Abstract

In the recent years, more and more modern cars have been equipped with perception capabilities. One of the key applications of such perception systems is the estimation of a risk of collision. This is necessary for both Advanced Driver Assistance Systems and Autonomous Navigation. Most approach for risk estimation propose to detect and track the dynamic objects in the scene. Then the risk is estimated as a Time To Collision (TTC) by projecting the object’s trajectory in the future. In this paper, we propose a new grid-based approach for collision risk prediction, based on the Hybrid-Sampling Bayesian Occupancy Filter framework. The idea is to compute an estimation of the TTC for each cell of the grid, instead of reasoning on objects. This strategy avoids to solve the difficult problem of multi-objects detection and tracking and provides a probabilistic estimation of the risk associated to each TTC value. After promising initial results, we propose in this paper to evaluate the relevance of the method for real on-road applications, by using a real-time implementation of our method in an experimental vehicle. Document type: Part of book or chapter of book

Abstract

Processor simulators are important parts of processor design toolsets in which they are used to verify and evaluate the properties of the designed processors. While simulating architectures with independent function unit pipelines using simulation techniques that avoid the overhead of instruction bit-string interpretation, such as compiled simulation, the simulation of function unit pipelines can become one of the new bottlenecks for simulation speed. This paper evaluates several resource conflict detection models, commonly used in compiler instruction scheduling, in the context of function unit pipeline simulation. The evaluated models include the conventional reservation table based-model, the dynamic collision matrix model, and an finite state automata (FSA) based model. In addition, an improvement to the simulation initialization time by means of lazy initialization of states in the FSA-based approach is proposed. The resulting model is faster to initialize and provides comparable simulation speed to the actively initialized FSA. Document type: Part of book or chapter of book

Abstract

Because of the key characteristics of Unmanned Aerial Vehicles (UAVs), removal of pilot, UAVs will be highly suited for repetitive, dirty, and dangerous operations. A wide range of civil and military applications are being explored in the community (Clapper et al., 2007). As a result, UAVs are given serious considerations in worldwide, making them the next step in evolution of aviation. Whatever missions are chosen for UAVs, their number and use will significantly increase in future. Currently, UAVs do not have convenient access to civil and military operation theatres due to their inability to provide an equivalent level-of-safety comparable to see-and-avoid requirements for manned aircraft. The current procedure requires a certificate of authorization be applied for every mission. Obtaining such an authorization may take more than a month. This lengthy process is not in line with increasing number of UAVs development. Therefore, an autonomous collision sensing, detection, awareness and avoidance system will be a key enabler for the integration of unmanned with manned aircraft in a shared airspace. The main objective of the Collision Avoidance System (CAS) is to allow UAVs to operate safely within non segregated civil and military airspace on a routinely basis. For this purpose, the UAV must be able to identify and be identified by the surrounding traffic. The diversity of UAVs and their missions involve a wide-range of system operating concept. Current unmanned aircraft range in size from small hand launch vehicles to large fixed-wing UAV with a wing span similar to Boeing 737. In addition, some UAV autonomously, semiautonomous or completely guided by ground pilot. Furthermore, unmanned vehicles cruise speed, climb/dive rate, turn rate and operating altitudes are similarly varied. Therefore, many CAS methods were proposed to account for that variation and to ensure that the unmanned aircraft efficiently avoids other cooperative traffic while also avoids fixed and moving obstructions such as terrain, obstacles and no flying zones. Numerous technologies are being explored in the community addressing CAS systems. Much of the research in collision avoidance methods for UAVs had been imparted from the air traffic management, maritime and mobile ground robot research communities. However, aircraft complicates the avoidance problem by added dynamic constraints that must be fulfilled for Document type: Part of book or chapter of book

Abstract

Civil aviation air traffic undergoes many random disturbances. Air traffic controllers watch the real traffic and ensure that it is free from collision hazards in the whole airspace — the ATC sector — under their control. The ATFM service takes care that the flow capacity in each sector, called capacity of the air traffic sector, is not exceeded. In the paper an original method of model estimation of the capacity of the designed ATC sectors is described. In this method an experimentally established statistical relationship between the random variables of control load and the air traffic density is used. The capacity of a sector was found from the joint probability distribution of such a two-dimensional random variable model determined as a quanti le of adequate order. This method was verified in practice by determining the capacity of the designed new ATC sectors in FIR Warsaw. Document type: Book

Abstract

International audience; This chapter describes the emerging robotics application field of intelligent vehicles – motor vehicles that have autonomous functions and capabilities. The chapter is organized as follows:- Section 62.1 provides a motivation for why the development of intelligent vehicles is important, a brief history of the field, and the potential benefits of the technology.- Section 62.2 describes the technologies that enable intelligent vehicles to sense vehicle, environment, and driver state, work with digital maps and satellite navigation, and communicate with intelligent transportation infrastructure.- Section 62.3 describes the challenges and solutions associated with road scene understanding – a key capability for all intelligent vehicles.- Section 62.4 describes advanced driver assistance systems, which use the robotics and sensing technologies described earlier to create new safety and convenience systems for motor vehicles, such as collision avoidance, lane keeping, and parking assistance.- Section 62.5 describes driver monitoring technologies that are being developed to mitigate driver fatigue, inattention, and impairment.- Section 62.6 describes fully autonomous intelligent vehicles systems that have been developed and deployed.- Sections 62.7 and 62.8 conclude the chapter with a discussion of future prospects, and provide references to further reading and additional resources. Document type: Part of book or chapter of book

Abstract

Despite being a basic tool for decision-making about the implementation and operation of enterprises with potential negative impacts on the environment, Environmental Impact Assessments (EIA) still facechallenges to its consolidation as an effective tool for achieving sustainable development. This study seeks to evaluate the EIAs available in the digital platforms of both federal and state agencies, with afocus on their development (based on regulatory laws), as well as to understand the perspectives of the professionals involved in the drafting and assessment of EIAs. A total of 151 EIA were analyzed and 27 questionnaires were applied to professional EIA drafters and evaluators. EIAs display as their main positive features a predominant authorship by multidisciplinary teams, while their main deficiency liesin their impact evaluations (including the valuation, significance and analysis of cumulative and synergistic impacts). Survey participants pointed out as potential improvement areas the phases of design, preparation, evaluation and implementation of EIAs. Document type: Part of book or chapter of book

Abstract

Aircraft collision avoidance maneuvers are important and complex applications. Curved flight exhibits nontrivial continuous behavior. In combination with the control choices during air traffic maneuvers, this yields hybrid systems with challenging interactions of discrete and continuous dynamics. As a case study illustrating the use of a new proof assistant for a logic for nonlinear hybrid systems, we analyze collision freedom of roundabout maneuvers in air traffic control, where appropriate curved flight, good timing, and compatible maneuvering are crucial for guaranteeing safe spatial separation of aircraft throughout their flight. We show that formal verification of hybrid systems can scale to curved flight maneuvers required in aircraft control applications. We introduce a fully flyable variant of the roundabout collision avoidance maneuver and verify safety properties by compositional verification. Document type: Part of book or chapter of book