Trip Generation

This paper compares the performance of trip generation models. Trip generation estimates the number of trips to and from a traffic analysis zone. This process is the first stage of the conventional four-step travel forecasting framework. Although many approaches have been suggested for this step, regression and category analyses have been widely applied. The two methods have generated an acceptable level of performance from the perspective of transport planning. Critical problems, however, have also been observed. In the regression analysis, trip rates are treated as continuous variables that can be negative, which is obviously unrealistic. Furthermore, the method does not incorporate traveler behavior. For the category analysis, its arbitrary way of choosing independent variables and their strata has drawn critiques. The cell-by-cell calculation in this method also increases the concerns about unreliable estimation of trip rates. Censored regression, count data, and discrete choice models have been visited for the alternative of regression approach while the multiple classification method has been conceived for the substitute of the category analysis. A systematic examination of the performance among the models has not been discussed sufficiently yet, which is the motive of this paper. Six representative models – regression, tobit, Poisson, ordered logit, category, and multiple classification analyses – were applied to the home-based work trips in the Seoul metropolitan area. Cross-validation and back-casting were the key for checking the performance among the models. In this process, the measures of correlation, variance, and coincidence were compared. The category-type model was superior in overall performance."

El desarrollo de técnicas integrales para evaluar las tendencias urbanas a largo plazo es una prioridad para el desarrollo de una sociedad más sostenible. Con el fin de dar un paso más allá de los modelos tradicionales de hora pico, el propósito de este trabajo es desarrollar un modelo estratégico de generación y atracción de viajes que represente la demanda de viajes en un día típico de acuerdo al motivo de viaje. Este estudio hace parte de un modelo de planeación estratégica que incluye, además de la generación de viajes, un modelo de transporte y modelos de usos del suelo, que integrados bajo un marco común, conforman un modelo LUTI (Land-Use and Transport Interaction) que permitirá capturar los mecanismos de retroalimentación que puedan afectar a la generación/atracción de viajes a lo largo del tiempo. Los modelos de generación y atracción de viajes se desarrollaron a partir de la encuesta de movilidad domiciliaria llevada a cabo en Bogotá en 2011. El análisis de regresión lineal múltiple se utiliza para investigar y modelar el efecto del ingreso, tamaño y estructura del hogar, la propiedad de automóviles, el tiempo de viaje y el uso mixto del suelo, en el número de viajes generados por hogar en un día típico. Los modelos de atracción de viajes se estimaron utilizando datos zonales. La integración dentro del modelo LUTI de la generación y atracción de viajes permitirá una discusión sobre la idoneidad del enfoque de modelación propuesto con el fin de probar varios escenarios con altas tasas de motorización de crecimiento y las posibles ventajas (o desventajas) asociados con ellos, proporcionando así conocimientos útiles que inspiren futuras investigaciones sobre la evaluación de las políticas de transporte en las ciudades en desarrollo.
PALABRAS CLAVES: generación de viajes, Bogotá, viajes diarios, modelos LUTI

Hospitals are major trip generators in any country. Significant amount of trips are attracted everyday by numbers of hospitals. A trip to hospital is generally considered as an emergency trip based on purpose. So as it is an emergency purpose, trip attraction plays vital role in solving and improving traffic facilities by developing road networks. Moreover, trip attraction rates of hospitals can be very useful in performing Traffic Impact Assessment (TIA).
Some studies have been conducted based on trips done by people and also on vehicular attraction on western countries, but for a country like Bangladesh no study has been performed for determining the trip attraction rates of hospitals. In this thesis an attempt has been taken to determine trip attraction rates of hospitals in Dhaka city. The study involves the estimation of trip attraction rates of eight different hospitals on various locations. Hourly trip attraction rates are determined based on gross floor area, number of beds, number of employee and number of parking spaces. Trip attraction rates are determined for both the morning and evening peaks. Average trip attraction rates for three major size categories of hospitals (small, medium and large hospitals) are determined. It has been observed that the trip attraction rates of large-size hospitals are higher than the trip attraction rates of small-size and medium-size hospitals.

Transportasi adalah pemindahan manusia atau barang dari satu tempat ke tempat lainnya dalam waktu tertentu dengan menggunakan sebuah kendaraan yang digerakkan oleh manusia, hewan, maupun mesin. Transportasi manusia atau barang biasanya bukanlah merupakan tujuan akhir, oleh karena itu permintaan akan jasa transportasi dapat disebut sebagai permintaan turunan (derived demand) yang timbul akibat adanya permintaan akan komoditas atau jasa lainnya.

Transportation planning is the process of defining future policies, goals, investments and design to prepare for future needs. Many urban cities and towns of India are facing transportation problems due to increased rate of urbanization, urban sprawl and tremendous increase in travel demand. Travel demand management is crucial part of transportation planning which depends on the socio-economic parameters of that area. The study has been carried out for Morbi (a medium town II) of Saurashtra region of Gujarat having population of 1.94 lakh. Morbi is ceramic hub of India which contributes more than 70% of the total ceramic production of India. It has also some other industrial development like manufacturing of wall clock, CFL bulbs and electric bikes which generates employment opportunities. There is remarkable rate of migration due to its industrial development. The public transportation system (city bus service) has been started in 2014 which is not sufficient to cope with the growing travel demand of Morbi. To overcome the transportation issues like increased travel demand, congestion, air pollution - a sustainable development is very much required for Morbi city. The first step taken by researcher is the digitization of map of Morbi city by using TransCAD software. The study area has been divided in to 14 zones. The Home Interview Survey has been carried out for socio economic data and trip information with sample size of 1 in 35 HH. The distances from CBD for all wards have been plotted on digitized map. Trip generation model with regression analysis in Excel sheet is developed for the study area. Mode choice for trips by two-wheeler (43%), Rickshaw (24%), Car (8%), Bus (2%), Bicycle (5%), and Walk (18%), are observed. Trip distribution is the second stage of travel demand modeling. This paper focuses on calibration of gravity model for medium sized city. Calibration parameters for four different impedance factors –Travel distance, Euclidean distance, Travel time and Travel cost have been derived. Trip length frequency distribution of observed trips and modeled trips is presented.

In this paper, we present an ordered logit model. The choice variable (dependent variable) is the number of trips done by an individual in a day. We estimate the model using the data of the Swiss national travel survey, the Mobility and Transport Microcensus, collected in 2015. We internally validate the model. We also externally validate the model using a synthetic population of the Swiss resident population of 2017. Finally, we apply the model to a synthetic population for 2030, forecasting the number of trips that will be done in the future. This is a work in progress, describing an approach and not final results. In particular, no calibration of the cuts of the ordered logit model was done.

This study aims to investigate the possibility of providing the appropriate environment for bicycle riding and walking behaviors. The research examined the students' trip generations and factors influencing the changes in students' travel behavior. Using Mahasarakham University as the study site, the study conducted field survey t o evaluate the spatial characteristics of the routes within the campus. The research interviewed 400 students from 12 Faculties. The current trips generated by students were analyzed and graphically presented. Results can be used to plan campus bike routes and pedestrian ways to fit the patterns of students' trip generation and traveling behavior.

Si bien la relación precisa entre el transporte y los usos del suelo resulta elusiva en muchos aspectos, la existencia de evidencia empírica y científica pone de manifiesto que el transporte y los usos del suelo mantienen entre sí una relación de tipo biunívoca, en la cual la disponibilidad de medios de transporte (públicos y privados) impacta en los patrones de uso del suelo, en tanto que los distintos niveles de densidad que adoptan dichos patrones inciden en la demanda de transporte. De este modo, la existencia de patrones de ocupación residencial de baja densidad incentiva un mayor uso del automóvil particular, incidiendo negativamente en la demanda de transporte público y en la sostenibilidad económica del mismo. Este hecho impacta en la movilidad de la población urbana, afectando principalmente al estrato de menor nivel de ingreso que depende fuertemente del sistema de transporte masivo, limitando así las posibilidades de uso extendido de los activos con los que cuenta la ciudad. A su vez, la implantación de conjuntos residenciales de gran porte contribuye a
congestionar las vías circundantes generando como consecuencia de ello importantes deseconomías de aglomeración, con efectos negativos en la economía y el ambiente urbano.
Las medidas de mitigación requieren un pronóstico del impacto de tránsito efectuado a partir de datos locales. En la ciudad de Córdoba no existen antecedentes de mediciones de tasas de generación de viajes para usos del suelo residenciales. El presente trabajo propone medir tasas de generación de viajes en localizaciones de uso residencial correspondientes a dos tipologías diferentes en relación al tipo de edificación y características del ambiente construido circundante. El trabajo contribuye a la formación de una base de datos con parámetros validados a nivel local, que posibiliten pronosticar el impacto de nuevos usos residenciales en el tránsito urbano.

In modeling travel demand and analyzing travel behavior, it is important to know the behavior of a large number
of individuals. How the individuals choose an alternative among others given in the choice set, and how they
assess and consider the different alternatives, must be a function of several factors including their need, task,
socio-economic, environmental and the level of service offered by the various alternatives. A qualitative analysis
of travel behavior was done with a number of individuals as the samples. To provide the required data, a field
survey as direct home interview survey and travel time survey were conducted and given a number of 233
households and 871 respondents obtained as the samples. Meanwhile, the socio-economic data were obtained
directly from the institution concerned. . The collected data were analyzed by using the Statistical Package for
Social Science (SPSS) Software.The results of the analysis show that people with higher income and more
automobile availability make more travel than people with low income and less automobile availability. The
home-based trips take the largest percentage (50%) of people in the study area. The result also indicates that the
shopping trips (15%) contribute higher among different trip purpose. The results also show that about 57% of
individuals are between 20-50 years. The number of trips generated from each zone is strongly related to the
amount of households, population, active workers and students of that zone. By considering a significant level of
5% four trip generation models have been developed. By using these models future trip generation from each
zone can be determined. By applying the Gravity Model and the Fratar Method, the trip distribution models have
been developed. Three basic models have been introduced by using travel time, road distance and straight
distance as the resistance index. From these models the future travel pattern of Khulna Metropolitan city,
Bangladesh can be predicted.

At Present in India, the Transportation Forecasting is carried out by sequential four step procedure, containing Trip Generation, Trip Distribution, Model Split and Route Assignment. Special generators are introduced in the sequential four-step modeling procedure to represent certain types of facilities (Like-Military bases, Universities, Hospitals and Major shopping centers, Large Industry) whose trip generation characteristics are not fully captured by the standard trip generation module which currently used for the transportation forecasting techniques in India. Special Generators are also used in the traffic impact analysis to represent new developments. Special generators have very different trip generation characteristics and cannot be treated as regular employers. These unique characteristics have a major impact on the transportation system, and treating them no different from a state capital or a major downtown employer does not realistically represent the transportation system and how people use the system.

The development of integrated techniques to evaluate long-term urban trends is a top priority in terms of creating a more sustainable society. In order to take a step forward from traditional peak-hour models, the purpose of this paper is to develop a travel demand (generation and attraction) strategic model of a typical day. The methodology integrates a commuting and non-commuting-related tour generation/attraction model and a Land-Use and Transport Interaction (LUTI) model to capture the feedback mechanisms that may affect tour generation in the long term. The travel demand model is developed from a cross-sectional household mobility survey carried out in Bogota in 2011. Multiple linear regression analysis is used to investigate and model the effect of income, household size and structure, car ownership, travel time and mixed land-use on the number of trips generated by a household on an average weekday. The trip attraction models are at best estimated using zonal data. The Bogota LUTI model that is adopted in this methodology has been benchmarked against other published models to compare its features and capabilities. The integration of the travel demand model and Bogota LUTI model will allow for a discussion on the suitability of the proposed modeling approach in order to test several scenarios with high motorization growth rates, and the possible advantages (or disadvantages) associated with them; thus, providing useful knowledge that will inspire future research on the evaluation of complex transportation policies in developing cities. Abstract The development of integrated techniques to evaluate long-term urban trends is a top priority in terms of creating a more sustainable society. In order to take a step forward from traditional peak-hour models, the purpose of this paper is to develop a travel demand (generation and attraction) strategic model of a typical day. The methodology integrates a commuting and non-commuting-related tour generation/attraction model and a Land-Use and Transport Interaction (LUTI) model to capture the feedback mechanisms that may affect tour generation in the long term. The travel demand model is developed from a cross-sectional household mobility survey carried out in Bogota in 2011. Multiple linear regression analysis is used to investigate and model the effect of income, household size and structure, car ownership, travel time and mixed land-use on the number of trips generated by a household on an average weekday. The trip attraction models are at best estimated using zonal data. The Bogota LUTI model that is adopted in this methodology has been benchmarked against other published models to compare its features and capabilities. The integration of the travel demand model and Bogota LUTI model will allow for a discussion on the suitability of the proposed modeling approach in order to test several scenarios with high motorization growth rates, and the possible advantages (or disadvantages) associated with them; thus, providing useful knowledge that will inspire future research on the evaluation of complex transportation policies in developing cities.

The purpose of this chapter is to highlight the basic ideas underlying social cost-benefit analysis, consider some of the limitations of the analysis, such as those involving measurement issues and philosophical questions, and to outline procedures that can be followed in applying social cost-benefit analysis to the evaluation of environmental spillovers and natural resource use. Subsequently, the valuation of spillovers that have an impact on marketed commodities is discussed and the methods for valuing of changes in environments or natural resources that involve non-marketed economic impacts are considered.

Transportation planners need proper data on ‘Trip Generation’ for new developments and manipulations in the trip generation due to alteration in existing land uses. Trip generation is the first step of the traditional of four step travel demand forecasting process. Thus, trip generation are mainly applied to determine trip production and trip attraction in research area. This study about the development of trip generation model for Putrajaya by using conventional cross classification method to determine the household travel characteristics. Household interview surveys were conducted to determine propose of travelling. A number of 400 household surveys were distributed in 20 selected zones in Putrajaya. The findings of the research show that the vehicle ownership, household size and income are the strong factor that can be af ect trip production in Putrajaya. The production of trips can be classified based on the purpose of the journey as trips for work, trip for education, trips for shopping and other type of trips. Most of the trips were produce due to homebased others which means respondents are very favourable towards went out for shopping, markets or restaurants. So, homebased other categories holding higher number of trips while compare to homebased work and homebased education. The study recommended that the results of trip generation in Putrajaya is useful for the further study on the trip distribution, mode choice and trip assignment models in order to forecast the travel demand for Putrajaya in the future time period.

The study was conducted in Akwa Ibom State, a fast emerging State in the Niger Delta Region of Nigeria. The aim of the study was to model future patterns of trips in the study region. To achieve this, types and volumes of trips generated weekly on the inter-city roads of the region were determined; the influence of the socio-economic development factors on the various trips generated was analyzed. Data on trip were obtained from travel survey while data on the socio-economic development factors were derived from existing records. Multiple regression analysis was used. Eleven types of trips were identified namely; work, school, recreation, religious, medical, wedding, burial, market, personal business, visit to friends/relations and other trips. Models for future estimate of the trips were generated. Establishment of Surveillance Transportation Programme to constantly generate and maintain trip data for update was recommended.

Trip generation and characteristic data was collected over a three week period in November 2002 at Texas Wesleyan School of Law in Fort Worth, Texas, a small urban commuter college.  As a result of this study, trip generation rates for students, staff, and overall were calculated.  In addition, hourly distributions of total daily trips were calculated for each weekday and a typical weekday, which was a synthesis of the daily distribution curves for each weekday.  The typical day distribution was further stratified by student parking lot location.  The results of these stratifications show that for two parking facilities that are equal with respect to cost, quality, size, security, and accessibility, a small difference in parking lot spatial distance can make a large difference in parking lot use and distribution patterns, as a difference on approximately 100 m in spatial difference resulted in the nearer lot being preferred twice as much.  In addition, pricing may not have a substantial affect on parking lot utilization, as students were will to pay more to park in spaces only a few meters closer.  Interviews conducted as part of this study reveal that perceived convenience and perceived safety heavily influence parking choices.

The study was conducted in Akwa Ibom State, a fast emerging State in the Niger Delta Region of Nigeria. The aim of the study was to model future patterns of trips in the study region. To achieve this, types and volumes of trips generated weekly on the inter-city roads of the region were determined; the influence of the socio-economic development factors on the various trips generated was analyzed.  Data on trip were obtained from travel survey while data on the socio-economic development factors were derived from existing records.  Multiple regression analysis was used. Eleven types of trips were identified namely; work, school, recreation, religious, medical, wedding, burial, market, personal business, visit to friends/relations and other trips. Models for future estimate of the trips were generated. Establishment of Surveillance Transportation Programme to constantly generate and maintain trip data for update was recommended. Keywords: Inter-urban, Trip generation, Models, Akwa Ib...

In this study, travel demand in Tehran, the capital of Iran, is modeled in GIS using 3191 census blocks of the city. In the proposed model, the census blocks are considered as traffic analysis zones used for simulating travel origins and destinations in Tehran. Proper demographic data needed for modeling the travel demand are gathered and linked to the census blocks. After data preparation, trip production and attraction are calculated for each block using multiple regression methods. Different types of travel (i.e. for different purposes such as work, study, shopping etc.) cannot be explained by one model only. Therefore, several models are developed for each type of travel considering appropriate parameters. In the next stage, distribution of trips is modeled according to the calculated trip production and attraction, and the distance between the census blocks. The shortest path distance along the street network is considered as the distance between blocks. Suitable friction (impedance) functions and separate gravity-based models are developed for each travel type, in order to distribute estimated trips. Finally, the origin-destination matrix is achieved as the output of trip distribution. Using this matrix, daily trips between various locations are estimated. Having good knowledge about travel demand and travel spatial patterns can be very helpful for urban transportation planners and decision makers to effectively improve and develop urban transportation system.