A system dynamics approach to land use/transportation system performance modeling Part I: Methodology

This paper presents a system dynamics approach to simultaneous land use/transportation system performance modeling. A model is designed based on the causality functions and feedback loop structure between a large number of physical, socioeconomic, and policy variables. The model consists of 7 sub‐models: population, migration of population, household, job growth‐employment‐land availability, housing development, travel demand, and traffic congestion level. The model is formulated in DYNAMO simulation language, and tested on a data set from Montgomery County, MD. In Part I: Methodology, the overall approach and the structure of the model system is discussed and the causal‐loop diagrams and major equations are presented. In Part II: Application, the model is calibrated and tested with data from Montgomery County, MD. Least square method and overall system behavior are used to estimate the model parameters. The model is fitted with the 1970–80 data and validated with the 1980–1990 data. Robustness and sensitivities with respect to input parameters such as birth rate or regional economy growth are analyzed. The model performance as a policy analysis tool is examined by predicting the year by year impacts of highway capacity expansion on land use and transportation system performance. While this is a first attempt in using dynamic system simulation modeling in simultaneous treatment of land use and transportation system interactions, and model development and application are limited due to data availability, the results indicate that the proposed method is a promising approach in dealing with complex urban land use/transportation modeling.     

Nonlinear Robust Control of Torque Converter Clutch Slip System for Passenger Vehicles Using Advanced Torque Estimation Algorithms

In this paper, a torque-estimation-based robust controller for passenger car torque converter clutch slip system is presented. The proposed robust controller uses only the measurements available from inexpensive sensors that are installed in current passenger vehicles for torque estimation and feedback control. A conventional full state observer along with a neural-network-based open-loop hydraulic actuator observer is designed to estimate the unknown driving load, and a neural-network-based turbine torque estimator considering the temperature of oil circulating the torque converter is developed for improved turbine torque estimation accuracy. The stability of the internal dynamics is also investigated, and the performance and robustness of the robust controller is validated by simulation studies.     

Transforaminal lumbar interbody fusion for traumatic lumbar spondylolisthesis

To evaluate the clinical outcome, effectiveness and safety of the surgical management of traumatic lumbar spondylolisthesis with transforaminal lumbar interbody fusion (TLIF) with short segmental instrumentation fixation. A retrospective review of a consecutive series of 24 patients with traumatic lumbar spondylolisthesis treated with TLIF procedure was carried out. Intraoperative spinal cord monitoring was used to confirm the peripheral neural function intact during the reduction of the spondylolisthesis. Preoperative clinical and radiographic evaluation of all cases were originally collected prospectively. Data regarding blood loss, operative time, duration of hospital stay, radiographic fusion, instrumentation failure and clinical result were collected and observed at regular follow-up periods. All patients were engaged in high-energy accidents in the lower back and 16 patients had concomitant injuries. The mean operative time was 124 min, mean blood loss was 350 mL, and mean hospital stay was 6.5 days. There were no complications such as incision infection, cerebrospinal fluide (CSF) leakage and nerve root injury and so on. All patients demonstrated a solid lumbar interbody fusion within 4 months, and no evidence of spondylolisthesis correction loss, instrumentation failure and loosing. They all were completely asymptomatic, with normal neurologic findings, and had resumed their previous level of physical activities on the final follow-up. Meticulous clinical examination and careful imaging assessment could assist an early diagonosis in cases of traumatic lumbar spondylolisthesis. Performing open reduction and the TLIF procedure as soon as possible could restore segmental stability and painless function. The TLIF procedure was a safe, effective technique to treat traumatic lumbar spondylolisthesis.     

Feasibility study for the application of air inflated membrane structure in China National Stadium

China National Stadium, also known as “Bird’s Nest”, is the main stadium of the 29th Olympic Games in Beijing in 2008, which has successfully held not only the Opening and the Closing ceremonies but also the track and field events. A new problem of rain preventing is brought out to improve the utilization of the Bird’s Nest after the Olympic Games. The scheme of installing an air inflated membrane at the opening of the steel structure is proposed in this paper to solve the rainproof problem of the Bird’s Nest. The form-finding and mechanical analyses of the air inflated membrane are carried out. Comparison between the mechanical performance and dynamical character before and after installing the air inflated membrane structure is given. To verify the analysis results, based on the practical structure of the Bird’s Nest, a test of a 1:20 model membrane is worked out.     

Face recognition via adaptive image combination

Dimension reduction and manifold learning are the two most popular feature extraction methods. The two methods focus on spatial locality as a guiding principle to find a low-dimensional basis for describing high-dimensional data, but no bases or features are more spatially localized than the original image pixels. So, adaptive image combination is presented to represent a class by a combined sample. The combined sample is a linear combination of original samples in the same class. Adaptive image combination (AIC) find the best combination coefficients by minimizing the intrapersonal distance and maximizing the interpersonal distance. Experimental results show that AIC is effective.     

Effects of task complexity and time pressure on activity-travel choices: heteroscedastic logit model and activity-travel simulator experiment

This paper derives, estimates and applies a discrete choice model of activity-travel behaviour that accommodates potential effects of task complexity and time pressure on decision-making. To the best of our knowledge, this is the first time that both factors (task complexity and time pressure) are jointly captured in a discrete choice model. More specifically, our heteroscedastic logit model captures potential impacts of task complexity and time pressure through the scale of the utility of activity-travel options. We collect data using a novel activity-travel simulator experiment that has been specifically designed with the aim of testing our model. Results are in line with expectations, in that higher levels of task complexity and time pressure are found to result in a smaller scale of utility. In other words, higher levels of task complexity and time pressure lead to more random choice behaviour and as a consequence to less pronounced differences in choice probabilities between alternatives. An empirical illustration suggests that choice probability-differences between models that do and those that do not capture these effects, can be very substantial; this in turn suggests that failing to capture the effects of task complexity and time pressure in discrete choice models of activity travel decision-making might lead to serious bias in forecasts of the effects of transport policies.     

The digital revolution and worthwhile use of travel time: implications for appraisal and forecasting

Savings in travel time and more specifically their monetary value typically constitute the main benefit to justify major investment in transport schemes. However, worthwhile use of travel time is an increasingly prominent phenomenon of the digital age. Accordingly, questions are increasingly being asked regarding whether values of time used by countries around the world based on their appraisal approaches are too high. This paper offers the most comprehensive examination of our theoretical and empirical understandings of international appraisal approaches and how they account for worthwhile use of travel time. It combines the economics perspective with wider social science insight and reaches the conclusion that past revolutions in transport that have made longer and quicker journeys possible are now joined by a digital revolution that is reducing the disutility of travel time. This revolution offers potential economic benefit that comes at a fraction of the cost of major investments in transport that are predicated on saving travel time. The paper highlights the challenges faced in both current and indeed potential alternative future appraisal approaches. Such challenges are rooted in the difficulty of measuring time use and productivity with sufficient accuracy and over time to credibly account for how travel time factors into the economic outcomes from social and working practices in the knowledge economy. There is a need for further research to: establish how improvements in the opportunities for and the quality of worthwhile use of travel time impact on the valuation of travel time savings for non-business travel; improve our understanding of how productive use of time impacts on the valuation of time savings for business travellers; and estimate how these factors have impacted on the demand for different modes of travel.