116,782 research outputs found
Vision-Based Lane-Changing Behavior Detection Using Deep Residual Neural Network
Accurate lane localization and lane change detection are crucial in advanced
driver assistance systems and autonomous driving systems for safer and more
efficient trajectory planning. Conventional localization devices such as Global
Positioning System only provide road-level resolution for car navigation, which
is incompetent to assist in lane-level decision making. The state of art
technique for lane localization is to use Light Detection and Ranging sensors
to correct the global localization error and achieve centimeter-level accuracy,
but the real-time implementation and popularization for LiDAR is still limited
by its computational burden and current cost. As a cost-effective alternative,
vision-based lane change detection has been highly regarded for affordable
autonomous vehicles to support lane-level localization. A deep learning-based
computer vision system is developed to detect the lane change behavior using
the images captured by a front-view camera mounted on the vehicle and data from
the inertial measurement unit for highway driving. Testing results on
real-world driving data have shown that the proposed method is robust with
real-time working ability and could achieve around 87% lane change detection
accuracy. Compared to the average human reaction to visual stimuli, the
proposed computer vision system works 9 times faster, which makes it capable of
helping make life-saving decisions in time
The State-of-the-art of Coordinated Ramp Control with Mixed Traffic Conditions
Ramp metering, a traditional traffic control strategy for conventional
vehicles, has been widely deployed around the world since the 1960s. On the
other hand, the last decade has witnessed significant advances in connected and
automated vehicle (CAV) technology and its great potential for improving
safety, mobility and environmental sustainability. Therefore, a large amount of
research has been conducted on cooperative ramp merging for CAVs only. However,
it is expected that the phase of mixed traffic, namely the coexistence of both
human-driven vehicles and CAVs, would last for a long time. Since there is
little research on the system-wide ramp control with mixed traffic conditions,
the paper aims to close this gap by proposing an innovative system architecture
and reviewing the state-of-the-art studies on the key components of the
proposed system. These components include traffic state estimation, ramp
metering, driving behavior modeling, and coordination of CAVs. All reviewed
literature plot an extensive landscape for the proposed system-wide coordinated
ramp control with mixed traffic conditions.Comment: 8 pages, 1 figure, IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE
- ITSC 201
Applying model-driven paradigm: CALIPSOneo experience
Model-Driven Engineering paradigm is being used by the research community in the last years, obtaining suitable results. However, there are few practical experiences in the enterprise field. This paper presents the use of this paradigm in an aeronautical PLM project named CALIPSOneo currently under development in Airbus. In this context, NDT methodology was adapted as methodology in order to be used by the development team. The paper presents this process and the results that we are getting from the project. Besides, some relevant learned lessons from the trenches are concluded.Ministerio de Ciencia e Innovación TIN2010-20057-C03-02Junta de Andalucía TIC-578
SOA-Driven Business-Software Alignment
The alignment of business processes and their supporting application software is a major concern during the initial software design phases. This paper proposes a design approach addressing this problem of business-software alignment. The approach takes an initial business model as a basis in deriving refined models that target a service-oriented software implementation. The approach explicitly identifies a software modeling level at which software modules are represented as services in a technology-platformindependent way. This model-driven service-oriented approach has the following properties: (i) there is a forced alignment (consistency) between business processes and supporting applications; (ii) changes in the business environment can be traced to the application and vice versa, via model relationships; (iii) the software modules modeled as services have a high degree of autonomy; (iv) migration to new technology platforms can be supported through the platform independent software model
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The uses of process modeling : a framework for understanding modeling formalisms
There is wide-spread recognition of the urgent need to improve software processes in order to improve the performance of software organizations. Process models are essential in achieving understanding and visibility of processes and are important for other uses including the analysis of processes for improvement. It has been increasingly difficult to compare and evaluate the variety of process modeling formalisms that have appeared in recent years without a clear understanding of precisely for what they will be used. The contribution of this paper is to provide an understanding and a fairly comprehensive catalog of the applications of process modeling for which formalisms may be used. The primary mechanism for doing this is a guided tour of the literature on process modeling supplemented by recent industrial experience. In the paper, basic definitions concerning processes, process descriptions and process modeling are reviewed and then uses of process modeling are surveyed under the following headings: communication among process participants, construction of new processes, control of processes, process· analysis, and process support by automation. Comments are offered on paradigms for process modeling formalisms and directions for future work to permit evolution of a discipline of process engineering are given
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