167,045 research outputs found
Environmental impact of combined ITS traffic management strategies
Transport was responsible for 20% of the total greenhouse gas emissions in Europe during 2011 (European Environmental Agency 2013) with road transport being the key contributor. To tackle this, targets have been established in Europe and worldwide to curb transport emissions. This poses a significant challenge on Local Government and transport operators who need to identify a set of effective measures to reduce the environmental impact of road transport and at the same time keep the traffic smooth. Of the road transport pollutants, this paper considers NOx, CO2 and black carbon (BC). A particular focus is put on black carbon, which is formed through incomplete combustion of carboneous materials, as it has a significant impact on the Earth’s climate system. It absorbs solar radiation, influences cloud processes, and alters the melting of snow and ice cover (Bond et al. 2013). BC also causes serious health concerns: black carbon is associated with asthma and other respiratory problems, heart attacks and lung cancer (Sharma 2010; United States Environmental Protection Agency 2012). Since BC emissions are mainly produced during the decelerating and accelerating phases (Zhang et al. 2009), ITS actions able to reduce stop&go phases have the potential to reduce BC emissions. This paper investigates the effectiveness of combined ITS actions in urban context in reducing CO2 and BC emissions and improving traffic conditions
A Hierarchal Planning Framework for AUV Mission Management in a Spatio-Temporal Varying Ocean
The purpose of this paper is to provide a hierarchical dynamic mission
planning framework for a single autonomous underwater vehicle (AUV) to
accomplish task-assign process in a limited time interval while operating in an
uncertain undersea environment, where spatio-temporal variability of the
operating field is taken into account. To this end, a high level reactive
mission planner and a low level motion planning system are constructed. The
high level system is responsible for task priority assignment and guiding the
vehicle toward a target of interest considering on-time termination of the
mission. The lower layer is in charge of generating optimal trajectories based
on sequence of tasks and dynamicity of operating terrain. The mission planner
is able to reactively re-arrange the tasks based on mission/terrain updates
while the low level planner is capable of coping unexpected changes of the
terrain by correcting the old path and re-generating a new trajectory. As a
result, the vehicle is able to undertake the maximum number of tasks with
certain degree of maneuverability having situational awareness of the operating
field. The computational engine of the mentioned framework is based on the
biogeography based optimization (BBO) algorithm that is capable of providing
efficient solutions. To evaluate the performance of the proposed framework,
firstly, a realistic model of undersea environment is provided based on
realistic map data, and then several scenarios, treated as real experiments,
are designed through the simulation study. Additionally, to show the robustness
and reliability of the framework, Monte-Carlo simulation is carried out and
statistical analysis is performed. The results of simulations indicate the
significant potential of the two-level hierarchical mission planning system in
mission success and its applicability for real-time implementation
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Extending TRANSIMS Technology to an Integrated Multilevel Representation
The TRANSIMS system developed at Los Alamos in the USA over the past decade is a world leader in providing an integrated land-use transportation dynamical model for large areas with a million or more inhabitants. TRANSIMS uses standard survey data to create synthetic micropopulations, including family structure, to simulate trip making and emergent traffic dynamics. We propose to extend TRANSIMS by adapting it to a new multi-level representation, allowing dynamics to be algebraically integrated at the micro-, meso- and macro-levels. The new representation builds a lattice hierarchy in a way that integrates non-partitional hierarchies of links and routes based on the usual hierarchy of geographical zones, e.g. neighbourhoods, districts, cities, counties and countries. Applying the representation to a big city starts by defining sets of zones at different levels. At the first level, N, is the street. This can be subdivided to building plots at level N-1, buildings at level N-2, and even rooms at level N-3. At level N+1 are the neighbourhoods, at level N+2 is the set of district zones (each of them containing the different neighbourhoods in the previous level), and at the top level N+3 (in this case), is just one zone, the city itself. If a larger study area is to be considered, we would have a whole set of N+3 zones defining N+4-level areas, and so on, extending to the level of counties, countries or even continents. This paper will explain the fundamentals of TRANSIMS technology and compare it to other systems. We will show how TRANSIMS and the new multi-level representation can be brought together to give new insights into the macro-dynamics of very large road systems such as London, England and even the whole of Europe
Drivers’ Response to In-Vehicle Route Guidance Information Systems: An Experiemnt with a Mock-Up Guidance System.
The paper reports an exploratory study, using an unusual technique to investigate drivers' response to in-vehicle route guidance information systems. Eighteen drivers were recruited, and asked to make a series of three trips in an unfamiliar area. Each driver was given turning advice, via a speech synthesiser, on one of these trips. This advice was based on average traffic conditions for the time of day. Unbeknown to the drivers, the advice was in fact triggered by the experimenter, who was riding as a back-seat passenger. Details were kept of times and routes taken with and without guidance, and with different levels of network familiarity. Records were also kept (using questionnaires and video and audio recording) of planning and route-following strategies.
As expected, both receipt of guidance and even very rudimentary network familiarity resulted in reduced journey times, and routes closer to the guidance recommendations. The study indicated that factors including the directness of possible routes, their perceived complexity, and familiarity all affect route choice, but to different extents for different individuals and under different circumstances. Error was shown to be important in determining the route actually followed when guidance was withheld. The study showed that giving in-vehicle guidance using the mock-up technique described is practicable, and does influence drivers' route-choice and route-following behaviour. A possible future study is outlined, aimed at identifying the determinants of the drivers' level of compliance with advice when they believe that advice is based on real-time traffic information
High speed research system study. Advanced flight deck configuration effects
In mid-1991 NASA contracted with industry to study the high-speed civil transport (HSCT) flight deck challenges and assess the benefits, prior to initiating their High Speed Research Program (HSRP) Phase 2 efforts, then scheduled for FY-93. The results of this nine-month effort are presented, and a number of the most significant findings for the specified advanced concepts are highlighted: (1) a no nose-droop configuration; (2) a far forward cockpit location; and (3) advanced crew monitoring and control of complex systems. The results indicate that the no nose-droop configuration is critically dependent upon the design and development of a safe, reliable, and certifiable Synthetic Vision System (SVS). The droop-nose configuration would cause significant weight, performance, and cost penalties. The far forward cockpit location, with the conventional side-by-side seating provides little economic advantage; however, a configuration with a tandem seating arrangement provides a substantial increase in either additional payload (i.e., passengers) or potential downsizing of the vehicle with resulting increases in performance efficiencies and associated reductions in emissions. Without a droop nose, forward external visibility is negated and takeoff/landing guidance and control must rely on the use of the SVS. The technologies enabling such capabilities, which de facto provides for Category 3 all-weather operations on every flight independent of weather, represent a dramatic benefits multiplier in a 2005 global ATM network: both in terms of enhanced economic viability and environmental acceptability
Towards Autonomous Aviation Operations: What Can We Learn from Other Areas of Automation?
Rapid advances in automation has disrupted and transformed several industries in the past 25 years. Automation has evolved from regulation and control of simple systems like controlling the temperature in a room to the autonomous control of complex systems involving network of systems. The reason for automation varies from industry to industry depending on the complexity and benefits resulting from increased levels of automation. Automation may be needed to either reduce costs or deal with hazardous environment or make real-time decisions without the availability of humans. Space autonomy, Internet, robotic vehicles, intelligent systems, wireless networks and power systems provide successful examples of various levels of automation. NASA is conducting research in autonomy and developing plans to increase the levels of automation in aviation operations. This paper provides a brief review of levels of automation, previous efforts to increase levels of automation in aviation operations and current level of automation in the various tasks involved in aviation operations. It develops a methodology to assess the research and development in modeling, sensing and actuation needed to advance the level of automation and the benefits associated with higher levels of automation. Section II describes provides an overview of automation and previous attempts at automation in aviation. Section III provides the role of automation and lessons learned in Space Autonomy. Section IV describes the success of automation in Intelligent Transportation Systems. Section V provides a comparison between the development of automation in other areas and the needs of aviation. Section VI provides an approach to achieve increased automation in aviation operations based on the progress in other areas. The final paper will provide a detailed analysis of the benefits of increased automation for the Traffic Flow Management (TFM) function in aviation operations
Model Predictive Control Based Trajectory Generation for Autonomous Vehicles - An Architectural Approach
Research in the field of automated driving has created promising results in
the last years. Some research groups have shown perception systems which are
able to capture even complicated urban scenarios in great detail. Yet, what is
often missing are general-purpose path- or trajectory planners which are not
designed for a specific purpose. In this paper we look at path- and trajectory
planning from an architectural point of view and show how model predictive
frameworks can contribute to generalized path- and trajectory generation
approaches for generating safe trajectories even in cases of system failures.Comment: Presented at IEEE Intelligent Vehicles Symposium 2017, Los Angeles,
CA, US
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