Cohort analysis of driving cessation and limitation among older adults

Automobiles are central to participation in economic, social, and cultural activities in the United States. The ability to drive as one ages is fundamental to the quality of life among older adults. Driving rates decline significantly with age. Researchers using cross-sectional data have studied the reasons former drivers have stopped driving, but few have followed individuals over time to examine changes in relationships among driving cessation, socio-demographics, and health conditions. We used longitudinal data from a national sample of 20,000 observations from the University of Michigan Health and Retirement Study (HRS) to examine relationships among demographic variables, health conditions, and driving reduction and driving cessation. Longitudinal data allow analysis of generational differences in behavior, a major advantage over cross-sectional data which only allow comparisons of different people at one point in time. We found, like many other studies, that personal decisions to limit and eventually stop driving vary with sex, age, and health conditions. In addition, unlike most previous studies, we also found that those relationships differ by birth cohort with younger cohorts less likely to stop and limit their driving than their older counterparts. The findings indicate an evolution in the association between driving cessation and its causes.

     

隧道-洞口滑坡平行体系受力变形模式与计算方法研究北大核心CSCD

我国目前对隧道-滑坡工程的设计尚无可供参照的行业标准,尤其是滑坡洞口段隧道缺少相应的计算理论。文章首先以平行体系中隧道-洞口滑坡为研究对象,通过归纳总结滑坡地段隧道衬砌的病害特征,构建了相应的工程地质模型;然后将剩余滑坡推力视为导致隧道变形破坏的直接原因,通过荷载传递规律得到作用于隧道结构上的附加荷载,将其与围岩压力叠加推导出了隧道外荷载的计算公式;接着采用弹性地基梁理论,推导出滑坡推力作用下的隧道内力计算方法,从而得到隧道-洞口滑坡的受力变形模式及计算理论;最后通过模型试验对其合理性进行了验证分析,结果表明该方法与实际工程相符,能够为滑坡地段洞口隧道的设计提供参考。     

Decision fusion of a multi-sensing embedded system for occupant safety measures

The need for an embedded system that can fuse incomplete, inconsistent, and imprecise decisions from several sensing systems is a crucial step in achieving an effective decision for occupant safety measures. This paper deals with the decision fusion strategies of a multi-sensing embedded system to achieve significant enhancement in the reliability of occupant safety through the fused decisions. Multi-sensing approaches to determine weight, vision, and crash sensing are developed for occupant detection, classification, position calculation, and crash detection. A rule-based decision fusion algorithm is then developed to fuse the multi-sensing decisions. The developed sensing systems are incorporated into an embedded device. To execute the embedded system, a system interface between the software and hardware is developed using Lab Window/CVI with the C programming language. The experimental results demonstrated that the real time operation of the embedded system validate the effectiveness of the decision fusion algorithm, characterize the safety measures and monitor the decision application. Several events were tested that prove the performance of the embedded system is robust towards occupant safety measures.     

Development of a microscopic activity-based framework for analyzing the potential impacts of transportation control measures on vehicle emissions

The 1990 Clean Air Act Amendments (CAAA) and the Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA) have defined a set of transportation control measures to counter the increase in the vehicle emissions and energy consumption due to increased travel. The value of these TCM strategies is unknown as there is limited data available to measure the travel effects of individual TCM strategies and the models are inadequate in forecasting changes in travel behavior resulting from these strategies. The work described in this paper begins to provide an operational methodology to overcome these difficulties so that the impacts of the policy mandates of both CAAA and ISTEA can be assessed. Although the framework, as currently developed, falls well short of actually forecasting changes in traveler behavior relative to policy options designed to encourage emissions reduction, the approach can be useful in estimating upper bounds of certain policy alternatives in reducing vehicle emissions. Subject to this important limitation, the potential of transportation policy options to alleviate vehicle emissions is examined in a comprehensive activity-based approach. Conclusions are drawn relative to the potential emissions savings that can be expected from efficient trip chaining behavior, ridesharing among household members, as well as from technological advances in vehicle emissions control devices represented by replacing all of the vehicles in the fleet by vehicles conforming to present-day emissions technology.     

Nonlinear pricing of taxi services

This paper examines the effects of nonlinear fare structures in taxi markets using an extended taxi model with an explicit consideration of perceived profitability. The expected profit, defined as the profit per unit time (inclusive of both occupied and vacant taxi times), that a taxi driver expects to receive from picking up a customer in a particular zone or location, has great impact on the taxi driver’s choice of location in the search for customers. The fare structure directly governs the profitability of taxi rides of different distances originating from different locations. With these explicit considerations, the extended model is intended to look into the market effects of adopting a nonlinear fare structure with declining incremental charges. The proposed nonlinear fare structure could help restore a level-playing field for taxi operators whose businesses have been affected by some taxi drivers who resort to practices such as offering fare discounts or accepting requests for discounted fares from passengers for long-haul trips. Analysis of sensitivity of social welfare and profit gain as well as taxi/customer wait/search times is conducted with respect to the parameters in the nonlinear fare structure for the Hong Kong taxi market, and Pareto-improving nonlinear fare amendments are identified that neither disadvantage any customer nor reduce the taxi operators’ profits.     

Estimating spatial interdependence in automobile type choice with survey data

In this article, we show that vehicle type ownership is spatially dependent at both the regional and household-level even after controlling for income and population density. We discuss reasons for the existence of spatial effects in vehicle ownership, and note potential implications for policymakers. Our results point to the importance of spatial relationships in transportation research and highlight the hazards of ignoring their role in affecting transportation outcomes. For example, if vehicle type choice is affected by neighborhood spillovers, agencies that regulate traffic flow and road safety could tailor their choice projections and policy tools to account for such interdependence.     

Connection design for two-floating beam system for minimum hydroelastic response

This paper is concerned with the connection design for a two-floating beam system for minimum hydroelastic response. The frequency domain approach is used for the hydroelastic analysis. The fluid is modelled as an ideal fluid, and the floating beams are modelled by the Euler–Bernoulli beam theory. The boundary element method (BEM) and the finite element method (FEM) are applied to solve the governing equation of the fluid motion and the beam equation of motion, respectively. The study aims to investigate the optimum location and rotational stiffness of the connection for the two-floating beam system with the view to minimize the compliance. The study also investigates the effects of relative beam stiffnesses on the hydroelastic response of the two-floating beam system.     

Modelling the effects of physical–biological interactions and spatial variability in spawning and nursery areas on transport and retention of sardine Sardinops sagax eggs and larvae in the southern Benguela ecosystem

A particle-tracking individual-based model (IBM) coupled with a 3-D hydrodynamic model was used to investigate how spatial variability in spawning and nursery grounds may influence transport and retention of sardine (Sardinops sagax) eggs and larvae in the southern Benguela ecosystem. A temperature-dependent Bělehrádek development model based on laboratory growth data was used to determine the duration of one egg and two larval stages. Successful transport/retention depended on each particle's stage of development rather than its age. Results show that recruitment could occur in two distinct nursery areas on the west and south coasts of South Africa. Three viable recruitment ‘systems’ were identified: two are retention-based (spawned and retained on the west coast (WC–WC) or the south coast (SC–SC)) and one is transport-based (spawned on the south coast and transported to the west coast (SC–WC)). In the WC–WC system, the vertical distribution of eggs influenced retention; at intermediate depths of spawning (25–50 m) eggs avoided both offshore Ekman drift and deep cold water. In the SC–SC system, the area of spawning was important; > 50% of eggs from the eastern Agulhas Bank (EAB) were retained in the south coast nursery grounds, whereas very few eggs were transported there from west of Cape Agulhas. In the SC–WC system, area of spawning was also important; 40% of the eggs spawned on the western Agulhas Bank (WAB) were transported to the west coast nursery ground. Sardine life history strategy could be divided between two main systems: the west coast system (spawning on the WAB and WC, and recruiting to the WC) and the Agulhas Bank system (spawning on the central and eastern Agulhas Bank, and recruiting to the SC).     

Stochastic cell transmission model (SCTM): A stochastic dynamic traffic model for traffic state surveillance and assignment

The paper proposes a first-order macroscopic stochastic dynamic traffic model, namely the stochastic cell transmission model (SCTM), to model traffic flow density on freeway segments with stochastic demand and supply. The SCTM consists of five operational modes corresponding to different congestion levels of the freeway segment. Each mode is formulated as a discrete time bilinear stochastic system. A set of probabilistic conditions is proposed to characterize the probability of occurrence of each mode. The overall effect of the five modes is estimated by the joint traffic density which is derived from the theory of finite mixture distribution. The SCTM captures not only the mean and standard deviation (SD) of density of the traffic flow, but also the propagation of SD over time and space. The SCTM is tested with a hypothetical freeway corridor simulation and an empirical study. The simulation results are compared against the means and SDs of traffic densities obtained from the Monte Carlo Simulation (MCS) of the modified cell transmission model (MCTM). An approximately two-miles freeway segment of Interstate 210 West (I-210W) in Los Ageles, Southern California, is chosen for the empirical study. Traffic data is obtained from the Performance Measurement System (PeMS). The stochastic parameters of the SCTM are calibrated against the flow-density empirical data of I-210W. Both the SCTM and the MCS of the MCTM are tested. A discussion of the computational efficiency and the accuracy issues of the two methods is provided based on the empirical results. Both the numerical simulation results and the empirical results confirm that the SCTM is capable of accurately estimating the means and SDs of the freeway densities as compared to the MCS.