Household Trip Generation Research Articles

Household Trip Generation and the Built Environment: Does More Density Mean More Trips?

Trip generation is the first step in the traditional four-step trip-based transportation model and an important transport outcome used in evaluating the impacts of new development. There has been a long debate on the association between trip generation and the built environment, with mixed results. This paper contributes to this debate and approaches the problem with two hypotheses: 1) built environment variables have significant impacts on household total trip generation; and 2) built environment variables have different impacts on trip generation by purpose. This study relied on data from the Portland, Oregon, metropolitan area to estimate negative binomial regression models of household trip generation rates across all modes. Results show that the built environment does have significant and positive influences on trip generation, especially for total number of trips, total number of tours, and home-based shopping-related trips. Moreover, log likelihood ratio tests implied that adding built environment to the base model contributed significantly to improving model explanatory and predictability. These findings suggest that transportation demand models should be more sensitive to the effects of the built environment to better reflect the variations in trip making across regions.

MODEL BANGKITAN PERGERAKAN RUMAH TANGGA BERDASARKAN GENDER UNTUK AKTIFITAS MANDOTORY DI KOTA BANDA ACEH

Trip generation in the household is very influential on the activity it has. Routine activity that should be done by an individual itself also called as mandatory activity. Also with the trip generation performed can be affected by social status owned, one of which is gender. Gender is the division of roles between men and women which can have a difference. The occurrence of traffic density due to the characteristics of community within a household of trip generation making the purpose of this research is to know the socio-economic characteristics, demography and tip behavior, knowing factors which influence the trip generation of a household based on gender for mandatory activity and to get the model, and the difference of utility and probability value. Area of this research are 4 sub-districts in Banda Aceh city which are Jaya Baru sub-districts, Banda raya, Lueng Bata, and Kuta raja sub-district with the sampe numbers of 400 samples. Method used is Model of Binomial Logit Difference then processed by using SPSS v20. Characteristics of Socio-economic, demography, and trip behavior which produced by 19 variables in this research one of its variable is gender that is 54% for men and 46% for women. From the utility model obtained, then the factors that affecting the movement of the household based on mandatory activity on men are number of family members and activity duration, while for women are number of family members who attend school and activity duration. Probability for the household Trip generation is probabilitas ≤ 3 movement and greater than 3 movements based on the mandatory activity for men are 75% and 25%, while for women are 72% and 28%.

Urban Socio-Economic Variables and Intra-Urban Trips in Ogun State, Nigeria

This study examines the relative influence of socio-economic variables of urban centers on intra-city tripgeneration. Data were collected on sixteen socio-economic variables and household trip generation in fourteen urbancenters of the state. The nature and degree of relationships between socio-economic variables and trips generated wereestablished through simple bivariate correlation technique. Multiple regression analysis was used to explain variablesthat predict trips generated. The principal component analysis was used to resolve observed collinearity problem in regressionanalysis.There is a strong significant positive correlation between trip generated and 13 out of sixteen socio-economicvariables. The principal component analysis on the socio-economic variables produced two components: socialand commercial component and industrial development component.The two components explain 58.68% of variationin intra-urban trips generated (F=7.830, P≤0.50), (F=13.982, P≤0.50). The industrial development component does notprovide significant explanation.The study emphasizes the need for proper planning and effective monitoring of developingof socio-economic variables in cities because of their critical influence on trip generation.

Urban Socio-economic Development and Intra-city travel in Ogun state, Nigeria

This study is on influence of socio-economic development of urban centers on intra-city trip generation in Ogun state, Nigeria. The proportion of the aggregate socio-economic variables in each city was used to rank the cities in hierarchical order of development while the average household trip per week was used to rank cities on trip generation. Spearman rank correlation was used to establish nature and extent of relationship between level of urban development and frequency of trip generation of urban centers. The urban centers exhibit hierarchical development pattern both in level of development and trip generation. Abeokuta dominates the distribution of socio-economic variables with aggregate average of 31.22%. This is followed by Ijebu-Ode (14.41%) and Sagamu (10.33%). In the same manner, Abeokuta has the highest average of household trip generation in the state. Ijebu-ode and Sagamu followed with 43 trips per week each. There is a significant high positive correlation coefficient (r=0.75, p≤0.01) between level of urban development and household trip generation. With coefficient of determination (r2) of 0.56, 56% of variation in household trip generation in Ogun state is explained by level of socio-economic development of cities. This suggests the needs to be critical in using socio-economic characteristics of residents alone as measures of determinants of household travel behavior as done in several previous studies in transport research.Key words: Intra-urban, trip generation, Socio-economic development, urban centers, Nigeria, OgunState.

Developing a Statewide Travel Demand Model from a Person-Based Time Series Household Survey

Balancing the funding needs of data collection and model development is a recurring problem for state departments of transportation and metropolitan planning organizations throughout the country. To address this problem, the Delaware Department of Transportation (DelDOT) and the University of Delaware have developed an innovative and cost-effective person-based time series household survey that has been conducted annually since 1995. The survey diverges from traditional household travel diary surveys in that it is a telephone survey that collects detailed demographic information on all household members but collects trip information from only one randomly selected household member. While the survey costs between 20% and 50% less than a typical household travel diary survey and greatly reduces nonresponse bias, this survey poses two complications. The first is that household trip generation rates must be synthesized if trip productions are to be estimated on the basis of household cross-classification tabl...

Developing a Statewide Travel Demand Model from a Person-Based Time Series Household Survey

Balancing the funding needs of data collection and model development is a recurring problem for state departments of transportation and metropolitan planning organizations throughout the country. To address this problem, the Delaware Department of Transportation (DelDOT) and the University of Delaware have developed an innovative and cost-effective person-based time series household survey that has been conducted annually since 1995. The survey diverges from traditional household travel diary surveys in that it is a telephone survey that collects detailed demographic information on all household members but collects trip information from only one randomly selected household member. While the survey costs between 20% and 50% less than a typical household travel diary survey and greatly reduces nonresponse bias, this survey poses two complications. The first is that household trip generation rates must be synthesized if trip productions are to be estimated on the basis of household cross-classification tables; the second is that the data must be normalized to represent a data set for a single year. A description is provided of the procedure by which this survey was used to perform a major update of DelDOT's statewide travel demand model in 2003. The survey was relied on to provide key information in the first three steps of the four-step travel demand modeling process. This survey method has the potential for widespread application, particularly for microsimulation models, which would not require the household synthesis step.

Unit of analysis in conventional trip generation modelling: an investigation

This paper examines the importance of the unit of analysis selected for trip generation modelling when the model estimation data are collected in a household travel survey. The paper reviews the literature on the arguments made for the use of the "individual" or the "household" as the unit of analysis in trip production modelling, and then through a statistical exposition it determines what should be the appropriate unit of analysis. An empirical test of the forecast performance of household- and person-trip generation models is conducted using data collected in a household-travel-behaviour survey in the Greater Toronto Area of Canada. The paper concludes that the household is theoretically the preferable analysis unit to use in trip production modelling when the model estimation data are collected in a household travel survey in which the household is the sampling unit. The empirical test indicates that household-trip generation models yield predictions of trips at the household and traffic zone level, respectively, that are marginally more accurate than those yielded by person-trip generation models.Key words: trip generation, travel demand forecasting, household trip generation, person trip generation, sampling unit, travel demand modeling, activity-based travel forecasting.

Microsimulation of Neighborhood Evacuations in the Urban–Wildland Interface

Residential development in fire-prone wildlands is occurring at an unprecedented rate. Community-based evacuation planning in many areas is an emerging need. In this paper we present a method for using microscopic traffic simulation to develop and test neighborhood evacuation plans in the urban–wildland interface. The method allows an analyst to map the subneighborhood variation in household evacuation travel times under various scenarios. A custom scenario generator manages household trip generation, departure timing, and destination choice. Traffic simulation, route choice, and dynamic visualization are handled by a commercial system. We present a case study for a controversial fire-prone canyon community east of Salt Lake City, Utah. GIS was used to map the spatial effects of a proposed second access road on household evacuation times. Our results indicate that the second road will reduce some household travel times much more than others, but all evacuation travel times will become more consistent.

Trip Generation Modeling Using CHAID, a Criterion-Based Segmentation Modeling Tool

Conventional trip generation models are identified, as are the difficulties of model application typical of segmentation problems: identification and categorization of explanatory variables and of the interactions among them. The use of CHAID (Chi-Squared Automatic Interaction Detection), a criterion-based segmentation modeling tool, is explored to analyze household trip generation rates. CHAID models are presented in the form of a tree, each final node representing a group of homogenous households concerning daily trip making. An application to data from an origin-destination survey for São Paulo produced interesting results, in agreement with theoretical expectations and amenable to interpretation based on the likely activity-travel patterns of each group of households generated by the technique. CHAID can be used as an exploratory technique for aiding model development or as a model by itself. The use of CHAID results as a trip generation model was verified through an evaluation of its predictive capability in a cross comparison of two subsamples and through a comparison of observed versus predicted trips at a zone level; the segmentation of households produced by the technique provided good estimates of trip rates and zone totals. The application of a modeling approach requiring a highly disaggregate projection of the population may become possible considering the advances in methods for the generation of synthetic populations. The use of these methods in conjunction with a segmentation model represents an alternative to conventional trip generation models and an opportunity to introduce new population forecasting techniques into transportation planning practice.

Household trip generation choice—Alternative empirical approaches

Trip generation models have generally received less attention than other aspects of travel decision making. This article presents some explorations into the structure of trip decisions for shopping, using data from weekly shopping diaries. The paper compares alternative formulations of the naturally-ordered choice model used by Sheffi (1979) to avoid the problems inherent in multinomial logit models. Firstly, imposing cross-alternative restrictions on some of the coefficient values is termed the constrained model. Secondly, when no such restrictions are imposed, the model decomposes into a sequence of binary models, and this is termed the unconstrained model, which can be used to test the validity of the restrictions. The variables used include both shopping expenditures and locational factors, both of which are found to play a key role in shopping travel decisions, as well as more conventional socio-economic variables. A clearer understanding of the role of car ownership in travel decisions is obtained.

Baysian Updating of Trip Generation Parameters

The use of borrowed models from similar urban areas is one way of reducing the costs associated with conducting full-scale travel surveys. However, in order to tune borrowed models to reflect the local conditions of the study area, these models can be updated using low-cost information (objective or subjective) from the study area. A method based on Bayesian statistics for updating cross-classified household trip generation rates is presented. Some updating techniques are briefly reviewed. Previous applications of Bayesian statistics in the transportation field are also discussed; a methodology for their use to update cross-classified trip rates is presented along with sample application.

An empirical comparison of disaggregate category and regression trip generation analysis techniques

Category and regression household trip generation analysis techniques were compared and contrasted. The comparative research was facilitated through a discussion that revealed the interchangeability of two methods of calibrating a category model. While the cell mean method is simple to implement, it does not readily yield statistical indexes for comparison with regression models. The general linear model analysis of variance (GLANOVA) readily provides statistical indexes for the comparison of category and regression trip generation models, and it produces identical empirical results to the simpler cell mean approach of calibrating a category model.

A minimum requirements approach to urban travel

The minimum requirements approach, which has heretofore been restricted to analyses of economic structures of cities and metropolitan regions, has a wider application which includes household travel patterns. Using a cross- section of Israeli settlements, it is shown that clear and consistent relationships exist between minimum expected daily household trip generation for various purposes and the size of the settlement from which these trips originate. Moreover, two distinct general patterns emerge, one for households with vehicles and- a second for households without vehicles; suggesting two distinct modes of "propensity to use" the city and perhaps varied perceptions as well.