Road Traffic Safety Research at DLR

Der Konferenzbeitrag gibt einen Überblick über Projekte und Methodik der Forschung im Bereich der Sicherheit im Straßenverkehr am Institut für Verkehrssystemtechnik des DLR. Dabei wird insbesondere auf die Verkehrskonflikttechnik, funktionale Zusammenhänge und Wirkungsanalysen eingegangen

Auslegung und Entwicklung einer Reluktanzmaschine in Sternschaltung (SRS)

Elektrische Maschinen welche die Reluktanzkraft ausnutzen um elektrische in mechanische Arbeit umzuwandeln, haben den Vorteil, dass sie ohne magnetische Permanenterregung ausgeführt werden können. Dies bringt Vorteile mit sich, welche insbesondere bei Fahrzeugantrieben eine Rolle spielen. So ermöglichen geringere Ummagnetisierungsverluste im Teillastbereich und damit ein geringeres Schleppmoment größere Reichweiten bei Elektrofahrzeugen. Bürstenlose Reluktanzmaschinen gemäß Stand der Technik haben jedoch eine um den Faktor 3 geringere Drehmomentdichte. Diese kann durch den Einsatz eines neuartigen Maschinenkonzeptes, des geschalteten Reluktanzmotors in Sternschaltung (SRS) um bis zu 50% gesteigert werden, sodass sich der Abstand von 1:3 auf 1:2 verringert. In diesem Vortrag wird der aktuelle Stand bei Auslegung und Entwicklung der SRS dargestellt

Boarding and Alighting Time of Passengers of the Berlin Public Transport System

The overall transportation speed is a significant factor influencing the attractiveness as well as the profitability of the transit system. If a vehicle needs less time to complete a tour, it can serve more tours and thus more passengers within the same time. Likewise, the passengers benefit from a decreased in-vehicle travel time. In this paper, the factors affecting the passenger transfer time are discussed for the case of Berlin, Germany. Furthermore, the paper presents the results of a survey that focuses (i) on the average time needed for passengers to board and alight a vehicle, (ii) its deviation, and (iii) the impact of the vehicle’s occupancy and number of boarding/alighting passengers. Such data can also be used to model the boarding and alighting process at stops in transport simulations in a more realistic way. For buses and subways, more passengers standing in the door area of a vehicle are found to slow down the boarding and alighting process. The Berlin specific policy to allow the boarding of a bus only at the first door induces a significantly higher boarding time per passenger

A smart data approach to traffic safety

This work demonstrates, how a large data-base of traffic crashes can be used to analyze ensemble data. It fused data from the German Unfallatlas (German Crash Database - GCDB) with Open Streetmap (OSM) data (both publicly available), and a database from the German Federal State Northrhine-Westfalia (NW) named NWSIB that provides additional information about each intersection, most importantly an estimate of the ADT-values and street view images. The results have to be taken with care, since the quality of the ADT's in the database is hard to control, and because this approach may have assignment errors. The results partially reproduce known findings; however, they allow in principle for a more detailed investigation of the relationship between crash-numbers and ADT-values than is possible with generalized linear models (glm). In line with the call, all the data, as well as the scripts that analyse the data are publicly available -- this text is entirely written in the Rmd format \citep{RStudio2022}, and most computations have been done in R \citep{R2021} and QGIS \citep{QGIS}

Observations on the Relationship between Crash Frequency and Traffic Flow

This work analyzes the relationship between crash frequency $N$ (crashes per hour) and exposure $Q$ (cars per hour) on the macroscopic level of a whole city. As exposure, the traffic flow is used here. Therefore, it analyzes a large crash database of the city of Berlin, Germany, together with a novel traffic flow database. Both data display a strong weekly pattern, and, if taken together, show that the relationship N(Q) is not a linear one. When Q is small, N grows like a second-order polynomial, while at large Q there is a tendency towards saturation, leading to an S-shaped relationship. Although visible in all data from all crashes, the data for the severe crashes display a less prominent saturation. As a by-product, the analysis performed here also demonstrates that the crash frequencies follow a negative binomial distribution, where both parameters of the distribution depend on the hour of the week, and, presumably, on the traffic state in this hour. The work presented in this paper aims at giving the reader a better understanding on how crash rates depend on exposure

Developing a Sensor Agnostic Infrastructure-Based Control Approach for Crossroad Assistance using Simulation

Crossroad assistance has the potential to contribute to a fair distribution of road space and increase the safety of all road users. This paper presents an infrastructure-based control approach to support crossroad assistance by implementing remote-controlled turning maneuvers on a test track. The approach involves several steps, including the detection of traffic events using camera- based object recognition, inserting dynamic objects into the simulation via V2X transmission, adding lanes and traffic signal phases through V2X data forwarding to a high-precision simulation map, trajectory prediction of all dynamic objects in the simulation, sending a trajectory list to the test vehicle, and providing feedback through the vehicle’s response to the trajectory list and re-detection of objects

Erkennung von Rissen mittels maschinellen Lernens

Instandhaltung ist eines der zentralen Themen für den Betreiber eines Schienennetzes. Um einen planmäßigen Schienenverkehr sicherzustellen, muss die zugrunde liegende Infrastruktur betriebsbereit gehalten werden. Dies geschieht, indem der momentane technische bzw. betriebliche Zustand der Infrastruktur bestimmt wird und Schäden, wie z. B. Risse in Schwellen, rechtzeitig erkannt werden. Vor diesem Hintergrund wird in diesem Beitrag dargestellt, wie ein modernes Verfahren des maschinellen Lernens für die Erkennung von Rissen in Bahnschwellen in das bestehende Erfassungssystem eines Messzuges der DB Netz AG (DB Netz) integriert worden ist

MAVEN Deliverable 6.4: Integration Final Report

This document presents the work that has been performed in WP6 after D6.3, and therefore focussing on the integration sprints 3-6. It describes which parts of the system are implemented and how they are put together. To do so, it builds upon the deliverables created so far, esp. D6.3 and all other deliverables of the underlying work packages 3, 4 and 5. Another important aspect for understanding the content of this deliverable is D2.1 [4] for the scenario definition of the whole MAVEN project, and the deliverables D6.1 [5] and D6.2 [6], which give an overview on the existing infrastructure and vehicles used in MAVEN