Estimating a model of dynamic activity generation based on one-day observations: Method and results

In this paper we develop and explore an approach to estimate dynamic models of activity generation on one-day travel-diary data. Dynamic models predict multi-day activity patterns of individuals taking into account dynamic needs as well as day-varying preferences and time-budgets. We formulate an ordered-logit model of dynamic activity-agenda-formation decisions and show how one-day observation probabilities can be derived from the model as a function of the model’s parameters and, with that, how parameters can be estimated using standard loglikelihood estimation. A scale parameter cannot be identified because information on within-person variability is lacking in one-day data. An application of the method to data from a national travel survey illustrates the method. A test on simulated data indicates that, given a pre-set scale, the parameters can be identified and that estimates are robust for a source of heterogeneity not captured in the model. This result indicates that dynamic activity-based models of the kind considered here can be estimated from data that are less costly to collect and that support the large sample sizes typically required for travel-demand modeling. We conclude therefore that the proposed approach opens up a way to develop large-scale dynamic activity-based models of travel demand.     

基于动态控制的船舶制造成本反馈系统

成本失控是制约船舶企业竞争力的关键因素.为实现成本的动态控制,要求成本反馈系统能够及时、经济地提供准确的产品成本信息.为适应船舶制造成本反馈的特殊需求,对作业成本法进行了三点改进:统一了直接成本和间接成本处理方式、以广义工作中心进行成本归集和分配、合并了成本动因.算例表明改进的作业成本法计算出的产品成本准确性介于传统的成本核算方法和作业成本法之间,且贴近作业成本法.     

基于ACE的ECDIS网络接口设计与实现

电子海图显示与信息系统（ECDIS）对于舰船航行安全意义重大,通过利用ACE具备的操作系统无关的接口封装性及面向网络化应用的设计模式,提出并实现了基于ACE反应器模式框架的ECDIS网络接口设计。     

Rural transport – Valuing the mobility of older people

This paper describes a series of focus groups that were undertaken in the Republic of Ireland and Northern Ireland to examine the challenges faced by older people in rural Ireland when trying to make trips. The paper outlines transport policy in both Northern Ireland and the Republic of Ireland and describes the activity patterns of older trip makers and the modes they use. It also discusses some of the contrasts between challenges faced by older men and older women. Both older men and older women experience a shrinking in activity spaces and activity participation when older. Older women are less likely to drive and to own a car and so are seriously impacted by loss of a spouse in terms of their unmet travel needs. However, older men also experience difficulties: the alternatives that are available (such as community transport schemes) provide trips and services that are more attractive to women. In addition, the car dependent lifestyles of men throughout their adult lives seems to make them less prepared for life without a car than older women.     

Attitudes of Hong Kong residents to cars and public transport: Some policy implications

Hong Kong currently has low levels of car ownership and use due to a combination of good public transport, high population densities and high private transport costs. However, levels are rising, contributing to congestion and environmental problems. A major response by the government is to seek to increase rail's share of public transport journeys from its current level of 33% to 45% by 2016. After reviewing the transport situation in Hong Kong, the paper discusses the appropriateness of these targets as well as questioning whether they are achievable. The results of a questionnaire survey of 595 residents of Hong Kong, designed to elicit people's attitudes to cars and public transport, are analysed. It is concluded that unless the government does more to curb car ownership and use, rail targets will have little chance of being achieved.     

What are the value and implications of two-car households for the electric car?

The major barriers to a more widespread introduction of battery electric vehicles (BEVs) beyond early adopters are the limited range, charging limitations, and costly batteries. An important question is therefore where these effects can be most effectively mitigated. An optimization model is developed to estimate the potential for BEVs to replace one of the conventional cars in two-car households and to viably contribute to the households’ driving demand. It uses data from 1 to 3 months of simultaneous GPS logging of the movement patterns for both cars in 64 commuting Swedish two-car households in the Gothenburg region.The results show that, for home charging only, a flexible vehicle use strategy can considerably increase BEV driving and nearly eliminate the unfulfilled driving in the household due to the range and charging limitations with a small battery. The present value of this flexibility is estimated to be on average $6000–$7000 but varies considerably between households. With possible near-future prices for BEVs based on mass production cost estimates, this flexibility makes the total cost of ownership (TCO) for a BEV advantageous in almost all the investigated households compared to a conventional vehicle or a hybrid electric vehicle. Because of the ubiquity of multi-car households in developed economies, these families could be ideal candidates for the initial efforts to enhance BEV adoptions beyond the early adopters. The results of this research can inform the design and marketing of cheaper BEVs with small but enough range and contribute to increased knowledge and awareness of the suitability of BEVs in such households.     

Characteristics of operating mode distributions of light duty vehicles by road type,average speed,and driver type for estimating on-road emissions: Case study of Beijing

Abstract

Researchers have collected extensive vehicle activity data in Beijing using GPS and attempted to develop a comprehensive database of facility- and speed-specific operating mode (OpMode) distributions of various vehicle types for estimating on-road vehicle emissions. This study developed the specific OpMode distributions of light duty vehicles (LDVs) for both restricted access and unrestricted access road types at various average speeds for characteristic analysis. (1) Strong patterns are found in the variations in OpMode distributions with the increase in the average speed: the time fraction of Decelerating/Braking remains less than 7%. The fraction of Idling decreases dramatically from 95% to 0%, while the fraction of Cruising/Accelerating increases from 2% to 94%. The fraction of Coasting increases to 28% and then decreases. (2) The time fractions for restricted access and unrestricted access are significantly different at the same average speeds, especially in Operating Modes #0, #1, #11, #12, #13, #14, #21, and #22, possibly causing an error of 20% in the emissions estimations. (3) Taxis show different OpMode distributions than those for private cars in the operating modes of Decelerating/Braking, Idling, and high-VSP modes, especially at low average speeds. The differences are derived from the more skillful driving behaviors of taxi drivers and may cause an estimation error of over 10%. Thus, the activities of taxis and private cars should be modeled separately for on-road emissions estimations.     

Unraveling the relationship between trip chaining and mode choice: evidence from a multi-week travel diary

Abstract

Trip chaining (or tours) and mode choice are two critical factors influencing a variety of patterns of urban travel demand. This paper investigates the hierarchical relationship between these two sets of decisions including the influences of socio-demographic characteristics on them. It uses a 6-week travel diary collected in Thurgau, Switzerland, in 2003. The structural equation modeling technique is applied to identify the hierarchical relationship. Hierarchy and temporal consistency of the relationship is investigated separately for work versus non-work tours. It becomes clear that for work tours in weekdays, trip-chaining and mode choice decisions are simultaneous and remain consistent across the weeks. For non-work tours in weekdays, mode choice decisions precede trip-chaining decisions. However, for non-work tours in weekends, trip-chaining decisions precede mode choice decisions. A number of socioeconomic characteristics also play major roles in influencing the relationships. Results of the investigation challenge the traditional approach of modeling mode choice separately from activity-scheduling decisions.     

Analysis of within-household effects and between-household differences in maintenance activity allocation

This paper investigates the allocation of household individuals to out-of-home maintenance activities using the rich activity-travel diary data from the San Francisco Bay Area. Two inter-related decisions are considered in this context: (i) whether the given activity episode is performed individually (solo) or jointly, and (ii) the person who participates in the activity, if it is a solo activity. To account for the conditional nature of the solo activity person selection, a nested mixed logit modeling framework is proposed and implemented to jointly analyze person allocation for all maintenance activities performed by a household on a given day. The model is used to investigate within-household effects and between-household differences. The proposed model relaxes some important restrictions in person allocation models by accounting for various sources of correlations and relaxing the assumption of constant variance across households. The proposed model is used to analyze the differences in person allocation between different types of households. The results indicate that life-cycle and household role, income, gender, employment status, and several types of constraints (activities including cost, time-availability, vehicle-availability, coordination constraints, and child-care obligations) affect person allocation decisions in the context of maintenance activities. The empirical results indicate the presence of various sources of correlations across persons, over activities, and within-household that are significant. In addition, the data also provides evidence that the unobserved variances in person selection utilities are not constant across households. A better understanding of these within-household interactions and between-household differences may be used in activity-based simulation models and to develop more effective and focused demand management measures.     

Generating complete all-day activity plans with genetic algorithms

Activity-based demand generation contructs complete all-day activity plans for each member of a population, and derives transportation demand from the fact that consecutive activities at different locations need to be connected by travel. Besides many other advantages, activity-based demand generation also fits well into the paradigm of multi-agent simulation, where each traveler is kept as an individual throughout the whole modeling process. In this paper, we present a new approach to the problem, which uses genetic algorithms (GA). Our GA keeps, for each member of the population, several instances of possible all-day activity plans in memory. Those plans are modified by mutation and crossover, while bad instances are eventually discarded. Any GA needs a fitness function to evaluate the performance of each instance. For all-day activity plans, it makes sense to use a utility function to obtain such a fitness. In consequence, a significant part of the paper is spent discussing such a utility function. In addition, the paper shows the performance of the algorithm to a few selected problems, including very busy and rather non-busy days.