PRORETA 3: Comprehensive Driver Assistance by Safety Corridor and Cooperative Automation

Winner, Hermann; Lotz, Felix; Bauer, Eric; Konigorski, Ulrich; Schreier, Matthias; Adamy, Jürgen; Pfromm, Matthias; Bruder, Ralph; Lüke, Stefan; Cieler, Stephan

doi:10.1007/978-3-319-12352-3_19

Cited by 11 publications

(13 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ultrasonic sensors can reliably detect objects over a distance of a few meters, almost regardless of their surface properties. Several sensors are required over the entire right side of the vehicle to cover the necessary detection range on a heavy commercial vehicle [20,21]. With the help of ultrasonic sensors, it is impossible to classify static and dynamic objects on the right-hand side of the road.…”

Section: Test Vehicles and Blind Spot Assistance Systemsmentioning

confidence: 99%

Influence of Blind Spot Assistance Systems in Heavy Commercial Vehicles on Accident Reconstruction

König,

Paula,

Quaschner

et al. 2024

Sensors

View full text Add to dashboard Cite

Accidents between right-turning commercial vehicles and crossing vulnerable road users (VRUs) in urban environments often lead to serious or fatal injuries and therefore play a significant role in forensic accident analysis. To reduce the risk of accidents, blind spot assistance systems have been installed in commercial vehicles for several years, among other things, to detect VRUs and warn the driver in time. However, since such systems cannot reliably prevent all turning accidents, an investigation by experts must clarify how the accident occurred and to what extent the blind spot assistance system influenced the course of the accident. The occurrence of the acoustic warning message can be defined as an objective reaction prompt for the driver, so that the blind spot assistance system can significantly influence the avoidability assessment. In order to be able to integrate the system into forensic accident analysis, a precise knowledge of how the system works and its limitations is required. For this purpose, tests with different systems and accident constellations were conducted and evaluated. It was found that the type of sensor used for the assistance systems has a great influence on the system’s performance. The lateral distance between the right side of the commercial vehicle and the VRU, as well as obstacles between them, along with the speed difference can have great influence on the reliability of the assistance system. Depending on the concrete time of the system’s warning signal, the accident can be avoided or not by the driver when reacting to this signal.

show abstract

Section: Test Vehicles and Blind Spot Assistance Systemsmentioning

confidence: 99%

Influence of Blind Spot Assistance Systems in Heavy Commercial Vehicles on Accident Reconstruction

König,

Paula,

Quaschner

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

“…Bird's-eye views are additionally rated as rather clear and comfortable than first person views. In order to provide a 360 • analysis, [19] lately introduced safety rings which bend to indicate positions of dangerous vehicles. Analogically, lateral lane change plus longitudinal speed recommendation can be conveyed by visual HMIs [20].…”

Section: B Related Workmentioning

confidence: 99%

Proactive Risk Navigation System for Real-World Urban Intersections

Puphal

Flade

Geus

et al. 2020

2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)

View full text Add to dashboard Cite

We consider the problem of intelligently navigating through complex traffic. Urban situations are defined by the underlying map structure and special regulatory objects of e.g. a stop line or crosswalk. Thereon dynamic vehicles (cars, bicycles, etc.) move forward, while trying to keep accident risks low.Especially at intersections, the combination and interaction of traffic elements is diverse and human drivers need to focus on specific elements which are critical for their behavior. To support the analysis, we present in this paper the so-called Risk Navigation System (RNS). RNS leverages a graph-based local dynamic map with Time-To-X indicators for extracting upcoming sharp curves, intersection zones and possible vehicleto-object collision points.In real car recordings, recommended velocity profiles to avoid risks are visualized within a 2D environment. By focusing on communicating not only the positional but also the temporal relation, RNS potentially helps to enhance awareness and prediction capabilities of the user.

show abstract

“…An iterative alternating normalization of the row and column sums of M is applied afterwards to ensure the constraints in (1).…”

Section: B Icp Map Matching With Orientation Aided Softassign and Dementioning

confidence: 99%

“…In future vehicles, the different assistance systems will have to be integrated cooperatively and rely on a common base of environment perception. This approach was investigated within the Proreta 3 project [1], which included the development of an appropriate commonly usable environment representation that describes static scenery and relevant dynamic objects. Such representation was proposed in [2]- [4] in form of a Parametric Free Space (PFS) map combined with a dynamic object map.…”

Section: Introductionmentioning

confidence: 99%

Efficient graph-based V2V free space fusion

Luthardt

Han

Willert

et al. 2017

2017 IEEE Intelligent Vehicles Symposium (IV)

Self Cite

View full text Add to dashboard Cite

A necessary prerequisite for future driver assistance systems as well as automated driving is a suitable and accurate representation of the environment around the vehicle with a sufficient range. To extend the range of the environment representation, sharing the environment detections of multiple vehicles via vehicle-to-vehicle (V2V) communication is a promising approach. In this paper, we present a method to fuse shared free space detections from multiple vehicles. The detections are represented as Parametric Free Space (PFS) maps, which are especially suitable for real-time radio V2Vtransmission due to their compactness. A graph-based algorithm to fuse PFS maps is proposed that solves possible contradictions between the maps and incorporates the maps' uncertainty attributes. By solely operating on the contour, the fusion can be carried out by a simple path search in a fusion graph that is constructed from the maps. This results in an efficient method that finds the fusion result within few iterations. To account for possible errors in the relative poses between the PFS maps, we furthermore present an adapted Iterative Closest Point (ICP) matching to align the maps before the fusion. Therein we employ a modified soft-assign scheme for robust outlier rejection, and incorporate the PFS maps' boundary orientation to improve the matching process. We show the capabilities of our method by presenting results on real test drive data.

show abstract

PRORETA 3: Comprehensive Driver Assistance by Safety Corridor and Cooperative Automation

Cited by 11 publications

References 11 publications

Influence of Blind Spot Assistance Systems in Heavy Commercial Vehicles on Accident Reconstruction

Influence of Blind Spot Assistance Systems in Heavy Commercial Vehicles on Accident Reconstruction

Proactive Risk Navigation System for Real-World Urban Intersections

Efficient graph-based V2V free space fusion

Contact Info

Product

Resources

About