Development of vehicle systems for driver assistance and automated driving contributes to the improvement of road safety. Previous studies within this project show the effectiveness of current Advanced Driver Assistance Systems (ADAS) for crash avoidance. All accident scenarios which cannot be solved by today’s ADAS, specified as white spots, show potentials for future systems. In this paper, white spot scenarios of the German In-Depth Accident Study (GIDAS) are analyzed in order to identify categories indicating potentials for collision avoidance by new ADAS. Regarding all rural and motorway scenarios of GIDAS with severe injuries, accidents with crossing and turning scenarios can be stated as the largest category among white spots. Using this information, a generic system for a crossing assist is implemented. Applying the method of prospective effectiveness assessment, the potential for collision avoidance of the crossing assist is evaluated based on scenarios of the GIDAS Pre-Crash-Matrix (PCM). The outcome of the work presented in this paper is a method for development and evaluation of future system approaches based on accident data simulation. This means closing the gap between previous studies on present ADAS effectiveness on the one hand, and the development of new vehicle systems for further reduction of severe traffic accidents on the other hand.

Objective: With the overall goal to harmonize prospective effectiveness assessment of active safety systems, the specific objective of this study is to identify and evaluate sources of variation in virtual precrash simulations and to suggest topics for harmonization resulting in increased comparability and thus trustworthiness of virtual simulation-based prospective effectiveness assessment. Methods: A round-robin assessment of the effectiveness of advanced driver assistance systems was performed using an array of state-of-the-art virtual simulation tools on a set of standard test cases. The results were analyzed to examine reasons for deviations in order to identify and assess aspects that need to be harmonized and standardized. Deviations between results calculated by independent engineering teams using their own tools should be minimized if the research question is precisely formulated regarding input data, models, and postprocessing steps. Results: Two groups of sources of variations were identified; one group (mostly related to the implementation of the system under test) can be eliminated by using a more accurately formulated research question, whereas the other group highlights further harmonization needs because it addresses specific differences in simulation tool setups. Time-to-collision calculations, vehicle dynamics, especially braking behavior, and hit-point position specification were found to be the main sources of variation. Conclusions: The study identified variations that can arise from the use of different simulation setups in assessment of the effectiveness of active safety systems. The research presented is a first of its kind and provides significant input to the overall goal of harmonization by identifying specific items for standardization. Future activities aim at further specification of methods for prospective assessments of the effectiveness of active safety, which will enhance comparability and trustworthiness in this kind of studies and thus contribute to increased traffic safety.

Objective: The Vision Zero initiative pursues the goal of eliminating all traffic fatalities and severe injuries. Today's advanced driver assistance systems (ADAS) are an important part of the strategy toward Vision Zero. In Germany in 2018 more than 26,000 people were killed or severely injured by traffic accidents on motorways and rural roads due to road accidents. Focusing on collision avoidance, a simulative evaluation can be the key to estimating the performance of state-of-the-art ADAS and identifying resulting potentials for system improvements and future systems. This project deals with the effectiveness assessment of a combination of ADAS for longitudinal and lateral intervention based on German accident data. Considered systems are adaptive cruise control (ACC), autonomous emergency braking (AEB), and lane keeping support (LKS). Methods: As an approach for benefit estimation of ADAS, the method of prospective effectiveness assessment is applied. Using the software rateEFFECT, a closed-loop simulation is performed on accident scenario data from the German In-Depth Accident Study (GIDAS) precrash matrix (PCM). To enable projection of results, the simulative assessment is amended with detailed single case studies of all treated cases without PCM data. Results: Three categories among today's accidents on German rural roads and motorways are reported in this study: Green, grey, and white spots. Green spots identify accidents that can be avoided by state-of-the-art ADAS ACC, AEB, and LKS. Grey spots contain scenarios that require minor system modifications, such as reducing the activation speed or increasing the steering torque. Scenarios in the white category cannot be addressed by state-of-the-art ADAS. Thus, which situations demand future systems are shown. The proportions of green, grey, and white spots are determined related to the considered data set and projected to the entire GIDAS. Conclusions: This article describes a systematic approach for assessing the effectiveness of ADAS using GIDAS PCM data to be able to project results to Germany. The closed-loop simulation run in rateEFFECT covers ACC, AEB, and LKS as well as relevant sensors for environment recognition and actuators for longitudinal and lateral vehicle control. Identification of green spots evaluates safety benefits of state-of-the-art level 0-2 functions as a baseline for further system improvements to address grey spots. Knowing which accidents could be avoided by standard ADAS helps focus the evolution of future driving functions on white spots and thus aim for Vision Zero.

Emergency vehicle missions underlie high risks in traffic. Having emergency vehicles only equipped with light and siren, other traffic participants will not be reached by a warning and behave inadequate. These situations pose a high risk which may be reduced by introducing novel systems for protecting both the emergency vehicles and the surrounding traffic participants. As novel systems could have a severe impact on the traffic itself, simulations are useful in order to estimate the benefit or avenues of further improvements. One system is a preemption system which is developed for a real traffic environment and evaluated regarding travelling time and traffic safety. Beside, this paper develops needed behavioral models for both emergency vehicles and individual traffic and integrates them into the traffic simulation.

The worthwhile goal of reducing fatalities in road systems inspires people ever since the appearance of the first vehicles. Policy makers, researchers, developers, and others have adopted various measures with a positive effect on the number of fatalities. In Germany, the number dropped from a peak of 21,095 in 1970, to 3,339 in 2013. Measures include new laws and restrictions by policy makers such as reducing speed limits, penalizing drunken drivers, and enhancing education by driving schools. Researchers and developers mainly focus on technical safety and assistance systems. These systems include the anti-lock braking system (ABS), the electronic stabilization control (ESC), the emergency brake system, adaptive cruise control (ACC), and the lane-keeping control.

Cooperative Driving has attracted significant attention in recent years. With the help of vehicleto-vehicle (V2V) communication, perception systems may increase their quality of signals, their availability, and their perception range as well as decrease their latency and probability of failure. Moreover, V2V communication enables advancements from individual to cooperative decision making. With the help of a decentralized decision making among road users, the compatibility of varying planning algorithms distributed on several vehicles can be guaranteed. Additionally, the presented approach offers the opportunity to preserve the autonomy of decision making for each vehicle with an integrated validation. The integrated validation declines contradicting maneuvers by applying internal functional safety rules. The increasing progress in the research of cooperative technologies imposes new requirements for testing and validation. Therefore, a modular test framework regarding both the simultaneous integration of several autonomous vehicles and characteristics of a V2V based peer-to-peer communication is described. A combination of ADTF (the application prototyping framework within the Volkswagen group), VTD (a simulation tool-chain of VIRES) and OMNet++ (an open-source component-based network simulator) allows a host of experiments to test and validate cooperative driver assistance systems. In order to prove the decentralization process and the test framework, the paper shows simulation results for a cooperative safety system and a cooperative comfort system.

Agents can benefit from cooperative behavior as it intends to increase the total utility. In traffic situations, one agent may behave cooperatively by yielding to another. In recurring situations, this may lead to an imbalanced distribution of the benefit. However, humans prefer balanced utility distributions over imbalanced ones. While state-of-the-art cooperative decentralized decision making may promote such an imbalanced utility distribution, advanced cooperative decentralized decision making can support equality among the agents. Three different approaches are compared: Considering the agents' utilities perfect substitutes, imperfect substitutes, and perfect substitutes with time-variable rates of substitution based on a cooperative reward system. Simulations of a highway scenario reveal the differences in recurring situations: Perfect substitutes indeed maximize total utility, but at the expense of a highly unequal utility distribution that may lead to poor long-term user acceptance; imperfect substitutes promote an equal utility distribution, but leave much of the potential of cooperative behavior unused; introducing a cooperative reward system based on memories of costs is shown to allow for a trade-off between both - altruistic-cooperative behavior without constant preference of one agent over the other, which is assumed to improve user acceptance.

Statistically, emergency vehicles (EVs) encounter a higher risk of getting involved in accidents during their missions than other road users. The successful completion of these missions can be facilitated by new applications. Simulations may support the development of applications, as it is not possible to test them in a real traffic system. Simulation of Urban Mobility (SUMO) is one possible tool to conduct simulations of real traffic systems. However, SUMO is not capable of modelling a realistic behavior of EVs, new types of infrastructure, and individual vehicles (IVs) concerning EVs by a predefined function. We propose models for each of the missing pieces towards an integrated approach to simulate EVs in an urban environment. Therefore, we adjust them with a video analysis and simulate them. Further, an assessment analyzes their usability as a reference for testing new applications. In order to identify supportive applications, we created and carried out a survey with 252 EV drivers. The deduced applications are a traffic light preemption via V2I and an automated formation of a rescue lane via V2V. We assess the models and applications by evaluating the travelling time, a speed profile of the EV, and speed profiles of the IVs. Additionally, we show the usefulness of the two applications for the EV as well as the IVs.

One strong motivation for introducing Vehicle-to-Vehicle technology is added safety. This technology will allow cooperative maneuver planing to help prevent many accidents in the future. However, safety for road users can only be effectively supported if the calculated motion plan for all participants is followed accurately and without deviation. A novel algorithm for monitoring of cooperative motion plans is presented. It solves a conflict by generating a state space for the possible maneuvers for the involved traffic participants, tracking the progress of these maneuvers, and reacting to deviations to help alleviate accidents and help ensure a safe conflict resolution. The proposed monitoring algorithm is applicable to all kinds of road environments and road users. Preliminary results indicate the wide usability and performance of this approach.

The V2V communication is a promising technology aiming at the growing demands on safety, comfort and efficiency. A variety of research projects demonstrate the expandability of the V2V communication across the boundaries of current industry standards. The authors divide the expandability into two key aspects: collective scene description and cooperative maneuvers. This article combines the expandability of the V2V communication with systematically deduced essential automotive requirements and the challenges of a distributed decision making process. That leads to a reference architecture for cooperative driver assistance systems (CDAS) and cooperative integrated safety systems (CISS), uniting the flexibility for several implementations and a defined focus by the help of clear modules and interfaces. This article verifies the reference architecture using a cooperative merging onto a highway with a focus on the diversity of feasible implementation. The reference architecture arranges the field of research in separate problems and stimulate discussions about the proposed interfaces as an important step to future standards. Further research will gradually address the separate modules to establish the performance of CDAS/CISS and evaluate several concept variants.

Dear reader, You are holding in your hands a volume of the series „Reports of the DLR-Institute of Transportation Systems“. We are publishing in this series fascinating, scientific topics from the Institute of Transportation Systems of the German Aerospace Center (Deutsches Zentrum fur Luft- und Raumfahrt e.V. - DLR) and from his environment. We are providing libraries with a part of the circulation. Outstanding scientific contributions and dissertations are here published as well as projects reports and proceedings of conferences in our house with different contributors from science, economy and politics. With this series we are pursuing the objective to enable a broad access to scientific works and results. We are using the series as well as to promote practically young researchers by the publication of the dissertation of our staff and external doctoral candidates, too. Publications are important milestones on the academic career path. With the series „Reports of the DLR-Institute of Transportation Systems / Berichte aus dem DLR-Institut fur Verkehrssystem¬technik“ we are widening the spectrum of possible publications with a bulding block. Beyond that we understand the communication of our scientific fields of research as a contribution to the national and international research landscape in the fiels of automotive, railway systems and traffic management. This volume contains the proceedings of the SUMO2014 – Modeling Mobility with Open Data, which was held from 15th to 16th May 2014 in Berlin-Adlershof, Germany. SUMO is a well established microscopic traffic simulation suite which has been available since 2002 and provides a wide range of traffic planning and simulation tools. The conference proceedings give a good overview of the applicability and usefulness of simulation tools like SUMO ranging from new methods in traffic control and vehicular communication to the simulation of complete cities. Another aspect of the tool suite, its universal extensibility due to the availability of the source code, is reflected in contributions covering parallelization and interfacing improvements to govern microscopic traffic simulation results. The major topic of this second edition of the SUMO conference is open data. Several articles cover the acquisition and refinement of traffic networks as one of the fundamental data sources. Subsequent specialized issues such as data models for emissions and Bluetooth simulation are targeted as well. The conference’s aim was bringing together the large international user community and exchanging experience in using SUMO, while presenting results or solutions obtained using the software or modeling mobility with open data. Let you inspire to try your next project with the SUMO suite. There are many new applications in your environment. Prof. Dr.-Ing. Karsten Lemmer

Growing interest in Cooperative Driving within the field of Intelligent Transport Systems (ITS) put forth novel concepts for both enhanced sensing and advanced solution making. Although various approaches deal with advanced solution making, none of the concepts consider the conflict situation as a holistic situation comprising defined end states and trajectories towards them. We propose a novel algorithm for cooperative maneuver planning that is not meant to optimize a high level strategy but shall solve a conflict in the following five steps: target point generation, risk assessment, trajectory generation, combination including assessment, and execution of the maneuvers. The proposed cooperative maneuver planning algorithm is applicable to all kinds of road users' interferences (safety, comfort, time efficiency, and consumption efficiency), highly adaptive in terms of complexity and scalability, individually parameterizable, and applicable in diverse and mixed traffic situations. Simulations indicate the wide usability and performance of this approach in two different scenarios. The algorithm solves a critical overtaking maneuver on a country road and a merging maneuver onto a highway. Modifications of the initial situation lead to different solutions and thus show the adaptive nature of the algorithm.

Autonomous agents plan their paths through known and unknown environments to reach their goals. When multiple autonomous agents share the same area, conflict situations may occur that need to be solved. We present a decentralized decision making algorithm to solve conflicts among autonomous agents. It is based on two main ideas: First, we introduce an innovative operationalization of cooperative behavior which allows to determine whether a behavior is cooperative by computing the total utility and comparing it to a reference utility. Second, we use motion primitives as a representation of available maneuvers obeying individual and environmental restrictions. The decentralized decision making algorithm is based on communication among the autonomous agents to find an optimal maneuver combination. Simulations show that our algorithm is applicable to different highway traffic scenarios of two automated vehicles. We use a mean-square acceleration as an individual cost function and show that our intelligent controller leads to cooperative solutions.