assume a value between 0 (non-critical) and 1 (highly critical), the entire situation is then evaluated by calculating the arithmetic mean of these criticalities and thus the final driving hose criticality (FSK). This methodology is applied for each time step stored in PCM format, resulting in an FSC curve.
The model approaches for calculating the TTC and FSK as well as the resulting curves are shown in the following video as examples for two different types of accident. The first case is a car-cyclist collision, the second case is a collision between two cars.
The VUFO mainly works with accident data from the GIDAS PCM. A TTC and FSK curve can be calculated and analyzed for approx. 95% of all almost 11,000 GIDAS PCM cases. However, it is also possible to calculate these histories for external data in PCM format, for example driving data from NDS studies.
We calculate the criticality of the journeys in your data or prepare GIDAS PCM analyses for you. For example, we can determine the danger and relevance of certain traffic scenarios for research and development projects.
By considering both criticality models, statements can be made about both temporal and spatial criticality. The respective model limits can be reduced by a combined consideration of the two criticality measures presented. This results in significant advantages in the criticality assessment of different driving situations.
We can help you with the interpretation and will be happy to advise you on how to use the results. In principle, this methodology can also be used for other data sources that are in PCM format and contain further information on the situation or accident.
We calculate the point of no return for you based on the GIDAS cases as well as the last possible avoidance maneuver for each case. This allows you to drive forward your developments in the field of active and passive vehicle safety in a data-driven manner and integrate the specific (time) requirements.
The complexity of developing and safeguarding new ADAS/AD (Advanced Driver Assistance System/Autonomous Driving) functionalities is constantly increasing. In order to be able to analyze and evaluate the benefits and functional safety of such systems at an early stage, simulating the function in a real accident is of crucial importance.
We support your development and validation in the area of ADAS/AD functionalities. We work closely with you to define the functions and limits of the system, as well as options for transferring it to the simulation environment. The system can then be simulated within various real and generic accident scenarios with different parameter sets. Both the parameters of the system and the accident scenario can be varied. The final step is the evaluation and classification of the results.
Take advantage of our expertise in accident research to maximize safety and prevent accidents! Our tailor-made scientific advice helps you to precisely analyze the causes of accidents and develop effective preventive measures. With their interdisciplinary know-how, our scientists will guide you to well-founded solutions.
If you would like to find out more about the application of the services, please get in touch with us. Thomas Unger will be happy to assist you.
Telephone: 0351 438989-35
E-mail: thomas.unger@vufo.de