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381.
[目的]针对无人艇协同围捕过程中逃跑目标具备智能性,现有无人艇策略难以围捕成功的问题,提出一种基于双层切换策略的多无人艇协同围捕算法。[方法]第1层围捕策略采用改进势点法,以无人艇与势点的总直线距离最小为优化目标,采用匈牙利算法为无人艇动态分配势点,并采用人工势场法实现无人艇的协同避碰;第2层围捕策略利用了阿波罗尼奥斯圆的性质,在两艘无人艇前往逃跑目标的目标点进行拦截,剩余无人艇运动方向保持与逃跑目标相同,以不断缩紧包围区域;为应对逃跑目标不同的逃跑方式,第1层围捕策略和第2层围捕策略可互相转化。[结果]仿真实验表明,该算法相较于顺序分配势点算法和极角分配势点算法,围捕时间更少或持平,证明了该算法的有效性和先进性。[结论]该多无人艇协同双层围捕算法,对具备典型智能性的逃跑目标具有围捕效果。  相似文献   
382.
A fully Lagrangian algorithm for numerical simulation of fluid-elastic structure interaction(FSI) problems is developed based on the Smoothed Particle Hydrodynamics(SPH) method. The developed method corresponds to incompressible fluid flows and elastic structures. Divergence-free(projection based) incompressible SPH(ISPH) is used for the fluid phase, while the equations of motion for structural dynamics are solved using Total Lagrangian SPH(TLSPH) method.The temporal pressure noise can occur at ...  相似文献   
383.
In the US, the rise in motorized vehicle travel has contributed to serious societal, environmental, economic, and public health problems. These problems have increased the interest in encouraging non-motorized modes of travel (walking and bicycling). The current study contributes toward this objective by identifying and evaluating the importance of attributes influencing bicyclists’ route choice preferences. Specifically, the paper examines a comprehensive set of attributes that influence bicycle route choice, including: (1) bicyclists’ characteristics, (2) on-street parking, (3) bicycle facility type and amenities, (4) roadway physical characteristics, (5) roadway functional characteristics, and (6) roadway operational characteristics. The data used in the analysis is drawn from a web-based stated preference survey of Texas bicyclists. The results of the study emphasize the importance of a comprehensive evaluation of both route-related attributes and bicyclists’ demographics in bicycle route choice decisions. The empirical results indicate that travel time (for commuters) and motorized traffic volume are the most important attributes in bicycle route choice. Other route attributes with a high impact include number of stop signs, red light, and cross-streets, speed limits, on-street parking characteristics, and whether there exists a continuous bicycle facility on the route.
Chandra R. Bhat (Corresponding author)Email:

Ipek N. Sener   is currently a Ph.D. candidate in transportation engineering at The University of Texas at Austin. She received her M.S. degrees in Civil Engineering and in Architecture, and her B.S. degree in Civil Engineering from the Middle East Technical University in Ankara, Turkey. Naveen Eluru   is currently a Ph.D. candidate in transportation engineering at The University of Texas at Austin. He received his M.S. degree in Civil Engineering from The University of Texas at Austin, and his Bachelors in Technology Degree from Indian Institute of Technology in Madras, India. Chandra R. Bhat   is a Professor in Transportation at The University of Texas at Austin. He has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE), and the 2008 Wilbur S. Smith Distinguished Transportation Educator Award from the Institute of Transportation Engineers (ITE). He is the immediate past chair of the Transportation Research Board Committee on Transportation Demand Forecasting and the International Association for Travel Behaviour Research.  相似文献   
384.
In this paper, a joint model of vehicle type choice and utilization is formulated and estimated on a data set of vehicles drawn from the 2000 San Francisco Bay Area Travel Survey. The joint discrete–continuous model system formulated in this study explicitly accounts for common unobserved factors that may affect the choice and utilization of a certain vehicle type (i.e., self-selection effects). A new copula-based methodology is adopted to facilitate model estimation without imposing restrictive distribution assumptions on the dependency structures between the errors in the discrete and continuous choice components. The copula-based methodology is found to provide statistically superior goodness-of-fit when compared with previous estimation approaches for joint discrete–continuous model systems. The model system, when applied to simulate the impacts of a doubling in fuel price, shows that individuals are more likely to shift vehicle type choices than vehicle usage patterns.
Chandra R. Bhat (Corresponding author)Email:

Erika Spissu   is currently a Research Fellow at the University of Cagliari (Italy). She received her Ph.D. from the University of Palermo and University of Cagliari (Italy) in Transport techniques and economics. She spent the past 2 years at The University of Texas at Austin as a Research Scholar focusing primarily in activity-based travel behavior modeling, time use analysis, and travel demand forecasting. Abdul Pinjari   is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of South Florida, Tampa. His research interests include time-use and travel-behavior analysis, and activity-based approaches to travel-demand forecasting. He has his Ph.D. from The University of Texas at Austin. Ram M. Pendyala   is a Professor of Transportation Systems in the Department of Civil, Environmental, and Sustainable Engineering at Arizona State University. He teaches and conducts research in travel behavior analysis, travel demand modeling and forecasting, activity-based microsimulation approaches, and time use. He specializes in integrated land use-transport models, transport policy formulation, and public transit planning and design. He is currently the Vice-Chair of the International Association for Travel Behavior Research and is the immediate past chair of the Transportation Research Board Committee on Traveler Behavior and Values. He has his PhD from the University of California at Davis. Chandra R. Bhat   is a Professor in Transportation at The University of Texas at Austin. He has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE), and the 2008 Wilbur S. Smith Distinguished Transportation Educator Award from the Institute of Transportation Engineers (ITE). He is the immediate past chair of the Transportation Research Board Committee on Transportation Demand Forecasting and the International Association for Travel Behaviour Research.  相似文献   
385.
This study presents a unified framework to understand the weekday recreational activity participation time-use of adults, with an emphasis on the time expended in physically active recreation pursuits by location and by time-of-day. Such an analysis is important for a better understanding of how individuals incorporate physical activity into their daily activities on a typical weekday, and can inform the development of effective policy interventions to facilitate physical activity. Furthermore, such a study of participation and time use in recreational activity episodes contributes to activity-based travel demand modeling, since recreational activity participation comprises a substantial share of individuals’ total non-work activity participation. The methodology employed here is the multiple discrete continuous extreme value (MDCEV) model, which provides a unified framework to explicitly and endogenously examine time use by type, location, and timing. The data for the empirical analysis is drawn from the 2000 Bay Area Travel Survey (BATS), supplemented with other secondary sources that provide information on physical environment variables. To our knowledge, this is the first study to jointly address the issues of ‘where’, ‘when’ and ‘how much’ individuals choose to participate in ‘what type of (recreational) activity’.  相似文献   
386.
Agent-based microsimulation models of transportation, land use or other socioeconomic processes require an initial synthetic population derived from census data, conventionally created using the iterative proportional fitting (IPF) procedure. This paper introduces a novel computational method that allows the synthesis of many more attributes and finer attribute categories than previous approaches, both of which are long-standing limitations discussed in the literature. Additionally, a new approach is used to fit household and person zonal attribute distributions simultaneously. This technique was first adopted to address limitations specific to Canadian census data, but could also be useful in U.S. and other applications. The results of each new method are evaluated empirically in terms of goodness-of-fit.  相似文献   
387.
Recent advances in global positioning systems (GPS) technology have resulted in a transition in household travel survey methods to test the use of GPS units to record travel details, followed by the application of an algorithm to both identify trips and impute trip purpose, typically supplemented with some level of respondent confirmation via prompted-recall surveys. As the research community evaluates this new approach to potentially replace the traditional survey-reported collection method, it is important to consider how well the GPS-recorded and algorithm-imputed details capture trip details and whether the traditional survey-reported collection method may be preferred with regards to some types of travel. This paper considers two measures of travel intensity (survey-reported and GPS-recorded) for two trip purposes (work and non-work) as dependent variables in a joint ordered response model. The empirical analysis uses a sample from the full-study of the 2009 Indianapolis regional household travel survey. Individuals in this sample provided diary details about their travel survey day as well as carried wearable GPS units for the same 24-h period. The empirical results provide important insights regarding differences in measures of travel intensities related to the two different data collection modes (diary and GPS). The results suggest that more research is needed in the development of workplace identification algorithms, that GPS should continue to be used alongside rather than in lieu of the traditional diary approach, and that assignment of individuals to the GPS or diary survey approach should consider demographics and other characteristics.  相似文献   
388.
Abstract

This paper deals with the topic of risk management in Public Private Partnership (PPP). The analysis of the related literature reveals that risks must be analyzed and managed on a context-specific approach, and that there is a lack of a comprehensive study on the appropriate risk mitigation strategies for each risk embedded in PPP projects. Focusing on the transport sector, based on the results of a Delphi survey, the paper provides guidelines for both public and private parties in defining a list of significant risks in PPP motorway projects, and identifying for them both the effective allocation and the suitable mitigation strategies. Results of the Delphi survey have been compared with the common practices on risk management applied in eight real motorway PPP projects.  相似文献   
389.
Ad hoc shared ride trip planning (SRTP) utilizes mobile devices, geo-sensors and wireless networks to match on-the-fly individual travel demand with transport supply. It represents one of many alternatives to single occupancy vehicle use. This paper outlines a SRTP approach via a two-phase algorithm based on user preferences in a time-dependent routing. Whereas current algorithms use minimization of travel time as the only optimization criterion in trip planning, in the framework presented here, the user can specify multiple trip preferences including travel time, walking time, number of transfers between cars and trip length. Various scenarios are simulated in the city of Tehran (Iran) to demonstrate how preference settings affect the routes of ad hoc shared journeys.  相似文献   
390.
Application of Optimal Control Theory to Inverse Simulation of Car Handling   总被引:5,自引:0,他引:5  
The application of Optimal Control Theory to time-optimal inverse simulation of car handling was investigated. Time-optimal inverse simulation of car handling involves the calculation of driver actions required to perform specified manoeuvres, in as short a time as possible. Driver actions consist of time-histories of front wheel steer rate and longitudinal force. Optimal time-histories of these quantities were calculated using the Gradient method after formulating the problem as one of optimal control. Simulation results are presented for two different cars performing similar lane-changes. These results show significant differences in necessary driver actions for different cars and demonstrate the suitability of the approach taken.  相似文献   
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