Trip Generation Rates Research Articles

Pedestrian-oriented development in Beirut: A framework for estimating urban design impacts on pedestrian flows through modeling, participatory design, and scenario analysis

As municipalities are setting ambitious targets to increase non-motorized transportation mode shares, analytic frameworks for examining how such targets will be met become increasingly important. In this article, we update the Urban Network Analysis pedestrian modeling framework designed to link land use and urban development changes with pedestrian mobility outcomes by introducing new methods for capturing the effects of street properties on pedestrian travel demand and adjusting pedestrian trip generation rates with k-nearest accessibility scores based on destination availability in each context. This framework was used in conjunction with a participatory design process in Beirut, Lebanon to estimate pedestrian mobility impacts of three urban design scenarios. We illustrate how each scenario affects pedestrian trip generation across various trip types and trip distribution on individual street segments. Our approach demonstrates how urban design interventions–both land use changes and street quality improvements–can influence pedestrian travel demand. Estimates of these changes can provide planners and policymakers with valuable benefit-cost analyses of public space improvements, and a framework for understanding how site-specific planning and development decisions can impact progress towards (or away from) non-motorized mobility goals.

The positive impact of transit-oriented-development characteristics on Metro Station usage: A case study of Tehran's metro stations and TOD index calculation

Transit-Oriented Development (TOD) facilitates the creation of more walkable cities. To implement TODs, urban planners need a mechanism to delineate TOD levels so they can envision future planning trajectories. This study offers an approach to developing scores for TODs within Tehran, a metropolitan area with metro stations and Bus Rapid Transit that facilitate public transportation usage. TODs exhibit distinct characteristics when compared to other areas within a city. Furthermore, TODs vary in their levels of integration across transit, commerce, and residential, necessitating policies specific to each TOD. The main objective is 1) To identify the factors that best define TODs for metro stations and 2) To develop a TOD index to measure the TOD score. We used three different spatial units of measurement to define a range of metrics to identify how effective TODs work with different characteristics. The spatial units include: 1. Thiessen polygons 2. the walkable distance of the transit nodes and 3. Thiessen polygons without the walkable distances. The main criteria we used are travel behavior, walkability, accessibility, transportation inclusivity, network attribute, trip generation rate, and land use. The metrics are weighted based on the correlation results with the usage rate. A Negative Binomial regression was developed to find the metrics that are significantly influential on the usage rate of the metro stations. Results indicate that all criteria except the land use are significantly correlated with the usage rate of metro stations.

Exploring the spatiotemporal factors affecting bicycle-sharing demand during the COVID-19 pandemic.

This study investigates the roles of the socio-economic, land use, built environment, and weather factors in shaping up the demand for bicycle-sharing trips during the COVID-19 pandemic in Toronto. It uses "Bike Share Toronto" ridership data of 2019 and 2020 and a two-stage methodology. First, multilevel modelling is used to analyze how the factors affect monthly station-level trip generation during the pandemic compared to pre-pandemic period. Then, a geographically weighted regression analysis is performed to better understand how the relationships vary by communities and regions. The study results indicate that the demand of the service for commuting decreased, and the demand for recreational and maintenance trips increased significantly during the pandemic. In addition, higher-income neighborhoods are found to generate fewer weekday trips, whereas neighbourhoods with more immigrants experienced an increase in bike-share ridership during the pandemic. Moreover, the pandemic trip generation rates are more sensitive to the availability of bicycle facilities within station buffers than pre-pandemic rates. The results also suggest significant spatial heterogeneity in terms of the level of influence of the explanatory factors on the demand for bicycle-sharing during the pandemic. Based on the findings, some neighbourhood-specific policy recommendations are made, which inform decisions regarding the locations and capacity of new stations and the management of existing stations so that equity concerns about the usage of the system are adequately accounted for.

Improvement of trip generation rates for mixed-use development in Klang Valley, Malaysia

Mixed-use developments (MXDs) are a single development project that integrates and interacts with different land uses. Traffic is estimated to be reduced with such development. However, there is no standard procedure is available to estimate the MXD trip generation rates in Malaysia. The Malaysian Trip Generation Manual (MTGM) is the guidelines currently been used to forecast future trips for single land use. If the trip generation rates for multiple land uses are summed as MXD trips, the total trips will be overestimated without considering the internal trip capture. This study aimed to establish an improved method for estimating the MXD trip generation rates. Four MXD observation sites were selected in Klang Valley. Traffic survey counts were conducted considering person-trip, including passengers in vehicles and pedestrians. The results revealed that the MXD trip generation rates with MTGM were higher than actual traffic counts during peak hours. The MXD adjustment factor was established as 0.63, which can be applied by multiplying the MTGM trip generation rates to reduce the generated MXD trips in PCU per hour. This research has formulated a new data collection method by integrating person counts, alongside with new guidelines for pedestrian counts. The findings provide an option to adjust the MXD trips and prevent from overestimating future trips, which may result in overdevelopment and spending on mitigation measures in urban planning and road infrastructure.

Trip Attraction Rates of Banking Services in Developing Countries' Cities

There is a lack of studies on trip generation rates related to land use activities in developing countries. The absence of trip rates makes transportation planners use rates listed in the Institute of Transportation Engineers (ITE) Trip Generation Manual, which may lead to unrealistic results. The study aims to determine trip attraction rates for banking services in Zagazig city, Egypt, and evaluate the factors affecting the attracted trips to the banks. The study has designed and implemented a comprehensive data collection and analysis program. The study sample contained nine banks. The study has conducted field surveys that counted the total number of persons entering/exiting the bank under investigation and the generated traffic volume of the adjacent street. The trip rates have been established in terms of independent variables, i.e., gross floor area, the total number of employees, and the number of tellers for different types of banks. Findings showed that average trip attraction rates for public banks were higher than for private banks. There was a strong relationship between trip attractions and the total number of employees at public banks. The most representative factor of private banks' trip attractions was the number of tellers. Doi: 10.28991/CEJ-2023-09-02-07 Full Text: PDF

A comprehensive review of trip generation models based on land use characteristics

• Existing researches on the impact of land use on trip generation has been explored. • Advanced data collection techniques for travel data collection were investigated. • Numerous approaches to trip generation modelling have been discussed. To assess the impact of any proposed development, it is necessary to estimate the trips that are likely to be generated because of such development. In case of developing countries, land use pattern varies significantly and it becomes very challenging to model the trip rates. In view of this, an effort has been made to synthesize the available literature related to modelling of trip generation rates. This paper provides a comprehensive review of studies related to impact of land use on trip rates, data collection techniques and modelling approaches. Major challenges associated with modelling of trip generation includes the unavailability of standard reference databases for multimodal trip generation, consideration of land use evolvement, less explored machine learning modelling approaches, and the feasibility of using emerging data collection techniques in travel surveys. Finally, a framework is proposed for modelling multimodal trip generation rates considering the above identified issues.

Contextual Adjustment of the Institute of Transportation Engineers Trip Generation Rates for Small and Medium Urban Areas in Louisiana

The Institute of Transportation Engineers (ITE) Trip Generation Handbook has been in common use since the 1970s to estimate vehicle trips generated by more than 172 land use categories as a function of establishment size. However, observed trip rates display a huge error range across different land use categories and urban contexts. Although contextual adjustment factors can ameliorate the error in the ITE trip generation estimates considerably, local site-specific trip generation rates should be collected for this purpose. Given the huge time and monetary costs of data collection, adjusting the ITE trip generation rate is mainly done in large metropolitan areas such as Portland, OR, Baltimore, MD, and San Francisco, CA, while it is ignored by many jurisdictions in small to medium-sized metropolitan areas. Here, the ITE trip generation rates for strip mall land use in Louisiana are adjusted by considering the extent to which the built environment characteristics can improve the accuracy of estimated vehicle trip generation rates in smaller urban areas. Vehicle trip data were collected for two consecutive days at 40 strip malls across eight different urban areas of Louisiana to develop whole day and afternoon peak hour contextual adjustment factors for the given land use category across the study area. The results of this study show noticeable improvement for whole day analysis compared with the ITE method by producing a 42% reduction in root mean square error .

Land use variables affecting travel behaviour: a review

Research on the impact of land use variables on travel behaviour is reviewed. The focus is on density as an important measure of land use and its interaction with transportation systems. The effect of density was first addressed decades ago, so research published since the 1960s was reviewed. The reviewed works were classified into two groups according to the most commonly used measure of density and the most common variables of travel behaviour. The first group comprised 26 studies published before 2000 and the second group comprised more than 45 studies published after 2000. Population density was the main density term used in the first group while employment density and configurations of densities were integrated as measures in the second group. A direct relationship between mode choice and journey length was established. However, knowledge gaps were also identified, such as the effect of density on trip generation rate, type of trip according to trip purpose, internal and external trips, and trips on weekdays and weekends.

A spatial analysis of demand patterns on a bicycle sharing scheme: Evidence from London

This paper investigates the spatial demand for bikesharing through the application of a series of trip generation models for the London Bicycle Sharing Scheme (LBSS). The production of trips from and the arrival of trips at scheme stations are evaluated in reference to how they connect with features of the built environment, demographics of the resident and workplace populations, and attributes of the scheme's structure. A spatial econometrics approach is taken to specify the models, with four different time windows considered throughout the day for all trips taken during 2016. The built environment features show a consistent pattern of results in the model, indicating that proximity to cycling infrastructure, rail stations, parks, university facilities, as well as the density of shops and conventional roads in the vicinity of stations is linked with trip generation rates. The presence of males and Caucasians are associated with higher station demand, aligning with other work on the introduction of new mobility solutions elsewhere, though we do find that greater distances to work tend to depress use. Trip generation is also reduced at the minority of stations located south of the River Thames, indicating that the presence of natural barriers can affect the operation of schemes. The results carry implications for scheme integration in other cities.

Short-term forecasts on individual accessibility in bus system based on neural network model

Precise forecasts on individual accessibility in bus system can help make policies to accommodate fluctuating bus travel demand and promoting social equity. In this study, we propose a three-stage method for short-term forecasts on individual accessibility in bus system based on neural network (NN) model. In the first stage, a NN model is designed to tackle the nonlinear mapping between passengers' bus trip appearances in historical periods and those in the predicted period. A rate function, which considers bus trip generation rates of passengers, is then applied using outputs of the designed NN model. In the second stage, probabilities of origin-destinations (ODs) chosen by passengers in the predicted period are calculated. In the third stage, land use information combined with results of previous two stages are used to obtain the individual accessibility in bus system in the predicted period. Compared to individual accessibility calculated by real data, it is found that the average errors of predicted results by the proposed method in weekdays and at weekends are only 8.37% and 10.13%, respectively. The results also demonstrate the capability of combining a NN model, traffic data and land use information to forecast the future spatial distribution of individual accessibility in transport system.

Estimation of trip generation rates for residential land use in Uyo, Nigeria

Change in trip rates affects a transportation system and could lead to the redesign of the transport infrastructure in order to satisfy the new demand. This study estimates trip generation rates for residential land use in Uyo using cross classification method. Five (5) residential estates were considered and household survey carried out to collect trip data from 500 households on purpose and mode of travel through household interview and their response recorded in questionnaire. Four independent variables (household size, household income, car ownership, number of employed persons) were used for the study based on the prevailing conditions of theresidential land use. Cross-classification trip rates were developed from the most significant variables; household size, household income and car ownership. The analysis indicated that work trip produced the highest reported trip rates of 29.6% followed by religious trip of 24.7%. Similarly, private car trips contributed 42.8% of trips made by mode of travel as the highest trip. It was found that household size is the strongest socio-economic variable that influence trip generation in residential land use in Uyo. The cross-classification trip rates developed in this study could provide basis for the estimation of trip generation in residential land use in Uyo.
 Keywords: Trip generation; analysis of variance, ANOVA; cross classification

Site characteristics associated with multi-modal trip generation rates at residential developments

This research aims to contribute to understanding the range of site characteristics that are associated with multi-modal trip generation rates at residential developments. Data was extracted from the Trip Rate Information Computer System (TRICS) database for 933 residential developments in the United Kingdom and Ireland, with trip generation rates estimated separately for person, vehicle, public transport, pedestrian and bicycle trips. A total of 65 independent variables were included in the analysis, representing a range of site characteristics relating to location and housing attributes, public transport service quality, parking and travel plan measures. Trip generation rates by mode and time period were then regressed against the site characteristics to explore their association with multi-modal trip generation. Key findings showed that multi-modal trip generation rates are associated with a range of site characteristics at residential developments. These include, to varying degrees, locational and housing attributes such as apartment developments and housing size, population density, car ownership, distance to local facilities such as the nearest local/corner shop, public transport service quality, on-site parking spaces/dwelling, plus various travel plan initiatives such as secure well-lit/covered cycle parking. The results imply that various site characteristics deserve greater consideration in establishing multi-modal trip generation rates and that characteristics that support travel by non-vehicle modes should be incorporated within new residential developments where possible.

Beyond land use mix, walkable trips. An approach based on parcel-level land use data and network analysis

ABSTRACT Land use mix is one of the cornerstones for urban sustainability, in opposition to functional segregation and zoning policies. Land use mix is a prerequisite for urban proximity dynamics, healthier lifestyles and public space vitality. However, methodological shortcomings to its measurement remain and are responsible for the unexpected weak association with pedestrian activity. This study puts forward a novel method to reframe, measure and map land use mix as ‘walkable trips’, a closer approach to its benefits based on functional and spatial complementarity. The method draws on newly available cadastral microdata at the parcel-level that, combined with trip generation rates and network analysis tools, enable a detailed assessment and mapping of potential for walkable trips, as well as a proxy to the spatial patterns of urban vitality, in line with the principle of the 15-minute city. The method is applied to the case of the Madrid metropolitan area.

Understanding the transport and CO2 impacts of on-demand meal deliveries: A London case study

The rise of the on-demand economy has led to a rapid increase in the delivery of meals from restaurants and fast food outlets by delivery drivers (DDs) using bicycles, mopeds and cars, with newly-established platform providers handling order and payment processing and, in many cases, the co-ordination of these deliveries. Little is currently understood about the collective transport impacts of such activity in urban centres and to what extent this poses challenges for transport policymakers. The paper provides an international review of market growth in this sector together with insight into key topics associated with its freight delivery operations in urban areas. Using a substantial database of meal deliveries made in London by a major platform provider, this paper quantifies the operational performance of these deliveries and their transport and environmental impacts. On average, 9.6 deliveries were undertaken by a DD daily, with each taking 25 min from pickup to delivery with an average trip length, from restaurant to customer of 2.2 km (1.4 miles) a DD travelling 41.3 km (25.7 miles) in total per day, The analysis of the case study indicates the relative transport inefficiency of these on-demand meal deliveries compared to other forms of urban road freight (with a meal delivered by car being responsible for approximately 1300 times the distance travelled by an articulated HGV operation per tonne delivered). It also highlights the far greater GHG emissions and transport intensity associated with meals deliveries by cars and petrol mopeds compared to bicycles (emitting 5 and 11 times more GHGs per meal delivered than bicycles, respectively).The transport and GHG emissions intensity of these meal deliveries raises important policy issues, especially given therapid growth in the provision of, and demand for, these services internationally, Based on the review and analysis, the paper provides a discussion of the key issues that urban policymakers around the world need to take account of in relation to this fast-growing sector including vehicle fuel sources, road safety, trip generation rates and their impacts on local residents, together with recommended actions.

Institute of Transportation Engineers Guidelines versus Actual Trip and Parking Generation for a Transit-Oriented Development in an Auto-Oriented Region

The Institute of Transportation Engineers (ITE) guidelines serve as the most widely used reference for trip and parking generation estimates for any new development in the U.S.A. However, recent empirical studies question the efficacy of ITE guidelines in forecasting trip and parking generation in transit-oriented developments (TODs). Following the methodology of studies on seven TODs across the U.S.A., this study focuses on Dallas (TX), as a more auto-oriented American city, to explore the trip and parking generation at Mockingbird TOD. It finds that, with the exception of Station Park in Salt Lake City (which is really a transit-adjacent development rather than a TOD), the Mockingbird TOD has the lowest walk mode share (13.6%), the lowest bike mode share (0.22%), the lowest bus transit mode share (1.09%), and by far the lowest rail transit mode share (5.9%) of all the other seven TODs. Similarly, the Mockingbird TOD ranks first in relation to the driving mode share, with about 80% of its daily trips generated by driving. This is almost twice as many driving trips as the average of the other six TODs, which makes Mockingbird an auto-oriented TOD located in an auto-oriented region where more than 96% of commuting trips are by automobile. Still, the total automobile trip generation rate in Mockingbird is about 12% lower than the ITE estimates. Similarly, while the parking supply in Mockingbird TOD is less than 48% of the ITE recommended supply rate, its peak parking occupancy is only about 55% of the TOD supply.

Trip Generation Rates of Land Uses in a Developing Country City

In recent decades, a major shift in the land use pattern has been observed in Dhaka, the capital city of Bangladesh. To understand and model the impact of these land use changes on transportation demand, this study aimed to determine the trip generation rates for six different land use categories adjacent to Mirpur Road in Dhaka. A total of 20 establishments consisting of six land use categories were selected for the collection of data on person trip rates and respective modal share by manual counts and intercept surveys. These data were used to develop vehicular trip generation rates for each land use category in passenger car equivalents as a uniform unit of comparison. Results showed that commercial and healthcare land uses had the highest average and peak-hour trip rates. There was also a significant variation in the share of eight transport mode categories among the trips generated by the land uses. The peak-hour trip generation rates of the study area were found to be different from the values established by the Institute of Transportation Engineers which corresponds to the fact that trip generation depends on a host of factors, such as surrounding land uses, modal share, the economic condition of a region, and so forth, rather than on a single factor inherent to the land use. The findings of this research can help to determine the trip generation impact of new establishments and consequently identify suitable locations to minimize the impact.

Links between freight trip generation rates, accessibility and socio-demographic variables in urban zones

This paper proposes an assessment of the links between freight trip generation (FTG) rates and accessibility. First, the paper overviews the background, sets the context and motivates the research. Second, it presents the proposed methodology, which combines an FTG model, two accessibility indicators and a linear regression analysis to assess the relationships between freight trip demand and a set of socio-demographic variables including accessibility. The FTG modelling framework, adapted from previous works, allows estimating the number of freight trips with a small amount of standard data, even when no surveyed data is available. The two gravity accessibility indexes, one potential and one exponential, are defined in the continuity of recent freight accessibility works. To those indicators, a set of socio-demographic variables, including population, area or a zone (or density), are introduced. The relationships between FTG and all those variables are assessed via standard linear regression methods completed by the verification of the corresponding linear relationship hypotheses. Third, the framework is applied to the urban area of Lyon (France), where no urban goods survey data is available. Results show that potential accessibility seems to have a better correlation to FTG and could be a good decision support indicator when combined with the population as an explanatory variable. The population can be added to accessibility as an explanatory variable, the resulting models with two variables have a slightly lower accuracy but remains close to that of models with only accessibility as an explanatory variable. This work remains exploratory and finishes by proposing practical implications and further development lines.

Influence of the built environment on sustainable trips: the case of Niterói, Brazil

Various studies have found that accessibility conditions, especially for non-motorised trips, can be more effective if solutions involving the built environment are considered. These studies reveal that the dimensions of the constructed space, such as dense, diverse and connected land use, can increase the potential for sustainable trips. To observe that influence, this paper reports the results of a survey conducted among residents of 24 condominiums in three districts of the city of Niterói, Brazil, to measure the index proposed by Grieco et al. This application intends to estimate the potential of the built environment of each area to stimulate the generation of sustainable trips and compares this with the overall trip-generation rates. The results show that the estimates of the index correspond to the patterns of sustainable trips, represented by the percentage of trips made on foot or by public transportation in relation to total trips. The empirical results also indicate that: (a) the built environment was more influential than income level in generating sustainable trips and (b) the built environment with lowest potential to promote walking generated more than four extra daily trips by car per residential unit than in the other two districts.

Predicting Carsharing Station-Based Trip Generation Using a Growth Model

Carsharing is a service that allows members to rent cars for a limited time. In Montreal, Quebec, Canada, two types of services exist: a station-based and a free-floating service. This paper proposes a trip generation model for the station-based service of the Communauto carsharing operator for 2016. To better understand relations between space and time, a growth model is used, considering these factors at different levels. For example, some factors can impact all stations similarly, while other factors may impact each station differently. Thus, this model allows to consider both spatial and temporal variables allowing more precise estimations. The aim of this research is to estimate carsharing trip generation at the station level and provide insights into the impacts of implementing new stations on demand. A step-by-step approach was adopted to define the best predictive model for the use of carsharing stations. While more complex model formulations need to be tested to enhance the analysis, the final growth model obtained indicates that, in addition to the number of vehicles available at the stations, several exogenous factors have a significant impact on the trip generation rate of a carsharing station. For instance, the model shows that demographic factors, walkability level and number of bus stations have significant impacts on the use of carsharing stations.

Taxas e modelos de geração de viagens para postos de combustíveis – estudo de caso em Florianópolis/SC

Este trabalho apresenta uma pesquisa realizada em treze postos de combustíveis na cidade de Florianópolis/SC, seis localizados no centro da cidade e outros sete em importantes praias, onde foram realizadas contagens volumétricas de tráfego nos principais acessos aos postos, num período de 16 horas. Da análise dos resultados, foram obtidas as taxas de geração de viagens em função das variáveis: área construída, número de bombas e posições de abastecimento e modelos de regressão linear múltipla que indicaram uma boa correlação das variáveis explicativas: área total construída, área da conveniência e o preço do combustível. Com base na bibliografia disponível, obtida através de uma revisão bibliográfica narrativa e sistemática, realizou-se a comparação das taxas propostas na pesquisa com a realidade americana. Espera-se, com este trabalho, contribuir para estudos mais abrangentes da geração de viagens em postos de combustíveis, oferecendo, aos planejadores de transporte, importante ferramenta para avaliação de impacto deste tipo de empreendimento.