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1.
The need of accurate forecasts of air passenger numbers to assist managerial decision making for both short and long terms is well recognized and a central problem on both short and long term forecasting is how to handle future trend. The aim of this paper is to develop a demand trend change early warning forecast model (EWFM) for the city of São Paulo multi-airport system (SPMARs). For SPMARs the EWFM is based on the combination of leading indicators and alarms against possible occurrence of changes on trend component of the monthly number of domestic air passengers. A topdown induction procedure is employed to identify leading indicators to provide an interpretable prediction procedure to support the development of scenarios for future demand trend. Results show that changes on such demand trend are mostly associated to changes on the economic activity and six different scenarios were built combining the identified leading indicators. The EWFM was employed to assist managerial decision making for both short and long terms in order to evaluate different alternatives to prevent congestion delay occurrences and to support infrastructure planning.  相似文献   

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Over one million workers commute daily to São Paulo City center, using different modes of transportation. The São Paulo subway network reaches 74.2 km of length and is involved in around 20% of the commuting trips by public transportation, enhancing mobility and productivity of workers. This paper uses an integrated framework to assess the higher-order economic impacts of the existing underground metro infrastructure. We consider links between mobility, accessibility and labor productivity in the context of a detailed metropolitan system embedded in the national economy. Simulation results from a spatial computable general equilibrium model integrated to a transportation model suggest positive economic impacts that go beyond the city limits. While 32% of the impacts accrue to the city of São Paulo, the remaining 68% benefit other municipalities in the metropolitan area (11%), in the State of São Paulo (12.0%) and in the rest of the country (45%).  相似文献   

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This study analyzes the annual vacation destination choices and related time allocation patterns of American households. More specifically, an annual vacation destination choice and time allocation model is formulated to simultaneously predict the different vacation destinations that a household visits in a year, and the time (no. of days) it allocates to each of the visited destinations. The model takes the form of a multiple discrete–continuous extreme value (MDCEV) structure. Further, a variant of the MDCEV model is proposed to reduce the prediction of unrealistically small amounts of vacation time allocation to the chosen destinations. To do so, the continuously non-linear utility functional form in the MDCEV framework is replaced with a combination of a linear and non-linear form. The empirical analysis was performed using the 1995 American Travel Survey data, with the United States divided into 210 alternative destinations. The model estimation results provide several insights into the determinants of households’ vacation destination choice and time allocation patterns. Results suggest that travel times and travel costs to the destinations, and lodging costs, leisure activity opportunities (measured by employment in the leisure industry), length of coastline, and weather conditions at the destinations influence households’ destination choices for vacations. The annual vacation destination choice model developed in this study can be incorporated into a larger national travel modeling framework for predicting the national-level, origin–destination flows for vacation travel.  相似文献   

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Recent work on risky choice modelling has sought to address the shortcomings of expected utility theory (EUT) by using non-expected utility theoretic (non-EUT) approaches. However, to date these approaches have been merely tested on stated choice data which is flexible and cheap. In this study, we empirically investigate the feasibility and validity of non-EUT approaches in a revealed preference (RP) context in which travel time distribution is extracted from observed historical travel time data, and subsequently present systematic comparisons between EUT, weighted utility theory, rank-dependent expected utility theory, and prospect theory (PT). The empirical evidence indicates that each non-EUT model has important behavioural insights to offer, moreover, EUT as well as non-EUT models can be applied to the RP context. However, the EUT and non-EUT model fits are generally similar with only PT providing a marginally improved model fit over EUT. The key findings presented in this study reinforce the importance of exploring non-EUT models within a revealed preference context before they can be applied reliably to modelling risky choices in the real world.  相似文献   

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In many past studies dealing with traffic phenomena in merging or weaving sections, only the influence of through traffic on the behavior of a merging car is considered in the analysis. It is, however, often seen that a through car, which runs on the most outside lane, takes a cooperative motion for the merging car called “giving way” by moving to the adjacent lane. That is, both the merging car and the through car affect one another. Because their influence is not independent from one another, it should be jointly treated in the analysis as “interaction”. This behavior is typical in merging sections, and is a dominant factor forming the traffic phenomena in a section of this type. This study develops a game theoretical model to describe the traffic behavior of a pair of merging and through cars, while explicitly considering the interaction between them. Both the merging and through cars attempt to take the best actions for themselves by forecasting the other’s action, respectively. Such a behavior is modeled as a two-person non-zero-sum non-cooperative game. Through a case study with data analysis of videotaped observation, the proposed model can be used to obtain an understanding of traffic behavior at on-ramp merging sections. ©  相似文献   

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The production and use of renewable fuels in the transport sector are rapidly increasing. Renewable fuel standard (RFS) is a strong regulatory component and quantitative policy expected to have a significant market impact. In Korea, RFS implementation was agreed upon in July 2013 and will be enforced beginning in July 2015. Drivers’ acceptance is the most important consideration for RFS introduction and sustainable implementation. This study analyzed Korean customer preferences for RFS and quantified their acceptance level according to policy design. A choice experiment was analyzed with a mixed logit model to reflect the heterogeneity of respondents’ preferences. Respondents were relatively sensitive to the price increase, while other attributes had little effect on acceptance of RFS. Differences between the influences of attributes on drivers’ acceptance should be considered when designing RFS implementation. Furthermore, it is recommended that the price of transportation fuels should be limited to an increase between KRW 10 and 20/liter (USD 8.879 × 10−3 and 1.776 × 10−2/liter) to ensure high acceptance level, secure a budget for infrastructure, and achieve substantial environmental improvement.  相似文献   

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This paper proposes a new econometric formulation and an associated estimation method for a finite discrete mixture of normals (FDMN) version of the multiple discrete–continuous probit (MDCP) model. To our knowledge, this is the first such formulation and application of an MDCP model in the econometric literature. Using the New Zealand Domestic Travel Survey data set, the model is applied to analyze individual-level decisions regarding recreational destination locations and the number of trips to each destination. The results provide insights into the demographic and other factors that influence individuals’ preferences for different destinations, and show that the FDMN MDCP model is able to identify different segments of the sample, each one of them with different effects of the exogenous variables on destination choice.  相似文献   

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This study estimates a random parameter (mixed) logit model for active transportation (walk and bicycle) choices for work trips in the New York City (using 2010–2011 Regional Household Travel Survey Data). We explored the effects of traffic safety, walk–bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk–bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the local authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Further, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists, will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The model would be an essential tool to estimate the impact of improving traffic safety and walk–bike infrastructure which will assist in investment decision making.  相似文献   

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This paper pursues three goals: (1) determining the relative importance of built environment barriers limiting walkability, (2) analyzing the existence of an asymmetry in the way people evaluate positive and negative built environment characteristics, and (3) identifying solutions to tackle the main barriers and quantify their impact in walkability. A best–worst scaling survey was developed to compare the importance of eight different attributes of the built environment regarding walkability. Model results show an asymmetry negative–positive in the judgment and choice of built environment characteristics that promote and impede walkability. The most important barriers, obtained from worst responses, are connectivity, topography, sidewalk surface and absence of policemen. Walkability scores were computed for different neighbourhoods and different policy scenarios were forecasted. Simulation results from the worst responses indicate that improvements in sidewalk quality, along with an increase in the number of police officers, lead to an 85% increase in the walkability score for the lower income neighbourhoods.

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Millennials, defined in this study as those born between 1979 and 2000, became the largest population segment in the United States in 2015. Compared to recent previous generations, they have been found to travel less, own fewer cars, have lower driver’s licensure rates, and use alternative modes more. But to what extent will these differences in behaviour persist as millennials move through various phases of the lifecycle? To address this question, this paper presents the results of a longitudinal analysis of the 2003–2013 American Time Use Survey data series. In early adulthood, younger millennials (born 1988–1994) are found to spend significantly more time in-home than older millennials (born 1979–1985), which indicates that there are substantial differences in activity-time use patterns across generations in early adulthood. Older millennials are, however, showing activity-time use patterns similar to their prior generation counterparts as they age, although some differences – particularly in time spent as a car driver – persist. Millennials appear to exhibit a lag in adopting the activity patterns of predecessor generations due to delayed lifecycle milestones (e.g. completing their education, getting jobs, marrying, and having children) and lingering effects of the economic recession, suggesting that travel demand will resume growth in the future.  相似文献   

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We investigate a utility-based approach for driver car-following behavioral modeling while analyzing different aspects of the model characteristics especially in terms of capturing different fundamental diagram regions and safety proxy indices. The adopted model came from an elementary thought where drivers associate subjective utilities for accelerations (i.e. gain in travel times) and subjective dis-utilities for decelerations (i.e. loss in travel time) with a perceived probability of being involved in rear-end collision crashes. Following the testing of the model general structure, the authors translate the corresponding behavioral psychology theory – prospect theory – into an efficient microscopic traffic modeling with more elaborate stochastic characteristics considered in a risk-taking environment.After model formulation, we explore different model disaggregate and aggregate characteristics making sure that fidelity is kept in terms of equilibrium properties. Significant effort is then dedicated to calibrating and validating the model using microscopic trajectory data. A modified genetic algorithm is adopted for this purpose while focusing on capturing inter-driver heterogeneity for each of the parameters. Using the calibration exercise as a starting point, simulation sensitivity analysis is performed to reproduce different fundamental diagram regions and to explore rear-end collisions related properties. In terms of fundamental diagram regions, the model in hand is able to capture traffic breakdowns and different instabilities in the congested region represented by flow-density data points scattering. In terms of incident related measures, the effect of heterogeneity in both psychological factors and execution/perception errors on the accidents number and their distribution is studied. Through sensitivity analysis, correlations between the crash-penalty, the negative coefficient associated with losses in speed, the positive coefficient associated with gains in speed, the driver’s uncertainty, the anticipation time and the reaction time are retrieved. The formulated model offers a better understanding of driving behavior, particularly under extreme/incident conditions.  相似文献   

14.
In this paper, we used the 10-wave Puget Sound Panel Dataset to investigate the response lag of a significant change in discretionary time use. In particular, we want to quantify the relative magnitude of the following factors: the built environment, family and social obligations, temporal constraints, or a psychological delay factor (people delay a behavioral change until the next life shock). To answer this question, we developed a survival model to treat (1) left-censoring, (2) partial observation, and (3) multi-type exits. The results suggest that family and social obligations, as well as temporal constraints, appear to play a more important role than the built environment. Support for the psychological delay factor is not evident. We also found that the probability of having a significant change in discretionary time use is negatively related to time progression, supporting the human adaptivity hypothesis.
Jason ChenEmail:

Cynthia Chen   is an assistant professor of Civil Engineering at the City College of New York. Her recent research interests have been in travel behavior dynamics and residential search and location process. Jason Chen   is a Ph.D. candidate in the department of civil engineering at the City University of New York. His research interests include travel behavior analysis, travel demand modeling, and residential location analysis.  相似文献   

15.
Guo  Yuntao  Peeta  Srinivas  Agrawal  Shubham  Benedyk  Irina 《Transportation》2022,49(2):395-444
Transportation - This study aims to understand the impacts of Pokémon GO, a popular location-based augmented reality (AR) mobile gaming app, on route and mode choices. Pokémon GO...  相似文献   

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Travel planning by employers promoting more sustainable travel has delivered less car dependent behaviour for the commute in many places. Area-wide or precinct travel plans are less common but, where they exist, attempt to provide a more holistic approach through capturing synergies between employers and employees throughout a precinct. Area-based travel planning aimed at influencing employers, employees and residents are new, especially in relation to creating synergies for a single precinct that has more of an origin focus with participants travelling to diverse destinations. This paper examines various strategies that have been employed in order to achieve greener travel and to provide a self-sustaining travel planning environment. The aim of this paper is to assess the community awareness, interest and involvement with a number of green initiatives and to understand how sustainable travel planning has been absorbed by residents within a new regional centre in New South Wales, Australia. The analysis of a resident survey undertaken in 2011 distinguishes between the community awareness and their propensity to take part in each of the greener travel initiatives. The results show that a generic approach is likely to be less effective than segmenting the market so as to more directly target likely participants. Attitudes to greener travel are also highly significant and working to change them should also affect potential take up of sustainable travel initiatives. The conclusions inform the development of successful precinct based travel demand strategies both in Australia and beyond.  相似文献   

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