Income-contingent user preferences in policy evaluation: application and discussion based on multi-agent transport simulations

Standard economic policy evaluation allows the realization of projects if the aggregated economic benefit outweighs their costs. The use of one single aggregated welfare measure for evaluating and ranking projects has often been criticized for many reasons. A major issue is that differentiated effects on individuals or subgroups of the population are not taken into consideration. This leads to the need for transport planning tools that provide additional information for politicians and decision makers. The microscopic multi-agent simulation approach presented in this paper is capable of helping to design better solutions in such situations. In particular, it is shown that the inclusion of individual income in utility calculations allows a better understanding of problems linked to public acceptance. First, individual income-contingent utility functions are estimated based on survey data in order to describe human mobility behavior. Subsequently, using the MATSim framework, the implementation is tested in a test scenario. Furthermore, and going beyond Franklin (2006), it is shown that the approach works in a large-scale real world example. Based on a hypothetical speed increase of public transit, effects on the welfare distribution of the population are discussed. It is shown that the identification of winners and losers seems to be quite robust. However, results indicate that a conversion or aggregation of individual utility changes for welfare analysis is highly dependent on the functional form of the utility functions as well as on the choice of the aggregation procedure.     

A random utility maximization (RUM) based dynamic activity scheduling model: Application in weekend activity scheduling

The paper presents a modeling framework for dynamic activity scheduling. The modeling framework considers random utility maximization (RUM) assumption for its components in order to capture the joint activity type, location and continuous time expenditure choice tradeoffs over the course of the day. The dynamics of activity scheduling process are modeled by considering the history of activity participation as well as changes in time budget availability over the day. For empirical application, the model is estimated for weekend activity scheduling using a dataset (CHASE) collected in Toronto in 2002–2003. The data set classifies activities into nine general categories. For the empirical model of a 24-h weekend activity scheduling, only activity type and time expenditure choices are considered. The estimated empirical model captures many behavioral details and gives a high degree of fit to the observed weekend scheduling patterns. Some examples of such behavioral details are the effects of time of the day on activity type choice for scheduling and on the corresponding time expenditure; the effects of travel time requirements on activity type choice for scheduling and on the corresponding time expenditure, etc. Among many other findings, the empirical model reveals that on the weekend the utility of scheduling Recreational activities for later in the day and over a longer duration of time is high. It also reveals that on the weekend, Social activity scheduling is not affected by travel time requirements, but longer travel time requirements typically lead to longer-duration social activities.     

Analyzing the time frame for the transition from leisure-cyclist to commuter-cyclist

A recent survey reported that many commuter-cyclists had enjoyed leisure bicycling on a regular basis prior to becoming a commuter-cyclist. While bicycling for leisure, it is assumed that they considered various factors that led them to consider becoming commuter-cyclists. This study began with the question of how long it would take for a leisure-cyclist to become a commuter-cyclist, and it focused on the time that elapsed between leisure-cyclists transitioning to commuter-cycling. In order to analyze the time frame, it was hypothesized that the probability that a leisure-cyclist would become a commuter-cyclist at a certain time would be conditional on the duration that elapsed from the onset of leisure cycling till that time, which represents the “snowballing” or “inertial” dynamics of duration. A robust methodology, which is known as the “hazard model,” was adopted to accommodate such characteristics of a time period. In addition, various external covariates such as individual-specific characteristics, variables associated with the current or previous commuting mode, supply variables regarding bicycle facilities, and individual latent propensities were adopted to account for the duration of changes that would be generally applicable. As a result, many useful results were derived that could be used in fomenting policies to promote cycling to work. It was found that government should invest in establishing segregated lanes for leisure- and commuter-cyclists. It also turned out that a long distance to work hinders a leisure-cyclist from progressing to commuter-cycling. According to the results, young white-collar workers who live in high-rise apartments and enjoy intensive leisure-cycling in groups, are a good target toward whom promotions for commuter-cycling should be focused. However, an unfortunate development was that, when compared with car-commuters, it was found that transit-commuters are more likely to become commuter-cyclists.     

Actively translating a rear diffuser device for the aerodynamic drag reduction of a passenger car

This research aims to develop an actively translating rear diffuser device to reduce the aerodynamic drag experienced by passenger cars. One of the features of the device is that it is ordinarily hidden under the rear bumper but slips out backward only under high-speed driving conditions. In this study, a movable arc-shaped semi-diffuser device, round in form, is designed to maintain the streamlined automobile??s rear underbody configuration. The device is installed in the rear bumper section of a passenger car. Seven types of rear diffuser devices whose positions and protrusive lengths and widths are different (with the basic shape being identical) were installed, and Computational Fluid Dynamics (CFD) analyses were performed under moving ground and rotating wheel conditions. The main purpose of this study is to explain the aerodynamic drag reduction mechanism of a passenger car cruising at high speed via an actively translating rear diffuser device. The base pressure of the passenger car is increased by deploying the rear diffuser device, which then prevents the low-pressure air coming through the underbody from directly soaring up to the rear surface of the trunk. At the same time, the device generates a diffusing process that lowers the velocity but raises the pressure of the underbody flow, bringing about aerodynamic drag reduction. Finally, the automobile??s aerodynamic drag is reduced by an average of more than 4%, which helps to improve the constant speed fuel efficiency by approximately 2% at a range of driving speeds exceeding 70 km/h.     

A novel adaptive algorithm with an IIR filter and a variable step size for active noise control in a short duct

The intake system in an automotive engine has a short duct compared with that of the exhaust system. The filtered-x LMS (FX-LMS) algorithm has been applied to the active noise control (ANC) system in a short acoustic duct. This algorithm design is based on the FIR (finite impulse response) filter; however, it has a slow convergence issue due to a large number of zero coefficients. To improve the convergence performance, the step size of the LMS algorithm was modified from fixed to variable. However, this algorithm is still not suitable for the ANC system of a short acoustic duct because the reference signal is affected by the backward acoustic wave propagated from a secondary source. Therefore, the recursive filtered-u LMS algorithm (FU-LMS) based on the infinite impulse response (IIR) is developed to consider backward acoustic propagation. Generally, this algorithm has a stability problem. The stability issue was improved using an error-smoothing filter. In this paper, the recursive LMS algorithm with a variable step size and smoothing error filter is designed. This recursive LMS algorithm, the FU-VSSLMS algorithm, uses an IIR filter. With fast convergence and good stability, this algorithm is suitable for the ANC system in a short acoustic duct, such as the intake system of an automotive engine. This algorithm is applied to the ANC system of a short acoustic duct. The disturbance signals used as primary noise source are a sinusoidal signal embedded in white noise and the chirp signal, which has a variable instantaneous frequency. The test results demonstrate that the FU-VSSLMS algorithm has a superior convergence performance when compared with the FX-LMS and FX-LMS algorithms. The algorithm can be successfully applied to the ANC system in a short duct, such as the intake duct.     

Reliability of Nanofluid Concentration on the Heat Transfer Augmentation in Engine Radiator

Nanofluids, the fluid suspensions of nanomaterial, became a promising fluid that is invoked when heat transfer increase is required. Using of nanofluids as a coolant in the engine radiators is a crucial topic for the thermal engines manufactrers due to the expected enhancement in the cooling process. In this study, Two nanofluids (Al₂O₃/water and CuO/water) flowing in a flat tube of radiator are investigated numerically to evaluate thermal and flow performance. The resizing process for the radiator is performed by using nanofluid instead of water flow. A significant reduction in the radiator volume is achieved due to marked improvement in the heat transfer performance while, the required pumping power after this reduction in the volume is increased over that needed for base fluid. The normalized heat transfer (heat transfer to the pumping power) is found to be a function of both Reynolds number and nanofluid concentration ratio while the ratio of the normalized heat transfer is found to be dependent only on the nanofluid concentration ratio. These dependencies are formulated as general correlations.