Intelligent Ground Vehicle Competition

The Intelligent Ground Vehicle Competition (IGVC) draws teams from various universities to compete in the annual autonomous vehicle challenge at the Oakland University campus. To compete, a vehicle must be fully autonomous and can navigate a course designated by various obstacles and painted white lines. Some design challenges are motor control, navigation, environment sensing and safety. A complex navigation system will utilize several tools including a high-precision differential GPS. The vehicle’s surroundings will be mapped using a combination of Light Detection and Ranging (LiDAR) and computer-vision enabled imaging. To comply with IGVC rules, the vehicle must also follow several safety requirements such as physical and wireless emergency stop, safety lighting, and the ability to assume manual control. By fulfilling these design challenges, the design team is seeking to compete in the 2017 Intelligent Ground Vehicle Competition

Making Transport Safer: V2V-Based Automated Emergency Braking System

An important goal in the field of intelligent transportation systems (ITS) is to provide driving aids aimed at preventing accidents and reducing the number of traffic victims. The commonest traffic accidents in urban areas are due to sudden braking that demands a very fast response on the part of drivers. Attempts to solve this problem have motivated many ITS advances including the detection of the intention of surrounding cars using lasers, radars or cameras. However, this might not be enough to increase safety when there is a danger of collision. Vehicle to vehicle communications are needed to ensure that the other intentions of cars are also available. The article describes the development of a controller to perform an emergency stop via an electro-hydraulic braking system employed on dry asphalt. An original V2V communication scheme based on WiFi cards has been used for broadcasting positioning information to other vehicles. The reliability of the scheme has been theoretically analyzed to estimate its performance when the number of vehicles involved is much higher. This controller has been incorporated into the AUTOPIA program control for automatic cars. The system has been implemented in Citroën C3 Pluriel, and various tests were performed to evaluate its operation

Towards a Reliable and Context-Based System Architecture for Autonomous Vehicles

Full vehicle autonomy excludes a takeover by passengers in case a safety-critical application fails. Therefore, the system responsible for operating the autonomous vehicle has to detect and handle failures autonomously. Moreover, this system has to ensure the safety of the passengers, as well as the safety of other road users at any given time. Especially in the initial phase of autonomous vehicles, building up consumer confidence is essential. Therefore, in this regard, handling all failures by simply performing an emergency stop is not desirable. In this paper, we introduce an approach enabling a dynamic and safe reconfiguration of the autonomous driving system to handle occurring hardware and software failures. Since the requirements concerning safe reconfiguration actions are significantly affected by the current context the car is experiencing, the developed reconfiguration approach is sensitive to context changes. Our approach defines three interconnected layers, which are distinguished by their level of awareness. The top layer, referred to as the context layer, is responsible for observing the context. These context observations, in turn, imply a set of requirements, which constitute the input for the reconfiguration layer. The latter layer is required to determine reconfiguration actions, which are then executed by the architecture layer

A cloud robotics architecture for an emergency management and monitoring service in a smart cityenvironment

Cloud robotics is revolutionizing not only the robotics industry but also the ICT world, giving robots more storage and computing capacity, opening new scenarios that blend the physical to the digital world. In this vision new IT architectures are required to manage robots, retrieve data from them and create services to interact with users. In this paper a possible implementation of a cloud robotics architecture for the interaction between users and UAVs is described. Using the latter as monitoring agents, a service for fighting crime in urban environment is proposed, making one step forward towards the idea of smart cit

Limited Visibility and Uncertainty Aware Motion Planning for Automated Driving

Adverse weather conditions and occlusions in urban environments result in impaired perception. The uncertainties are handled in different modules of an automated vehicle, ranging from sensor level over situation prediction until motion planning. This paper focuses on motion planning given an uncertain environment model with occlusions. We present a method to remain collision free for the worst-case evolution of the given scene. We define criteria that measure the available margins to a collision while considering visibility and interactions, and consequently integrate conditions that apply these criteria into an optimization-based motion planner. We show the generality of our method by validating it in several distinct urban scenarios