Driving in the Rain: A Survey toward Visibility Estimation through Windshields

Rain can significantly impair the driver’s sight and affect his performance when driving in wet conditions. Evaluation of driver visibility in harsh weather, such as rain, has garnered considerable research since the advent of autonomous vehicles and the emergence of intelligent transportation systems. In recent years, advances in computer vision and machine learning led to a significant number of new approaches to address this challenge. However, the literature is fragmented and should be reorganised and analysed to progress in this field. There is still no comprehensive survey article that summarises driver visibility methodologies, including classic and recent data-driven/model-driven approaches on the windshield in rainy conditions, and compares their generalisation performance fairly. Most ADAS and AD systems are based on object detection. Thus, rain visibility plays a key role in the efficiency of ADAS/AD functions used in semi- or fully autonomous driving. This study fills this gap by reviewing current state-of-the-art solutions in rain visibility estimation used to reconstruct the driver’s view for object detection-based autonomous driving. These solutions are classified as rain visibility estimation systems that work on (1) the perception components of the ADAS/AD function, (2) the control and other hardware components of the ADAS/AD function, and (3) the visualisation and other software components of the ADAS/AD function. Limitations and unsolved challenges are also highlighted for further research

Modelling, real-time simulation and control of automotive windscreen wiper systems for electronic control unit development

In recent years there has been a growth in the automotive industry, coupled with a growth in the amount of electronic components and systems in a modern vehicle. The higher amount of electronics has led to an increased amount of Electronic Control Units (ECU) in a vehicle which require advanced simulation based testing procedures throughout their development process. One such method is Hardware in the Loop (HIL) simulation in which a real ECU is connected to simulation models of its environment via a real-time simulator. This project is concerned with developing a plant model of a windscreen wiper system for use in the development of Jaguar Land Rover’s (JLR) body electronics ECU. The system is divided into four parts which are modelled separately: Wiper motor, linkages, arm and blades, and the windscreen environment. The wiper motor and mechanical elements models are derived and implemented using the physical modelling tools SimScape and SimMechanics. A dynamic friction model describing the interaction between the wiper blades and the windscreen is developed, based on results presented in the literature. A simple aerodynamic model describing the forces on the wiper blades is also established. The parameters of the models are derived using three sequential optimisation methods: Transfer function parameter identification, Genetic Algorithms (GA) and a nonlinear least squares local optimiser. A transfer function relating the motor current to the voltage was derived for step one, and a bespoke GA has been developed for step two. The parameters were successfully identified. Following this, Artificial Neural Networks (ANN) were used to convert the physical models into real-time capable models suitable for HIL simulation. Finally, adaptive control systems are designed in order to maintain the motor at a constant velocity. The models are presented in a Simulink library and graphical user interface modelling tool for ease of use

A service oriented virtual environment for complex system analysis: Preliminary report

Distributed virtual simulation is a capability that is increasing in demand within the automotive manufacturing industry. The distributed and networked approach to system level design and simulation stands to benefit from a unifying relational oriented modeling and simulation framework due to the large number of simulation technologies that must be integrated. This will also permit innovative use of existing independent simulations for increased concurrency in design and verification and validation. Through relational orientation, high level syntax and semantics for representing models and simulations have been developed for proof of concept analysis. This paper presents an approach to drive a process of analysis of the vehicle as a complex system through the combination of a relational trade-off analysis framework and a distributed simulation execution delivered through a service-oriented integration architecture. This promises to provide a rigorous, traceable and agile approach to early stage conceptual vehicle design and analysis

DIVIDER: Modelling and Evaluating Real-Time Service-Oriented Cyberphysical Co-Simulations

The ability to reliably distribute simulations across a distributed system and seamlessly integrate them as a workflow regardless of their level of abstraction is critical to improving the quality of product manufacturing. This paper presents the DIVIDER architecture for managing and maintaining real-time performance simulations integrated through SOAs. The described approach captures features present in complex workflow patterns such as asynchronous arbitrary cycles and estimates the worst case execution time in the context of the interfering execution environment

A demonstration of a service oriented virtual environment for complex system analysis

Distributed virtual simulation is increasingly in demand within the automotive industry. A distributed and networked approach to system level design and simulation stands to benefit from a unifying relational oriented modeling and simulation framework. This will permit innovative use of existing independent simulations for increased concurrency in design and verification and validation. This paper demonstrates an analysis of the vehicle as a complex system through the combination of a relational framework, high level syntax and semantics for representing models and distributed simulation. This promises to provide a rigorous, traceable and agile approach to conceptual vehicle design and analysis

Advanced flight control system study

The architecture, requirements, and system elements of an ultrareliable, advanced flight control system are described. The basic criteria are functional reliability of 10 to the minus 10 power/hour of flight and only 6 month scheduled maintenance. A distributed system architecture is described, including a multiplexed communication system, reliable bus controller, the use of skewed sensor arrays, and actuator interfaces. Test bed and flight evaluation program are proposed

VANET Applications: Hot Use Cases

Current challenges of car manufacturers are to make roads safe, to achieve free flowing traffic with few congestions, and to reduce pollution by an effective fuel use. To reach these goals, many improvements are performed in-car, but more and more approaches rely on connected cars with communication capabilities between cars, with an infrastructure, or with IoT devices. Monitoring and coordinating vehicles allow then to compute intelligent ways of transportation. Connected cars have introduced a new way of thinking cars - not only as a mean for a driver to go from A to B, but as smart cars - a user extension like the smartphone today. In this report, we introduce concepts and specific vocabulary in order to classify current innovations or ideas on the emerging topic of smart car. We present a graphical categorization showing this evolution in function of the societal evolution. Different perspectives are adopted: a vehicle-centric view, a vehicle-network view, and a user-centric view; described by simple and complex use-cases and illustrated by a list of emerging and current projects from the academic and industrial worlds. We identified an empty space in innovation between the user and his car: paradoxically even if they are both in interaction, they are separated through different application uses. Future challenge is to interlace social concerns of the user within an intelligent and efficient driving

No Ground Truth at Sea – Developing High-Accuracy AI Decision-Support for Complex Environments

As AI decision-support systems are increasingly developed for applications outside of traditional organizational confinements, developers are confronted with new sources of complexity they need to address. However, we know little about how AI applications are developed for natural use domains with high environmental complexity, stemming from physical influences outside of the developers’ control. This study investigates what challenges emerge from such complexity and how developers mitigate them. Drawing upon a rich longitudinal single-case study on the development of AI decision-support for maritime navigation, findings show that achieving high output accuracy is complicated by the physical environment hindering training data creation. Further, developers chose to reduce the output accuracy and adapt the HMI design to successfully situate the AI application in an existing sociotechnical context. This study contributes to IS literature following recent calls for phenomenon-based examination of emerging challenges when extending the scope frontier of AI and provides practical recommendations for developing AI decision-support for complex environments

Improving Fuel Economy via Management of Auxiliary Loads in Fuel-Cell Electric Vehicles

The automotive industry is in a state of flux at the moment. Traditional combustion engine technologies are becoming challenged by newer, more efficient and environmentally friendly propulsion methods. These include bio-fuel, hybrid, and hydrogen fuel-cell technologies. Propulsion alone, however, is not the only area where improvements can be made in vehicle efficiency. Current vehicle research and development focuses heavily on propulsion systems with relatively few resources dedicated to auxiliary systems. These auxiliary systems, however, can have a significant impact on overall vehicle efficiency and fuel economy. The objective of this work is to improve the efficiency of a Fuel Cell Electric Vehicle (FCEV) through intelligent auxiliary system control. The analysis contained herein is applicable to all types of vehicles and may find applications in many vehicle architectures. A survey is made of the various types of alternative fuels and vehicle architectures from conventional gasoline vehicles to hybrids and fuel cells. Trends in auxiliary power systems and previous papers on control of these systems are discussed. The FCEV developed by the University of Waterloo Alternative Fuels Team (UWAFT) is outlined and the design process presented. Its powertrain control strategy is analyzed with a proposal for modifications as well as the addition of an auxiliary control module to meet the aforementioned objectives. Simulations are performed to predict the efficiency and fuel economy gains that can potentially be realized using these proposed techniques. These gains prove to be significant, with an almost 2% improvement realized through intelligent control of the air conditioning compressor, and further gains possible through other auxiliary power reduction techniques

n-Dimensional QoS Framework for Real-Time Service-Oriented Architectures

Service-Orientation has long provided an effective mechanism to integrate heterogeneous systems in a loosely coupled fashion as services. However, with the emergence of Internet of Things (IoT) there is a growing need to facilitate the integration of real-time services executing in non-controlled, non-real-time, environments such as the Cloud. With the need to integrate both cyberphysical systems as hardware-in-the-loop (HIL) components and also with Simulation as a Service (SIMaaS) the execution performance and response-times of the services must be managed. This paper presents a mathematical framework that captures the relationship between the host execution environment and service performance allowing the estimation of Quality of Service (QoS) under dynamic Cloud workloads. A formal mathematical definition is provided and this is evaluated against existing techniques from both the Cloud and Real-Time Service Oriented Architecture (RT-SOA) domains. The proposed approach is evaluated against the existing techniques through simulation and demonstrates a reduction of QoS violation percentage by 22% with respect to response-times as well as reducing the number of Micro-Service (uS) instances with QoS violations by 27%