D6.3 - Press Releases

Besides other dissemination activities like the Project Brochure, the Project Website, and the publication and presentation of Articles on Workshops, Conferences and in Journals, press releases are a means of making the project known to interested parties. This deliverable gives the SimpleFleet Press Releases until March 2014

Exact BDD Minimization for Path-Related Objective Functions

Abstract. In this paper we investigate the exact optimization of BDDs with respect to path-related objective functions. We aim at a deeper understanding of the computational effort of exact methods targeting the new objective functions. This is achieved by an approach based on Dynamic Programming which generalizes the framework of Friedman and Supowit. A prime reason for the computational complexity can be identified using this framework. For the first time, experimental results give the minimal expected path length of BDDs for benchmark functions. They have been obtained by an exact Branch&Bound method which can be derived from the general framework. The exact solutions are used to evaluate a heuristic approach. Apart from a few exceptions, the results prove the high quality of the heuristic solutions

Lower bounds for dynamic BDD reordering

Abstract — In this paper we present new lower bounds on BDD size. These lower bounds are derived from more general lower bounds that recently were given in the context of exact BDD minimization. The results presented in this paper are twofold: first, we gain deeper insight by looking at the theory behind the new lower bounds. Examples lead to a better understanding, showing that the new lower bounds are effective in situations where this is not the case for previous lower bounds and vice versa. Following the constraints in practice, we then compromise between runtime and quality of the lower bounds. Finally, a clever combination of old and new lower bounds results in a final lower bound, yielding a significant improvement. Experimental results show the efficiency of our approach. I

Automatic relocation of link related data in an updated road map

For a rising number of ITS applications, location information obtained by the processing of sensor data is related to the links of a specific digital road map. Such maps are available from different vendors like Here, TomTom/TeleAtlas and OSM. They are created with different philosophies, resulting in significant differences in the geometry and the topology of the road networks. If a map needs to be updated to a new release, the user faces the problem that a relocation of any annotated location data, i.e. a proper mapping of these locations from the old to the new map becomes necessary. For this reason, DLR developed a new prototypic software application called DataRelocator@Map2Map. It enables the automatic relocation of location data between the two maps. Using this new tool, an almost fully automatic relocation is possible and thus the cost of service failures related to the map update can be avoided

A probabilistic framework for traffic data quality

Regarding the assessment of traffic data in ITS, there is an increasing need for answers to the following questions: (i) What exactly is "traffic data quality"?, and, related to that, (ii) There are too many ways to define and to do things, and results of different researchers are inconsistent or not comparable. How can we overcome this situation? With that background, an important aim of the ongoing DLR-project I.MoVe is to develop a consistent understanding of traffic data quality, together with a unified framework for its assessment. To this end, a probabilistic framework for traffic data quality is provided in this paper. Real-world examples from I.MoVe demonstrate its application for the assessment of data sources like induction loops, stationary bluetooth sensors and floating car data (FCD). A first important point is to distinguish strictly between quality indices, quality requirements, and quality itself. While the present framework develops quality indices based on established quality criteria like accuracy, completeness, validity, and coverage, the usual understanding of quality is extended to a probabilistic view. This also addresses the problem of information retrieval in the presence of vagueness and uncertainty. The provided examples are making full use of the proposed framework, and also constitute interesting results for the practitioner by themselves. Examples include the assessment of induction loop count data, and assessing the temporal coverage of a stretch of road with stationary bluetooth data, or of the whole city of Berlin, Germany with FCD

Improvements for Constraint Solving in the SystemC Verification Library

For verification of complex system-on-chip designs often constraint-based randomization is used. This allows to simulate scenarios that may be difficult to generate manually. For the system description language SystemC the SystemC Verification (SCV) Library has been introduced. Besides advanced verification features like data introspection and transaction recording the SCV library enables constraint-based randomization for SystemC models. However, the SystemC library has two disadvantages that restrict the practical use: There is no support of bit operators in SCV constraints and the SCV constraint solver cannot guarantee a uniform distribution of the constraint solutions. In this paper we provide a detailed analysis of these problems and present solutions that have been integrated in the library

D6.2 - SimpleFleet brochure and fact sheet

GPS positioning devices are becoming a commodity sensor platform with the emergence and popularity of smartphones and ubiquitous networking. While the positioning capability has been exploited in location-based services, so has its spatiotemporal cousin, tracking, so far only been considered in costly and complex fleet management applications. The proposed project, SimpleFleet will make it easy for SMEs, both, from a technological and business perspective, to create (Mobile) Web-based fleet management applications. For this purpose, we build a large data pool comprising base data such as maps and traffic data from dedicated providers. A simple interface will provide a means to connect user-contributed data streams to this pool. In addition and to increase the market potential of the data pool, we also want to address the related geomarketing domain, which uses travel information in various geo-statistical analysis methods as well as visualizations of the data to be used in online and print publications. An algorithmic framework dubbed “TrafficIntelligence” that includes map-matching algorithms, vehicle routing services and a statistics package will utilize the collected data and provide value-added service. SMEs will be able to access the data and services by means of a Web-based API, a Software Development Kit (SDK) wrapping API access for specific languages and environments and Application Frameworks for rapid application development for target platforms such as Web (JavaScript), and iPhone and Android mobile platforms

Utilizing historical and current travel times based on floating car data for management of an express truck fleet

During the last nine years, a couple of prototype ITS applications based on Floating Car Data (FCD) of taxi fleets have been developed at German Aerospace Center (DLR). A core application is a route guidance and monitoring system based on current and historical road segment travel times. Recently, it has been extended for use in the German funded project SmartTruck, run by a consortium consisting of the logistics key player DHL, DLR and the German Research Center for Artificial Intelligence (DFKI). An important aim of the project was the use of historical and current traffic information for energy-efficient, optimized offline planning and dynamic re-planning of the tours of DHL express trucks in Berlin, Germany. This paper discusses the architecture of the SmartTruck system and the methodology used to generate historic and current road segment travel times from positional data