Verkehrsdatenerfassung mit Bluetooth-Detektion: Möglichkeiten und Grenzen

Die vorliegende Arbeit beschäftigt sich mit dem Einsatz der Bluetooth‐Technologie als Verkehrsdetektor zur Erfassung von Verkehrsströmen. Sie legt die Eigenschaften und Charakteristiken dieser Technik dar und stellt diese in den Kontext gängiger Detektionsverfahren. Anhand der Betrachtung qualitativer Anforderungsaspekte sowie potentieller Einsatzbereiche werden Stärken und Schwächen der Technologie und somit die Eignung für die Verkehrserfassung auf theoretischer Ebene analysiert. Der Vergleich zu anderen Detektoren ermöglicht die Einordnung in den Gesamtkomplex der Verkehrserfassungssysteme. Eine praktische Umsetzung ermöglicht schließlich die empirisch gestützte Validierung der theoretischen Erkenntnisse und kennzeichnet die Möglichkeiten und Grenzen der Bluetooth‐Technologie im Praxiseinsatz. Mit Hilfe der theoretisch und praktisch gewonnenen Erkenntnisse dieser Arbeit wird die Eignung der Bluetooth‐Detektion für Anwendungen im Straßenverkehrsmanagement verdeutlicht

Trialing Innovative Technologies in Crisis Management - “Airborne and Terrestrial Situational Awareness” as Support Tool in Flood Response

Flooding represents the most-occurring and deadliest threats worldwide among natural disasters. Consequently, new technologies are constantly developed to improve response capacities in crisis management. The remaining challenge for practitioner organizations is not only to identify the best solution to their individual demands, but also to test and evaluate its benefit in a realistic environment before the disaster strikes. To bridge the gap between theoretic potential and actual integration into practice, the EU-funded project DRIVER+ has designed a methodical and technical environment to assess innovation in a realistic but non-operational setup through trials. The German Aerospace Center (DLR) interdisciplinary merged mature technical developments into the “Airborne and terrestrial situational awareness” system and applied it in a DRIVER+ Trial to promote a sustainable and demand-oriented R&D. Experienced practitioners assessed the added value of its modules “KeepOperational” and “ZKI” in the context of large-scale flooding in urban areas. The solution aimed at providing contextual route planning in police operations and extending situational awareness based on information derived through aerial image processing. The user feedback and systematically collected data through the DRIVER + Test-bed approved that DLR’s system could improve transport planning and situational awareness across organizations. However, the results show a special need to consider, for example, cross-domain data-fusion techniques to provide essential 3D geo-information to effectively support specific response tasks during flooding

Determining Optimal Fleet Distribution for Dynamic Indirect Traffic Detection based on Bluetooth

Highly accurate spatio-temporal traffic data (e.g. origin destination matrices, route flows and paths) can be obtained by the newly developed Dynamic Indirect Traffic Detection (DITD) approach, which was recently developed by the German Aerospace Center. DITD enables an efficient and powerful traffic monitoring and control system on the basis of wireless communication systems, which minimizes the number of costly stationary traffic detection infrastructure (e.g. traffic sensors, detection gantries, etc.) and thus will be superior to existing costly traffic detection systems. With DITD all detections are made indirectly by traffic observers using wireless radio-based technologies (e.g. Bluetooth/Wi-Fi) while passing other traffic objects (vehicles, cyclists, pedestrians). Since many traffic participants use devices with activated Bluetooth/Wi-Fi functionality (e.g. mobile phones), a car equipped with a specific receiver (Mobile Traffic Observer Unit - MTOU) detects all traffic objects featuring Bluetooth/Wi-Fi devices and being in the detection area by their identification number. Augmented by time stamps and positions of the observer, the measured data can be processed to trajectories, travel times, etc. Due to the novelty of this approach several fundamental research questions have not been answered yet. For instance, questions regarding to the required number of cars featuring the MTOU, the size of the underlying network and the amount of edges and intersections which have to be contained or the mileage of the vehicle fleet are required to be answered to put the method into practice and to prove the approach to determine high quality traffic data. In this paper, the research will be taken to the next level. Hence, the focus is now on the optimal distribution of the equipped vehicle fleet within the network. By the use of analytical and model respective simulation based methods fleet related parameters like vehicle fleet flow rates and detection rates per edge and time interval as well as network related parameters like the amount of travelled kilometers or the sum of covered edges are identified to determine effective spatio-temporal mileages of the fleet and optimal dispersion patterns for given networks. In addition, the coverage effectiveness of different fleet types will be analysed too. Referring to the routing, there are two different fleet types to be determined within this study: observer cars with randomly chosen routes on the one hand, and preassigned routes as in the case of taxi or mail car fleets on the other hand. According to the fleet types’ characters diverse operating ranges are expected to occur. The mentioned research study refers to an internal project of the German Aerospace Center dealing with the improvement of the efficiency, safety and environmental friendliness of mobility and traffic and transportation management at different DLR sites in everyday life. Therefore, a concept is implemented, which includes traffic detection, simulation, communication, control and benchmark issues. Within this project the presented approach will be put in practice to display applicability in real environment

Conceptual Approach for Determining Penetration Rates for Dynamic Indirect Traffic Detection

An efficient traffic management requires current and area-wide traffic data. Today different systems exist on highways, main roads and major arteries for a comprehensive traffic collection. It is the goal of traffic authorities world-wide to obtain highly accurate spatialtemporal traffic data without installation of costly and deteriorating physically invasive infrastructure in inner-city and rural areas, too. Therefore, a novel approach for an efficient and low-cost large-scale traffic monitoring was presented in further proceedings, which augments the Floating Car Data (FCD) principles by an anonymous indirect detection of traffic objects (cars, cyclists, pedestrians) using cars which are equipped with specific radio-based Bluetooth/Wi-Fi receivers. By introducing a conceptual method the presented paper deliberates to the question how many equipped cars are required to derive dynamic high quality traffic information on the basis of this new approach

Bluetooth-based Floating Car Observer: Model Evaluation using Simulation and Field Measurements

This paper depicts a Bluetooth-enabled Floating Car Observer approach to monitor Bluetooth-enabled traffic participants, in order to generate real-time spatiotemporal traffic data in a road network. By using Bluetooth as sensing module traffic objects such as vehicles, cyclists, pedestrians which are equipped with Bluetooth-enabled devices can be observed. Due to the specific Bluetooth connection establishment behaviour a Bluetooth-enabled device can be recognised on every point within the road network by using its unique identifier address. Hence, particularly desired traffic information such as origin-destination information can be derived. A major drawback of that kind of traffic monitoring is the prediction of the likelihood of a (re)-detection of such a Bluetooth-enabled traffic object. Since Bluetooth has a specific detection range and a complex connection establishment process, it is not clear, how long it takes to detect a device and where that device was exactly recognised within detection range. This paper tries to answer this question by introducing a theoretical model to describe the detection process as an exponential distribution and to determine it specific properties such as the encounter rate of Bluetooth-FCO and detectable traffic objects. To evaluate the analytical model, simulations as well as laboratory and field experiments with Bluetooth observers and detectable Bluetooth devices were conducted to measure detection rates as a function of encounter times

Performance Measurement of a Bluetooth-based Floating Car Observer

The German Aerospace Center (DLR) developed a traffic monitoring approach, called DYNAMIC, which combines the advantages of Floating Car Data (FCD) and Floating Observer Data (FOD) principles. DYNAMIC is based on detections which are made by floating traffic observers using wireless radio-based technologies such as Bluetooth while passing other traffic objects (vehicles, cyclists, pedestrians). For the evaluation of the performance of DYNAMIC it is crucial to know how likely it is that a detectable traffic object (i.e. with Bluetooth device on board) within the detection range will be monitored. The major point to answer this question is the inquiry process which sets up the connection between Bluetooth devices and which can take up to several seconds. Given the possibly high speed of the vehicles and the relatively small detection range this poses a major problem to this detection mechanism. Within the paper an analytical model of the time it takes an observer to discover traffic objects nearby is introduced. Therefore, the device discovery process will be described as an exponential distribution, that is, the number of detections based on Bluetooth is a sequence of independent respectively seen or not seen trials each of which occurs with a certain probability. This follows from the assumption that the number of vehicles equipped with Bluetooth devices and the number of observer vehicles within the network is small, so that the chances to encounter are statistically independent events. To evaluate the analytical model, simulations as well as laboratory and field experiments with Bluetooth receivers and senders were conducted to measure detection rates as a function of inquiry times. On that base the performance is analysed using measures as the penetration rate, the encounter rate as well as the detection and redetection rate. By introducing a theoretical model, it is possible to describe the detection process as an exponential distribution and to determine its specific properties such as the encounter rate of Bluetooth-FCO and detectable traffic objects. The results of the field measurement indicate a good accordance to the simulation model results. Still the functions look different enough to require some further adaptions of the parameters. Since broader field test (e.g. with a higher amount of observing vehicles) are difficult to conduct due to economic reasons, the simulation offers a wide range of possible further research studies