Advanced FNN control of mini underwater vehicles

Fuzzy neural networks （FNN） based on Gaussian membership functions can effectively control the motion of underwater vehicles. However, their operating processes and training algorithms are complicated, placing great demands on embedded hardware. This paper presents an advanced FNN with an S membership function matching the motion characteristics of mini underwater vehicles with wings. A leaming algorithm was then developed. Simulation results showed that the modified FNN is a simpler algorithm with faster calculations and improves responsiveness, compared with a Gaussian membership function-based FNN. It is applicable for mini underwater vehicles that don＇t need accurate positioning but must have good maneuverability.     

Fatigue crack growth rates of rotor steel at elevated temperatures

Low fatigue samples were obtained from the outer edges of rotor steel （30CrlMolV） which had operated under different temperatures conditions. Based on this data, the effects of temperature on fatigue crack growth rates were investigated. This paper presents a derivation of the superposition expression of two natural logarithms governing crack growth rates and also discusses the relationship between a material’s constants and temperature. These results can provide experimental and theoretical references for fatigue life design of rotor steel in steam turbines.     

Integrating land use and transport knowledge in strategy-making

There is broad and growing consensus regarding the central place of integrated Land Use and Transport (LUT) strategy development in establishing more efficient and sustainable urban environments. However, empirical evidence shows that such integration is hard to achieve in daily planning practice, due to many institutional barriers and substantive differences. More specifically, the tools developed to support LUT strategy development have very low implementation rates in daily planning practice. This paper introduces the concept of ‘knowledge generation’ as a potentially useful mechanism for closing the gap between support tools and planning practice. Through two specific Dutch planning cases, we analyze the applicability of this concept in supporting integrated LUT strategy development. The paper focuses on the developed strategies, how these differ from current practice, and how knowledge generation supported their development. We argue that socialization produces shared strategies and that effective socialization needs to be supported by efficient mutual exchange between tacit and explicit knowledge. We conclude by discussing the implications of this argument for the wider practice of LUT planning integration.     

A joint flexible econometric model system of household residential location and vehicle fleet composition/usage choices

Modeling the interaction between the built environment and travel behavior is of much interest to transportation planning professionals due to the desire to curb vehicular travel demand through modifications to built environment attributes. However, such models need to take into account self-selection effects in residential location choice, wherein households choose to reside in neighborhoods and built environments that are conducive to their lifestyle preferences and attitudes. This phenomenon, well-recognized in the literature, calls for the specification and estimation of joint models of multi-dimensional land use and travel choice processes. However, the estimation of such model systems that explicitly account for the presence of unobserved factors that jointly impact multiple choice dimensions is extremely complex and computationally intensive. This paper presents a joint GEV-based logit regression model of residential location choice, vehicle count by type choice, and vehicle usage (vehicle miles of travel) using a copula-based framework that facilitates the estimation of joint equations systems with error dependence structures within a simple and flexible closed-form analytic framework. The model system is estimated on a sample derived from the 2000 San Francisco Bay Area Household Travel Survey. Estimation results show that there is significant dependency among the choice dimensions and that self-selection effects cannot be ignored when modeling land use-travel behavior interactions.     

Scrutinizing individuals’ leisure-shopping travel decisions to appraise activity-based models of travel demand

Activity-based models for modeling individuals’ travel demand have come to a new era in addressing individuals’ and households’ travel behavior on a disaggregate level. Quantitative data are mainly used in this domain to enable a realistic representation of individual choices and a true assessment of the impact of different Travel Demand Management measures. However, qualitative approaches in data collection are believed to be able to capture aspects of individuals’ travel behavior that cannot be obtained using quantitative studies, such as detailed decision making process information. Therefore, qualitative methods may deepen the insight into human’s travel behavior from an agent-based perspective. This paper reports on the application of a qualitative semi-structured interview method, namely the Causal Network Elicitation Technique (CNET), for eliciting individuals’ thoughts regarding fun-shopping related travel decisions, i.e. timing, shopping location and transport mode choices. The CNET protocol encourages participants to think aloud about their considerations when making decisions. These different elicited aspects are linked with causal relationships and thus, individuals’ mental representations of the task at hand are recorded. This protocol is tested in the city centre of Hasselt in Belgium, using 26 young adults as respondents. Response data are used to apply the Association Rules, a fairly common technique in machine learning. Results highlight different interrelated contexts, instruments and values considered when planning a trip. These findings can give feedback to current AB models to raise their behavioral realism and to improve modeling accuracy.     

Temporal transferability of updated alternative-specific constants in disaggregate mode choice models

Methods of updating disaggregate discrete choice models have been proposed as a means of obtaining better transferability. However, the temporal transferability of models updated for better spatial transferability has rarely been analysed, and the factors affecting temporal transferability have not been determined. This paper deals with one updating method—the use of disaggregate data to update alternative-specific constants—and investigates the factors affecting the temporal transferability of the updated constants. In the analysis, repeated cross-section data collected in the Chukyo metropolitan area are divided, efficiently generating many application areas. The analysis showed that the factors can depend on regional characteristics and past travel behaviours (inertia), and are anti-symmetric and path-dependent of changes in the level of service.     

Evaluation of an existing bus network using a transit network optimisation model: a case study of the Hiroshima City Bus network

This study evaluates an existing bus network from the perspectives of passengers, operators, and overall system efficiency using the output of a previously developed transportation network optimisation model. This model is formulated as a bi-level optimisation problem with a transit assignment model as the lower problem. The upper problem is also formulated as bi-level optimisation problem to minimise costs for both passengers and operators, making it possible to evaluate the effects of reducing operator cost against passenger cost. A case study based on demand data for Hiroshima City confirms that the current bus network is close to the Pareto front, if the total costs to both passengers and operators are adopted as objective functions. However, the sensitivity analysis with regard to the OD pattern fluctuation indicates that passenger and operator costs in the current network are not always close to the Pareto front. Finally, the results suggests that, regardless of OD pattern fluctuation, reducing operator costs will increase passenger cost and increase inequity in service levels among passengers.     

Catching a ride on the information super-highway: toward an understanding of internet-based carpool formation and use

Fluctuating fuel prices, rising congestion, longer commutes, and related environmental and human health effects have combined to once more draw the interest of governments, commuters, and firms toward the concept of travel demand management (TDM). While TDM is not new, the proliferation of mobile telephony, fixed Internet, and associated applications has created fresh prospects for the implementation of commuter focused TDM strategies. One recent example is Carpool Zone, an on-line carpool-matching tool deployed and managed by the TDM group at Metrolinx, the regional transportation planning agency within Canada’s largest metropolitan region, the Greater Toronto and Hamilton Area. Using data provided by Metrolinx, this paper broadens current thinking on carpool formation and use. The main hypothesis guiding this work is that the carpool formation and use process is sensitive to personal and household characteristics, space, time, travel cost, and workplace TDM policies. Results from a logistic regression analysis suggest that geographical proximity to other users; workplace TDM policies; the scheduling of work; and commuter role preference increase the odds of successfully carpooling. Importantly, findings regarding the positive influence of workplace TDM policies suggest that Internet based TDM tools will likely require critically important investment in human capital at the back-end to ensure program participation.     

基于Simulink的带式浮桥动态仿真

A mathematical model of a ribbon pontoon bridge subjected to moving loads was formulated using the theory of simply supported beams. Two types of moving load models were used, the first a moving-constant-force model and the second a moving-mass model. Using both types of loads, the dynamic behavior of a ribbon pontoon bridge was simulated while subjected to a single moving load and then multiple moving loads. Modeling was done with the Simulink package in MATLAB software. Results indicated that the model is correct. The two types of moving load models made little difference to the response ranges when loads moved on the bridge, but made some difference to the response phases. When loads left, the amplitude of the dynamic responses induced by the moving-constant-force model load were larger than those induced by the moving-mass model. There was a great deal more difference when there were more loads.     

多Agent的船舶电力系统网络重构技术

Reconfigurability of the electrical network in a shipboard power system (SPS) after its failure is central to the restoration of power supply and improves survivability of an SPS. The navigational process creates a sequence of different operating conditions. The priority of some loads differs in changing operating conditions. After analyzing characteristics of typical SPS, a model was developed used a grade III switchboard and an environmental prioritizing agent (EPA) algorithm. This algorithm was chosen as it is logically and physically decentralized as well as multi-agent oriented. The EPA algorithm was used to decide on the dynamic load priority, then it selected the means to best meet the maximum power supply load. The simulation results showed that higher priority loads were the first to be restored. The system satisfied all necessary constraints, demonstrating the effectiveness and validity of the proposed method.