FESTA. Handbook version 2

In Japan and in the United States Field Operational Tests (FOTs) have been introduced as an evaluation method for driver support systems and other functions several years ago with the aim of proving that such systems can deliver real‐world benefits. In Europe too, FOTs have been conducted at a national or regional level, particularly on speed support systems and lane departure warning systems. These FOTs have proven to be highly valuable. Recently FOTs have been identified as an important means of verifying the real‐world impacts of new systems at a European level and in particular to verify that European R&D has the potential to deliver identifiable benefits. This Handbook is the result of a joint effort of several research institutes, OEMs and other stakeholders from across Europe to prepare a common methodology for European FOTs. It is also highly relevant, and it is hoped useful, for FOTs conducted at a regional or national level within Europe as well as outside Europe

FESTA. D2.6: Socio-economic impact assessment for driver assistance systems

This deliverable provides further advice on the methodology for socio-economic assessment of ICT based systems, within the Field Operational Tests (FOTs) being part-funded by the European Commission. It can be treated as a supplement to Chapter 9 of the FESTA Handbook. Use of a consistent methodology in the FOTs will maximise the comparability of the results across regions, ICT systems and individual FOTs. The goal of this deliverable is therefore to provide concise advice on how to carry out a socio-economic impact assessment, addressing issues likely to arise and giving references to more detailed guidance elsewhere, plus examples of good practice in existing (web) documents. Topics covered by this document include: • the assessment framework; • the approach to specific stakeholders as part of the wider picture; • scope of the assessment - which impacts should be included; • analysis methods for specific impacts; • financial analysis; • data needs. Data will be one of the keys to success for the FOTs. This deliverable provides advice on which data will need to be collected during the FOT itself, i.e. 'FOT-specific data' (with implications for the design of FOTs), as well as generic data needed to carry out a socio-economic assessment. The latter include values for accident and casualty reduction. This advice will be useful for: clients commissioning FOTs; consortia drawing up proposals for FOTs; and organisations carrying-out FOTs. It is assumed that a specialist in the area of socioeconomic impact assessment will carry out the analysis - so a full "tutorial" on socio-economic assessment is neither feasible nor necessary in this deliverable. We will refer to this specialist as the “analyst”. The advice was prepared by a group of European experts in the area of stand-alone and cooperative vehicle ICT systems and socio-economic impact assessment. Their experience was enriched by a literature review of over twenty state-of-the-art sources, covering methodologies and applications in studies and FOTs from Europe, Australia and the United States. Taking into account the findings of those studies and the experience of the team, an assessment methodology was specified: cost-benefit analysis (CBA) was chosen as the overall framework for assessment

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

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 Leistungsfähigkeit, 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 Übergang von einer quantitativen Kilometerzahl zu einer qualitativen Testabdeckung zu ermöglichen. Die adaptive Testabdeckung zielt somit auf einen Kompromiss zwischen Effizienz- und Effektivitätskriterien für 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 für die Anforderungen der Teststrategie werden hochautomatisierte Testansätze entwickelt. Dementsprechend wird jeder Testansatz mit seinen jeweiligen Testzielen integriert, um die Basis eines kontextgesteuerten Testkonzepts zu realisieren. Die wesentlichen Beiträge dieser Arbeit befassen sich mit vier Schwerpunkten: * Zunächst wird ein Co-Simulationsansatz präsentiert, mit dem sich die Sensoreingänge in einem Hardware-in-the-Loop-Prüfstand mithilfe synthetischer Fahrszenarien simulieren und/ oder stimulieren lassen. Der vorgestellte Aufbau bietet einen phänomenologischen Modellierungsansatz, um einen Kompromiss zwischen der Modellgranularität und dem Rechenaufwand der Echtzeitsimulation zu erreichen. Diese Methode wird für eine modulare Integration von Simulationskomponenten, wie Verkehrssimulation und Fahrdynamik, verwendet, um relevante Phänomene in kritischen Fahrszenarien zu modellieren. * Danach wird ein Messtechnik- und Datenanalysekonzept für 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 länderspezifischen Feldversuchen werden aufgezeichnet und zentral in einer Cloud-Datenbank gespeichert. * Anschließend wird ein ontologiebasierter Ansatz zur Integration einer komplementären 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 ausführbare Szenario-Spezifikationen erweitert. * Schließlich wird eine prospektive Risikobewertung als invertiertes Konfidenzniveau der messbaren Sicherheit mithilfe von Sensitivitäts- und Zuverlässigkeitsanalysen durchgeführt. Der Versagensbereich kann im Parameterraum identifiziert werden, um die Versagenswahrscheinlichkeit für jedes extrahierte logische Szenario durch verschiedene Stichprobenverfahren, wie beispielsweise die Monte-Carlo-Simulation und Adaptive-Importance-Sampling, vorherzusagen. Dabei führt die geschätzte Wahrscheinlichkeit einer Sicherheitsverletzung für jedes gruppierte logische Szenario zu einer messbaren Sicherheitsvorhersage. Das vorgestellte Framework erlaubt es, die Lücke zwischen wissensbasierten und datengetriebenen Testplattformen zu schließen, um die Wissensbasis für die Abdeckung der Operational Design Domains konsequent zu erweitern. Zusammenfassend zeigen die Ergebnisse den Nutzen und die Herausforderungen des entwickelten Frameworks für messbare Sicherheit durch ein Vertrauensmaß der Risikobewertung. Dies ermöglicht eine kosteneffiziente Erweiterung der Validität der Testdomäne im gesamten Softwareentwicklungsprozess, um die erforderlichen Testabbruchkriterien zu erreichen

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

Identifikation von Beinahekollisionen in maritimen Verkehrsdaten als Ground-Truth für szenariobasiertes Testen

Diese Arbeit geht der Frage nach, wie sich validierungsrelevante Beinahekollisionssituationen aus historischen Verkehrsdaten detektieren und als Ground Truth nutzen lassen. Nach der Sichtung des Stands der Technik werden Anforderungen an die Datenerhebung, Datenspeicherung, sowie die Datenanalyse erhoben und ein entsprechendes Konzept erstellt. Zur Bestimmung von Beinahekollisionen werden zunächst die relevanten Einflussfaktoren hergeleitet und es folgt, gemäß der Definition, die Entwicklung mehrerer Methoden und Werkzeuge zur Identifikation von fahrerreaktionsbasierten, funktionsreaktionsbasierten, kontextbasierten und historienbasierten Auffälligkeiten. Als Vorbereitung auf die Evaluation schließt sich die Implementierung und Integration der Systemartefakte in das maritime Testfeld eMIR an. Es kann gezeigt werden, dass der Ansatz zur objektiven Erkennung von Beinahekollisionen geeignet ist und als Ground Truth für das szenariobasierte Testen eingesetzt werden kann

A REAL-TIME TRAFFIC CONDITION ASSESSMENT AND PREDICTION FRAMEWORK USING VEHICLE-INFRASTRUCTURE INTEGRATION (VII) WITH COMPUTATIONAL INTELLIGENCE

This research developed a real-time traffic condition assessment and prediction framework using Vehicle-Infrastructure Integration (VII) with computational intelligence to improve the existing traffic surveillance system. Due to the prohibited expenses and complexity involved for the field experiment of such a system, this study adopted state-of-the-art simulation tools as an efficient alternative. This work developed an integrated traffic and communication simulation platform to facilitate the design and evaluation of a wide range of online traffic surveillance and management system in both traffic and communication domain. Using the integrated simulator, the author evaluated the performance of different combination of communication medium and architecture. This evaluation led to the development of a hybrid VII framework exemplified by hierarchical architecture, which is expected to eliminate single point failures, enhance scalability and easy integration of control functions for traffic condition assessment and prediction. In the proposed VII framework, the vehicle on-board equipments and roadside units (RSUs) work collaboratively, based on an intelligent paradigm known as \u27Support Vector Machine (SVM),\u27 to determine the occurrence and characteristics of an incident with the kinetics data generated by vehicles. In addition to incident detection, this research also integrated the computational intelligence paradigm called \u27Support Vector Regression (SVR)\u27 within the hybrid VII framework for improving the travel time prediction capabilities, and supporting on-line leaning functions to improve its performance over time. Two simulation models that fully implemented the functionalities of real-time traffic surveillance were developed on calibrated and validated simulation network for study sites in Greenville and Spartanburg, South Carolina. The simulation models\u27 encouraging performance on traffic condition assessment and prediction justifies further research on field experiment of such a system to address various research issues in the areas covered by this work, such as availability and accuracy of vehicle kinetic and maneuver data, reliability of wireless communication, maintenance of RSUs and wireless repeaters. The impact of this research will provide a reliable alternative to traditional traffic sensors to assess and predict the condition of the transportation system. The integrated simulation methodology and open source software will provide a tool for design and evaluation of any real-time traffic surveillance and management systems. Additionally, the developed VII simulation models will be made available for use by future researchers and designers of other similar VII systems. Future implementation of the research in the private and public sector will result in new VII related equipment in vehicles, greater control of traffic loading, faster incident detection, improved safety, mitigated congestion, and reduced emissions and fuel consumption

Car crashes with two-wheelers in China: Proposal and assessment of C-NCAP automated emergency braking test scenarios

In China, around 15,000 users of two-wheelers (TWs) die on the road every year. Passenger cars are the dominating crash opponent of TWs in road traffic crashes. Understanding the characteristics of car crashes with TWs is essential to enhance cars’ safety performance and improve the safety of TW riders in China. This thesis has three objectives. First, to define test scenarios of Automated Emergency Braking systems for cars encountering TWs (TW-AEB) in China (Paper I). Second, to assess whether cars with good ratings in consumer safety rating programs (e.g., New Car Assessment Program: NCAP) are also likely to perform well in the real-world. Finally, to understand the characteristics of the car crashes with TWs after the TW-AEB application. To achieve the first objective, cluster analysis was applied to the China In-Depth Accident Study (CIDAS). The results were six test scenarios (Paper I), which are proposed for the Chinese NCAP (C-NCAP) TW-AEB testing. To achieve the second and third objectives, counterfactual virtual simulations were performed with and without TW-AEB to a) a C-NCAP TW-AEB test scenario set ; b) an alternative scenario set based on the results of Paper I; and c) real-world crashes in China. Results show much higher crash avoidance rate and lower impact speed were found for C-NCAP scenario set than for the other two sets. To better reflect car crashes with TW in China, longitudinal same-direction scenarios with the car or TW turning and perpendicular scenarios with high TW traveling speed are recommended to be included in C-NCAP future releases. Future work will focus on assessing the combined benefit of preventive and protective safety systems for car-to-TW crashes in China

Evaluating the Impacts of Accelerated Incident Clearance Tools and Strategies by Harnessing the Power of Microscopic Traffic Simulation

Traffic incidents cause Americans delay, waste fuel, cause injuries, and create toxic emissions. Transportation professionals have implemented a variety of tools to manage these impacts and researchers have studied their effectiveness, illustrating a wide range between different tools and locations. To improve this state of knowledge, this dissertation sought to 1) identify prominent and effective incident management strategies, 2) model six selected incident management strategies within five highway corridors in South Carolina, and 3) apply benefit-cost analysis to evaluate the impact of various combinations of these strategies. To meet these objectives, the author evaluated published literature of the selected strategies, administered a nationwide survey of these strategies, conducted traffic simulation, and performed benefit-cost analysis. The literature review guided the author to fill gaps in knowledge regarding the effectiveness and expense of identified strategies. The nationwide survey identified effective incident management tools, the extent of their adoption, and their common problems. The author then applied PARAMICS traffic simulation software to evaluate the impact of six tools at five sites on metropolitan interstates throughout South Carolina. Finally, benefit-cost analysis was used to evaluate the benefits against costs at each study site. The survey provided many insights into both the effectiveness and collaboration within and among traffic incident management agencies and guided the author in selecting tools for evaluation. While the simulation study found that as the severity and duration of incident increases, so does the potential benefit of incident management tools, the frequency of incidents also produces significant impact on annual benefits. The benefit-cost analysis indicated that while all the incident management tools evaluated provided more benefits than costs, freeway service patrols and traffic cameras produced the highest return for incidents of varying severity. It was also found more advantageous to select one expensive but efficient incident management technology, rather than engage in the incremental deployment of various systems that might provide redundant benefits. Departments of transportation across the United States see the need to manage incidents more efficiently, consequently this dissertation developed data and analysis to compare benefits with costs to aid decision makers in selecting tools and strategies for future incident management endeavors