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31.
Recent advances in agent-based micro-simulation modeling have further highlighted the importance of a thorough full synthetic population procedure for guaranteeing the correct characterization of real-world populations and underlying travel demands. In this regard, we propose an integrated approach including Markov Chain Monte Carlo (MCMC) simulation and profiling-based methods to capture the behavioral complexity and the great heterogeneity of agents of the true population through representative micro-samples. The population synthesis method is capable of building the joint distribution of a given population with its corresponding marginal distributions using either full or partial conditional probabilities or both of them simultaneously. In particular, the estimation of socio-demographic or transport-related variables and the characterization of daily activity-travel patterns are included within the framework. The fully probabilistic structure based on Markov Chains characterizing this framework makes it innovative compared to standard activity-based models. Moreover, data stemming from the 2010 Belgian Household Daily Travel Survey (BELDAM) are used to calibrate the modeling framework. We illustrate that this framework effectively captures the behavioral heterogeneity of travelers. Furthermore, we demonstrate that the proposed framework is adequately adapted to meeting the demand for large-scale micro-simulation scenarios of transportation and urban systems. 相似文献
32.
为适应发展需要,提高服务水平,港口通信网络在具备媒体网关的基础上引进软交换技术已成为一个趋势。介绍了综合接入媒体网关系统的功能及具体应用,媒体网关与软交换联接后对下一代港口通信网络发展的作用。 相似文献
33.
The social dimension of activity–travel behavior has recently received much research attention. This paper aims to make a contribution to this growing literature by investigating individuals’ engagements in joint activities and activity companion choices. Using activity–travel diary data collected in Hong Kong in 2010, this study examines the impact of social network attributes on the decisions between solo and joint activities, and for joint activities, the choices of companions. Chi-square difference tests are used to assess the importance of social network variables in explaining joint activity behavior. We find that the inclusion of social network attributes significantly improves the goodness-of-fit of the model with only socioeconomic variables. Specifically, individuals receiving emotional support and social companionship from family members/relatives are found to more likely undertake joint activities with their family members/relatives; the size of personal social networks is found to be a significant determinant of companion choices for joint activities; and activity companions are found to be significant determinants of travel companions. The findings of this study improve the understanding about activity–travel, especially joint activity–travel decisions. 相似文献
34.
The focus of this paper is to learn the daily activity engagement patterns of travelers using Support Vector Machines (SVMs), a modeling approach that is widely used in Artificial intelligence and Machine Learning. It is postulated that an individual’s choice of activities depends not only on socio-demographic characteristics but also on previous activities of individual on the same day. In the paper, Markov Chain models are used to study the sequential choice of activities. The dependencies among activity type, activity sequence and socio-demographic data are captured by employing hidden Markov models. In order to learn model parameters, we use sequential multinomial logit models (MNL) and multiclass Support Vector Machines (K-SVM) with two different dependency structures. In the first dependency structure, it is assumed that type of activity at time ‘t’ depends on the last previous activity and socio-demographic data, whereas in the second structure we assume that activity selection at time ‘t’ depends on all of the individual’s previous activity types on the same day and socio-demographic characteristics. The models are applied to data drawn from a set of California households and a comparison of the accuracy of estimation of activity types and their sequence in the agenda, indicates the superiority of K-SVM models over MNL. Additionally, we show that accuracy in estimating activity patterns increases using different sets of explanatory variables or tuning parameters of the kernel function in K-SVM. 相似文献
35.
A parameterized consideration set model for airport choice: an application to the San Francisco Bay Area 总被引:1,自引:0,他引:1
Airport choice is an important air travel-related decision in multiple airport regions. This paper proposes the use of a probabilistic choice set multinomial logit (PCMNL) model for airport choice that generalizes the multinomial logit model used in all earlier airport choice studies. The paper discusses the properties of the PCMNL model, and applies it to examine airport choice of business travelers residing in the San Francisco Bay Area. Substantive policy implications of the results are discussed. Overall, the results indicate that it is important to analyze the choice (consideration) set formation of travelers. Failure to recognize consideration effects of air travelers can lead to biased model parameters, misleading evaluation of the effects of policy action, and a diminished data fit. 相似文献
36.
K. M. Saqr M. K. Mansour M. N. Musa 《International Journal of Automotive Technology》2008,9(2):155-160
The potential for thermoelectric power generation (via waste heat recovery onboard automobiles) to displace alternators and/or
provide additional charging to a vehicle battery pack has increased with recent advances in thermoelectric material processing.
In gasoline fueled vehicles (GFVs), about 40% of fuel energy is wasted in exhaust heat, while a smaller amount of energy (30%)
is ejected through the engine coolant. Therefore, exhaust-based thermoelectric generators (ETEG) have been a focus for GFV
applications since the late 1980s. The conversion efficiency of modern thermoelectric materials has increased more than three-fold
in the last two decades; however, disputes as to the thermal design of ETEG systems has kept their overall efficiency at limited
and insufficient values. There are many challenges in the thermal design of ETEG systems, such as increasing the efficiency
of the heat exchangers (hot box and cold plate), maintaining a sufficient temperature difference across the thermoelectric
modules during different operating conditions, and reducing thermal losses through the system as a whole. This paper focuses
on a review of the main aspects of thermal design of ETEG systems through various investigations performed over the past twenty
years. This paper is organized as follows: first, the construction of a typical ETEG is described. The heat balance and efficiency
of ETEG are then discussed. Then, the third section of this paper emphasizes the main objectives and challenges for designing
efficient ETEG systems. Finally, a review of ETEG research activities over the last twenty years is presented to focus on
methods used by the research community to address such challenges. 相似文献
37.
This paper presents a steering control method for lane-following in a vehicle using an image sensor. With each image frame
acquired from the sensor, the steering control method determines target position and direction, and constructs a travel path
from the current position to the target position either as an Arc-path or S-path. The steering angle is calculated from the
travel path thus generated, and the vehicle follows the travel path via motor-control. The method was tested using a vehicle
dubbed as KAV (Korea Autonomous Vehicle) along an expressway (Seoul Inner Beltway) trajectory with a variety of radii (50
m ∼ 300 m) while traveling at a speed of 60 km/h to 80 km/h. Compared with an experienced human driver, the method showed
little much difference in performance in terms of lane-center deviation. The proposed method is currently employed for high
speed autonomous driving as well as for stop and go traffic. 相似文献
38.
In this paper, we take an initial look at the spatial and temporal flexibility in the activity patterns of the so-called “baby-boomer”
cohort (born 1947–1966) in comparison with younger and older adults. Using a unique longitudinal survey carried in Quebec
City from 2002 to 2005, we explore activity patterns and trip rates over a seven-day observation period during the first wave,
and take a first look at some aspects of their evolution over two subsequent waves at about one-year intervals. We model the
propensity to undertake activities within selected conventional non-work classifications such as “shopping” and “leisure”,
and also according to respondents’ own perceptions of the spatial and temporal flexibility of each out-of-home activity that
they had executed. While we cannot strictly separate cohort effects from age-related effects, after controlling for gender
and household structure, we infer that age and related lifestyle effects dominate in explaining these propensities. However,
the boomers were the only age stratum to increase their total out-of-home activity participation over the course of the panel,
an intriguing starting point for the future study of this cohort.
Luis F. Miranda-Moreno has been recently appointed as Assistant Professor in the Department of Civil Engineering and Applied Mechanics at McGill University. His research focuses on travel behaviour, transportation safety and evaluation of sustainable transport strategies. Martin Lee-Gosselin recently retired as Full Professor at the Graduate School of Planning and CRAD, Université Laval, Québec, and is Visiting Professor at Imperial College London. His research interests are transport and telecommunications behaviour, survey methods, energy efficiency and the impacts of transport on the environment and public health. 相似文献
Martin Lee-GosselinEmail: |
Luis F. Miranda-Moreno has been recently appointed as Assistant Professor in the Department of Civil Engineering and Applied Mechanics at McGill University. His research focuses on travel behaviour, transportation safety and evaluation of sustainable transport strategies. Martin Lee-Gosselin recently retired as Full Professor at the Graduate School of Planning and CRAD, Université Laval, Québec, and is Visiting Professor at Imperial College London. His research interests are transport and telecommunications behaviour, survey methods, energy efficiency and the impacts of transport on the environment and public health. 相似文献
39.
Clarke Wilson 《Transportation》2008,35(4):485-499
Daily activity diaries can be recorded as sequences of characters representing events and their contexts as they unfold during
the day. Dynamic programming algorithms as used in bioinformatics have been used by a number of researchers to measure the
similarities and differences between travel patterns on the basis of temporal sequencing of events, activity transition, and
total activity time. The resultant similarity matrices have been shown to be more effective in classifying sequential patterns
than classifications based on alternative similarity indices. The basic algorithms can be amended to include the geographic
coordinates of events by a suitable amendment to the definition of distance. This permits quantitative classification of Hagerstrand-type
activity trajectories on the basis of both activity and spatial similarity. Such a classification can be used to group similar
trajectories and to identify representative trajectories that are analogous to measures of central tendency in univariate
statistics, giving more concrete meaning to the concept of the activity pattern than any other method now available. The paper
illustrates the effect of considering both events and locations in the classification of daily activity patterns using activity
diary data gathered in the town of Reading. The algorithm has been implemented in the Clustal_TXY alignment software package.
相似文献
Clarke WilsonEmail: |
40.
Exploring spatial variety in patterns of activity-travel behaviour: initial results from the Toronto Travel-Activity Panel Survey (TTAPS) 总被引:1,自引:0,他引:1
Studies of urban travel behaviour typically focus on weekday activities and commuting. This is surprising given the rising
contribution of discretionary activities to daily travel that has occurred during the last few decades. Moreover, current
understanding of the relationship between travel behaviour and land use remains incomplete, with little research carried out
to explore spatial properties of activity-travel behaviour during the off-peak and weekend time periods. Weekend behaviours,
for example, influenced by the availability of time and the spatiotemporal distribution of “weekend” destinations, likely
produce spatially and temporally distinct activity-travel patterns. Using data from the first wave of the Toronto Travel-Activity
Panel Survey (TTAPS), this paper examines an area of research that has received little attention; namely, the presence of
spatial variety in activity-travel behaviour. The paper begins by looking at the extent to which individuals engage in spatially
repetitive location choices during the course of a single week. Area-based measures of geographical extent and activity dispersion
are then used to expose differences in weekday-to-weekend and day-to-day activity-travel patterns. Examination of unclassified
activities carried out over a 1 week period reveals a level of spatial repetition that does not materialise across activities
classified by type, travel mode, and planning strategy. Despite the inherent spatial flexibility offered by the personal automobile,
spatial repetition is also found to be surprisingly similar across travel modes. The results also indicate weekday-to-weekend,
and day-to-day fluctuations in spatial properties of individual activity-travel behaviour. These findings challenge the utility
of the short-run survey as an instrument for capturing archetypal patterns of spatial behaviour. In addition, the presence
of a weekday-to-weekend differential in spatial behaviour suggests that policies targeting weekday travel reduction could
have little impact on travel associated with weekend activities.
相似文献
Tarmo K. RemmelEmail: |