1,177 research outputs found
Technology transfer: Transportation
The application of NASA derived technology in solving problems related to highways, railroads, and other rapid systems is described. Additional areas/are identified where space technology may be utilized to meet requirements related to waterways, law enforcement agencies, and the trucking and recreational vehicle industries
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Camera-Based Articulation Angle Sensing for Heavy Goods Vehicles
Articulation angle sensing is an essential component of manoeuvrability and stability control systems for articulated heavy goods vehicles, particularly long combination vehicles. Existing solutions to this sensing task are limited by reliance on trailer modifications or information or by measurement accuracy, or both, restricting commercial adoption. In this paper we present a purely tractor-based sensor concept comprising a rear-facing camera and the parallel tracking and mapping (PTAM) image processing algorithm. The system requires no prior knowledge of or modifications to the trailer, is compatible with planar and non-planar trailer shapes, and with multiply-articulated vehicle combinations. The system is validated in full-scale vehicle tests on both a tractor semi-trailer combination and a truck and full-trailer combination, demonstrating robust performance in a number of conditions, including trailers with non-planar geometry and with minimal visual features. Average RMS measurement errors of 1.19, 1.03 and 1.53 degrees were demonstrated for the semi-trailer and full-trailer (drawbar and semi-trailer) respectively. This compares favourably with the state-of-the-art in the published literature. A number of improvements are proposed for future development based on the observations in this research.This work was funded by the Cambridge Commonwealth,
European and International Trust (CCEIT), the Council for
Scientific and Industrial Research (CSIR, South Africa), and
the Cambridge Vehicle Dynamics Consortium (CVDC). At the
time of writing the Consortium consisted of the University of
Cambridge with the following partners from the heavy vehicle
industry: Anthony Best Dynamics, Camcon, Denby Transport,
Firestone Industrial Products, Goodyear, Haldex, MIRA, SDC
Trailers, Tinsley Bridge, Tridec, Volvo Trucks, and Wincanton
An Advanced Driver-Assistance System: Using Mono-Camera Vision-Based Detection and Tracking for Control of an Autonomous Vehicle
Advanced driver assistance systems used to increase the safety of everyday transportation are
increasingly common in todayâs automotive industry. In conducting research for the Texas
Department of Transportationâs Commercial Truck Platooning Project, an autonomous truck
capable of communicating with a manually driven lead vehicle can follow at close distances to
increase the fuel economy and safety of both vehicles. In the event of a communications failure,
however, the following vehicle requires immediate human intervention to regain control of the
vehicle. To increase the safety of these situations, a backup vision-based advanced driver
assistance system comprised of a separate camera and computer was developed and successfully
implemented in an autonomous vehicle.
The system is comprised of a controller that takes inputs from a truck detection algorithm and a
tracking algorithm that run in parallel at all times. The detection algorithm passes new detection
information to the tracking algorithm when available. In each frame of incoming video, the
tracking algorithm communicates the position of the lead vehicle to the controller. Based upon
the size of the detection and the intrinsic properties of the camera, the longitudinal distance to the
lead vehicle and the lateral error are calculated.
The detection, tracking, and control algorithms were implemented in an autonomous car. A
variety of lane changes and emergency stop maneuvers were successfully completed. GPS
position information was gathered during testing to validate the accuracy of the algorithms. The
results of the GPS information show that the tracking algorithm can encounter some error in
estimating the separation at large following distances of more than 30 meters. Overall, the single
camera system is capable of providing smooth and safe control in a variety of test scenarios
Measurable Safety of Automated Driving Functions in Commercial Motor Vehicles
With the further development of automated driving, the functional performance increases resulting in the need for new and comprehensive testing concepts. This doctoral work aims to enable the transition from quantitative mileage to qualitative test coverage by aggregating the results of both knowledge-based and data-driven test platforms. The validity of the test domain can be extended cost-effectively throughout the software development process to achieve meaningful test termination criteria
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Vision-based trailer pose estimation for articulated vehicles
Articulated Heavy Goods Vehicles (HGVs) are more efficient than conventional rigid lorries, but exhibit reduced low-speed manoeuvrability and high-speed stability. Technologies such as autonomous reversing and path-following trailer steering can mitigate this, but practical limitations of the available sensing technologies restrict their commercialisation potential. This dissertation describes the development of practical vision-based articulation angle and trailer off-tracking sensing for HGVs.
Chapter 1 provides a background and literature review, covering important vehicle technologies, existing commercial and experimental sensors for articulation angle and off-tracking measurement, and relevant vision-based technologies. This is followed by an introduction to pertinent computer vision theory and terminology in Chapter 2.
Chapter 3 describes the development and simulation-based assessment of an articulation angle sensing concept. It utilises a rear-facing camera mounted behind the truck or tractor, and one of two proposed image processing methods: template-matching and Parallel Tracking and Mapping (PTAM). The PTAM-based method was shown to be the more accurate and versatile method in full-scale vehicle tests. RMS measurement errors of 0.4-1.6 were observed in tests on a tractor semi-trailer (Chapter 4), and 0.8-2.4 in tests on a Nordic combination with two articulation points (Chapter 5). The system requires no truck-trailer communication links or artificial markers, and is compatible with multiple trailer shapes, but was found to have increasing errors at higher articulation angles.
Chapter 6 describes the development and simulation-based assessment of a trailer off-tracking sensing concept, which utilises a trailer-mounted stereo camera pair and visual odometry. The concept was evaluated in full-scale tests on a tractor semi-trailer combination in which camera location and stereo baseline were varied, presented in Chapter 7. RMS measurement errors of 0.11-0.13 m were obtained in some tests, but a sensitivity to camera alignment was discovered in others which negatively affected results. A very stiff stereo camera mount with a sub-0.5 m baseline is suggested for future experiments.
A summary of the main conclusions, a review of the objectives, and recommendations for future work are given in Chapter 8. Recommendations include further refinement of both sensors, an investigation into lighting sensitivity, and alternative applications of the sensors.This work was supported by a "CSIR South Africa Cambridge Scholarship", funded jointly by the Cambridge Commonwealth, European & International Trust and the Council for Scientific & Industrial Research (CSIR South Africa)
Measurable Safety of Automated Driving Functions in Commercial Motor Vehicles - Technological and Methodical Approaches
Fahrerassistenzsysteme sowie automatisiertes Fahren leisten einen wesentlichen Beitrag zur Verbesserung der Verkehrssicherheit von Kraftfahrzeugen, insbesondere von Nutzfahrzeugen. Mit der Weiterentwicklung des automatisierten Fahrens steigt hierbei die funktionale LeistungsfÀhigkeit, woraus Anforderungen an neue, gesamtheitliche Erprobungskonzepte entstehen. Um die Absicherung höherer Stufen von automatisierten Fahrfunktionen zu garantieren, sind neuartige Verifikations- und Validierungsmethoden erforderlich.
Ziel dieser Arbeit ist es, durch die Aggregation von Testergebnissen aus wissensbasierten und datengetriebenen Testplattformen den Ăbergang von einer quantitativen Kilometerzahl zu einer qualitativen Testabdeckung zu ermöglichen. Die adaptive Testabdeckung zielt somit auf einen Kompromiss zwischen Effizienz- und EffektivitĂ€tskriterien fĂŒr die Absicherung von automatisierten Fahrfunktionen in der Produktentstehung von Nutzfahrzeugen ab.
Diese Arbeit umfasst die Konzeption und Implementierung eines modularen Frameworks zur kundenorientierten Absicherung automatisierter Fahrfunktionen mit vertretbarem Aufwand. Ausgehend vom Konfliktmanagement fĂŒr die Anforderungen der Teststrategie werden hochautomatisierte TestansĂ€tze entwickelt. Dementsprechend wird jeder Testansatz mit seinen jeweiligen Testzielen integriert, um die Basis eines kontextgesteuerten Testkonzepts zu realisieren. Die wesentlichen BeitrĂ€ge dieser Arbeit befassen sich mit vier Schwerpunkten:
* ZunĂ€chst wird ein Co-Simulationsansatz prĂ€sentiert, mit dem sich die SensoreingĂ€nge in einem Hardware-in-the-Loop-PrĂŒfstand mithilfe synthetischer Fahrszenarien simulieren und/ oder stimulieren lassen. Der vorgestellte Aufbau bietet einen phĂ€nomenologischen Modellierungsansatz, um einen Kompromiss zwischen der ModellgranularitĂ€t und dem
Rechenaufwand der Echtzeitsimulation zu erreichen. Diese Methode wird fĂŒr eine modulare Integration von Simulationskomponenten, wie Verkehrssimulation und Fahrdynamik, verwendet, um relevante PhĂ€nomene in kritischen Fahrszenarien zu modellieren.
* Danach wird ein Messtechnik- und Datenanalysekonzept fĂŒr die weltweite Absicherung von automatisierten Fahrfunktionen vorgestellt, welches eine Skalierbarkeit zur Aufzeichnung von Fahrzeugsensor- und/ oder Umfeldsensordaten von spezifischen Fahrereignissen einerseits und permanenten Daten zur statistischen Absicherung und Softwareentwicklung andererseits erlaubt. Messdaten aus lĂ€nderspezifischen Feldversuchen werden aufgezeichnet und zentral in einer Cloud-Datenbank gespeichert.
* AnschlieĂend wird ein ontologiebasierter Ansatz zur Integration einer komplementĂ€ren Wissensquelle aus Feldbeobachtungen in ein Wissensmanagementsystem beschrieben. Die Gruppierung von Aufzeichnungen wird mittels einer ereignisbasierten Zeitreihenanalyse mit hierarchischer Clusterbildung und normalisierter Kreuzkorrelation realisiert. Aus dem extrahierten Cluster und seinem Parameterraum lassen sich die Eintrittswahrscheinlichkeit jedes logischen Szenarios und die Wahrscheinlichkeitsverteilungen der zugehörigen Parameter ableiten. Durch die Korrelationsanalyse von synthetischen und naturalistischen Fahrszenarien wird die anforderungsbasierte Testabdeckung adaptiv und systematisch durch ausfĂŒhrbare Szenario-Spezifikationen erweitert.
* SchlieĂlich wird eine prospektive Risikobewertung als invertiertes Konfidenzniveau der messbaren Sicherheit mithilfe von SensitivitĂ€ts- und ZuverlĂ€ssigkeitsanalysen durchgefĂŒhrt. Der Versagensbereich kann im Parameterraum identifiziert werden, um die Versagenswahrscheinlichkeit fĂŒr jedes extrahierte logische Szenario durch verschiedene Stichprobenverfahren, wie beispielsweise die Monte-Carlo-Simulation und Adaptive-Importance-Sampling, vorherzusagen. Dabei fĂŒhrt die geschĂ€tzte Wahrscheinlichkeit einer Sicherheitsverletzung fĂŒr jedes gruppierte logische Szenario zu einer messbaren Sicherheitsvorhersage.
Das vorgestellte Framework erlaubt es, die LĂŒcke zwischen wissensbasierten und datengetriebenen Testplattformen zu schlieĂen, um die Wissensbasis fĂŒr die Abdeckung der Operational Design Domains konsequent zu erweitern.
Zusammenfassend zeigen die Ergebnisse den Nutzen und die Herausforderungen des entwickelten Frameworks fĂŒr messbare Sicherheit durch ein VertrauensmaĂ der Risikobewertung. Dies ermöglicht eine kosteneffiziente Erweiterung der ValiditĂ€t der TestdomĂ€ne im gesamten Softwareentwicklungsprozess, um die erforderlichen Testabbruchkriterien zu erreichen
Supply Chain Based Solution to Prevent Fuel Tax Evasion: Proof of Concept Final Report
The goal of this research was to provide a proof-of-concept (POC) system for preventing non-taxable (non-highway diesel use) or low-taxable (jet fuel) petrochemical products from being blended with taxable fuel products and preventing taxable fuel products from cross-jurisdiction evasion. The research worked to fill the need to validate the legitimacy of individual loads, offloads, and movements by integrating and validating, on a near-real-time basis, information from global positioning system (GPS), valve sensors, level sensors, and fuel-marker sensors
Measurable Safety of Automated Driving Functions in Commercial Motor Vehicles
With the further development of automated driving, the functional performance increases resulting in the need for new and comprehensive testing concepts. This doctoral work aims to enable the transition from quantitative mileage to qualitative test coverage by aggregating the results of both knowledge-based and data-driven test platforms. The validity of the test domain can be extended cost-effectively throughout the software development process to achieve meaningful test termination criteria
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