Trip Origin Research Articles

How Urban Form Characteristics at Both Trip Ends Influence Mode Choice: Evidence from TOD vs. Non-TOD Zones of the Washington, D.C. Metropolitan Area

Understanding travel behavior and its relationship with built environment is crucial for sustainable transportation and land-use policy-making. This study provides additional insights into the linkage between the built environment and travel mode choice by looking at the built environment characteristics at both the trip origin and destination in the context of transit-oriented development (TOD). The objective of this research is to provide a better understanding of how travel mode choice is influenced by the built environment surrounding both trip end locations. Specifically, it investigates the effect of transit-oriented development policy and the way it affects people’s mode choice decisions. This is accomplished by developing discrete choice models and consideration of urban form characteristics at both trip ends. Our findings not only confirmed the important role the built environment plays in influencing mode choice, but also highlighted the influence of policies, such as TOD, at both trip end locations. Results suggest that the probability of choosing transit and non-motorized modes is higher for trips originating and ending in TOD areas. However, the magnitude of this TOD effect is larger at trip origin compared to destination. Higher residential and employment densities at both trips ends are also associated with lower probability of auto and higher probability of transit and non-motorized mode choices.

Unravel the landscape and pulses of cycling activities from a dockless bike-sharing system

The recent boom of sharing economy along with its technological underpinnings have brought new opportunities to urban transport ecosystems. Today, a new mobility option that provides station-less bike rental services is emerging. While previous studies mainly focus on analyzing station-based systems, little is known about how this new mobility service is used in cities. This research proposes an analytical framework to unravel the landscape and pulses of cycling activities from a dockless bike-sharing system. Using a four-month GPS dataset collected from a major bike-sharing operator in Singapore, we reconstruct the temporal usage patterns of shared bikes at different places and apply an eigendecomposition approach to uncover their hidden structures. Several key built environment indicators are then derived and correlated with bicycle usage patterns. According to the analysis results, cycling activities on weekdays possess a variety of temporal profiles at both trip origins and destinations, highlighting substantial variations of bicycle usage across urban locations. Strikingly, a significant proportion of these variations is explained by the cycling activeness in the early morning. On weekends, the overall variations are much smaller, indicating a more uniform distribution of temporal patterns across the city. The correlation analysis reveals the role of shared bikes in facilitating the first- and last-mile trips, while the contribution of the latter (last-mile) is observed to a limited extent. Some built environment indicators, such as residential density, commercial density, and number of road intersections, are correlated with the temporal usage patterns. While others, such as land use mixture and length of cycling path, seem to have less impact. The study demonstrates the effectiveness of eigendecomposition for uncovering the system dynamics. The workflow developed in this research can be applied in other cities to understand this new-generation system as well as the implications for urban design and transport planning.

Visitor Mobility and Spatial Structure in a Local Urban Tourism Destination: GPS Tracking and Network analysis

Visitor mobility is an important element for facilitating sustainable local economics and management in urban tourism destinations. Research on visitor mobility often focuses on the patterns and structures of spatial visitor behavior and the factors that influence them. This study examines the relationship between visitor mobility and urban spatial structures through an exploratory analysis of visitors’ movements and characteristics, which were collected from surveys with global positional system (GPS) tracking technologies and questionnaires. The Ueno district, one of the most popular tourism destinations in Tokyo, Japan, was selected as the study area. For local stakeholders, the low accessibility levels between this district’s park zone and downtown zone have become a major destination management issue. We compared visitor movements and flow networks in various places from different major trip origins (railway stations) by using several analysis techniques (GPS log distribution, spatial movement sequences, and network analysis), and examined physical and human factors that caused the different mobility patterns. The results demonstrated that physical factors, including major transport hubs (railway stations), topography, commercial accumulation, and POI distribution, affected intra-destination visitor behavior, and segmented visitor markets into different main zones. Such findings could inform future destination management policies and planning in local urban tourism destinations.

Urban transportation system design and feasibility analysis: a case study of Lagos Mega-City

This paper examines how urban transportation, urban mobility and urban land Planning at urban Centres influence urban space that serves a variety of human needs; housing, working, social interaction, leisure, and mobility of persons and goods. Transportation and planning are co-dependent, mutually influencing each other in complex and dynamic ways. To create a livable urban environment, there is a need to balance transportation with planning. The skewers of any of these will result in serious environment issues. To identify the role and impact of road transportation in a mega city, the research methodology adopted in this work utilized environmental management system techniques. Key impacts on local community includes exchange of energy, function and maintenance of ordered structures, directly or indirectly supplied and maintained by natural system. Various socio-economic activities and professional judgment from the findings shows that spatial distribution of housing, working, shopping, leisure and other activities determines aver-age trip distances in urban mobility. High population density as well as a mixture of land use for various social and economic activities, maintains low distances between origin and destination of urban trips. It also shows that road development parameters were well within the range of metropolis city, the low density urban development and large road areas increases trip length and lead to higher share of automobile trips. The study recommends that the state government should engaged in traffic management by adjusting the use of existing road system to improve traffic operation with-out resorting to major new constructions, provision of time-based traffic lights, and enforcement of traffic lights and signs, manning of road junctions by traffic wardens, constructing overhead bridges and zebra crossings, encouragement of park and ride system and educating drivers and ensure compulsory written test before the issuance of any driving license. This can be embarked through a technology- supported joint venture that aims to integrate and systematically optimize the State’s intermodal transportation system.

Health screening strategies for international air travelers during an epidemic or pandemic

Air travelers can carry an infectious disease's pathogenic microorganism in their bodies and spread the disease from one country to another in a few days. To delay the spread, health screening stations may be set up at airport terminals to screen travelers. This research tested three different health screening strategies, each with a different combination of screening stations at trip origins, destinations and connecting airports. Discrete event simulations were performed, based on the 2014 to 2016 Ebola virus epidemic, with special focus on travelers from the West African countries traveling to the United States, including travelers who transferred flights at airports in European Union member states. The effectiveness of the screening strategies was analyzed in terms of correct detection, missed detection and false alarm rate. The results showed that exit screening at trip origins brought big improvements in the performance measurements compared to no screening. However, additional screening at the destinations and connecting airports contributed marginal benefits.

Measuring changes in taxi trips near infill development and issues for curbside management of for-hire vehicles

This research examines changes in taxi trip origins and destinations after new multifamily residential buildings opened in New York City. We argue that taxi trips are a reasonable proxy for other for-hire vehicles trips, which are expected to grow in coming years. The analysis contributes to a more nuanced understanding of transportation effects of infill development. Infill developments are typically required to mitigate potential vehicular traffic increases, which are often ill suited to redevelopment of denser, more transit adjacent sites. This research uses geolocated trip data from New York City taxicabs combined with US Census, real estate pricing and tax lot data to develop a baseline understanding of the relationship between trip generation and infill residential development. The objective of this work is twofold. First, establish a measure of taxi activities based on neighborhood and building characteristics to help adapt transportation impact assessments for multimodal travel. Second, through observational data we discuss unique aspects of passenger pick-ups and drop offs as they relate to curb space and street use. Our results show that taxi trip making is positively associated with new residential construction, rental costs and places with high levels of transit usage, and adds demand to congested curb space. Curb space should be considered “wetlands” of urban systems, a poorly understood, yet key, component that connects the flows of traffic and activities in the built environment.

Incorporation of Travel Time Reliability in Regional Travel Model

The paper presents a practical method for incorporation of travel time reliability in a regional travel model. The discussion includes five consecutive steps. First it describes how the vehicle speed dataset for the metropolitan area of Phoenix, AZ, termed HERE, was processed and link-level volume–delay–reliability functions were estimated, and then how link-level reliability measures can be applied for network path building. The third step describes how trip origin–destination (OD) reliability measures can be constructed out of the link-level reliability measures. The fourth step involves implementation of the link-level and OD-level reliability measures in highway assignment, mode choice, and other travel models. The fifth step includes model validation and sensitivity tests. The paper addresses several long-standing issues associated with incorporation of travel time reliability in operational travel models in practice. These issues include construction of OD reliability measures with the recognition that the core link-level reliability measures such as standard deviation or variance are not additive in a general case, accounting for a partial correlation between travel time distributions for different links, and incorporation of travel time reliability in a standard static assignment.

Theoretical substantiation of trip length distribution for home-based work trips in urban transit systems

Modern approaches to the modeling of transport demand imply the use of calibration procedures during the origin-destination (O-D) matrix estimation or transit assignment. These procedures lead to misrepresenting generated and attracted trips or changing the trip length distribution (TLD). It means that the methods of transport planning can be improved by means of determination, validation and implementation of the TLD to calculate the O-D matrix. The analysis of research results in the field of mass transit reveals an explicit similarity between TLD in different cities and the gamma distribution. It points to general regularities in various systems of mass transit that lead to the similarity in TLD. The regularities are determined by studying the spatial distribution of mass transit stops, which are considered trip origins and destinations. The experimental research was conducted in 10 Ukrainian cities using probability theory methods.

Level of service and the transit neighbourhood - Observations from Dublin city and suburbs

Few studies have looked at the impact Level-of-Service (LOS) might have on the distances people walk to public transport. The relationship, if any, has implications for transit-oriented-development and the viability of different transit modes serving suburban areas. This paper examines pedestrian catchment areas and LOS across a light rail, a metro rail and two bus corridors in Dublin. Public transport users have been surveyed at 17 stops around the city and their trip origin identified. Catchment areas for bus services with high levels of service were found to be comparable and often greater than those for LRT or metro rail. 65% of all bus trip-origins are more than 500 m from stops. A standard distance analysis suggests natural catchment limits of over 1400 m for high quality bus, significantly greater than light rail and metro rail of similar service levels. The shape of transit catchment areas are also distinctive and appear to be most influenced by: network density, stopping patterns, urban gravity and quality of service. While further analysis is recommended, public transport users in Dublin city and suburbs appear more influenced by level-of-service than by modal type when deciding how far they are prepared to walk to public transport.

Accessibility to urban services: influence on pedestrian users of public transit

Several studies in the last two decades have investigated the role of built environment on walking. Studies that investigated the role of built environment on walking to transit analyzed the role of various destinations in proximity to the stations. However, few studies have investigated the role of these destinations on walking trip generation at the origin of the trip. Moreover, none of these studies have investigated the role of availability of public services on walking to transit. This study identifies the urban services at the origin of walking trips of the tri-rail commuters in the West Palm, Broward, and Miami-Dade Counties of South Florida. The number of pedestrian users of tri-rail stations and the available urban service were aggregated per Traffic Analysis Zones and analyzed using standard Poisson regression. Findings indicate that availability of urban services such as public education and public recreation have a positive effect on walking to commuter-rail. Implications of this study include the identification and development of Capital Improvement Projects such as libraries to be located in close proximity to schools and colleges. New and proposed train stations should be located in proximity to urban services such as school, colleges, and libraries to encourage pedestrian users.

Trip2Vec: a deep embedding approach for clustering and profiling taxi trip purposes

With the wide availability of GPS trajectory data, sustainable development on understanding travel behaviors has been achieved in recent years. But relatively less attention has been paid to uncovering the trip purposes, i.e., why people make the trips. Unlike to the GPS trajectory data, the trip purposes cannot be easily and directly collected on a large scale, which necessitates the inference of trip purposes automatically. To this end, in this paper, we propose a device-free and novel model called Trip2Vec, which consists of three components. In the first component, it augments the context on trip origins and destinations, respectively, by extracting the information about the nearby point of interest configurations and human activity popularity at particular time periods (i.e., activity period popularity) from two crowdsourced datasets. Such context is well-recognized as the clear clue of trip purposes. In the second component, on the top of the augmented context, a deep embedding approach is developed to get a more semantical and discriminative context representation in the latent space. In the third component, we simply adopt the common clustering algorithm (i.e., K-means) to aggregate trips with similar latent representation, then conduct trip purpose interpretation based on the clustering results, followed by understanding the time-evolving tendency of trip purpose patterns (i.e., profiling) in the city-wide level. Finally, we present extensive experiment results with real-world taxi trajectory and Foursquare check-in data generated in New York City (NYC) to demonstrate the effectiveness of the proposed model, and moreover, the obtained city-wide trip purpose patterns are quite consistent with real situations.

User perspectives on emerging mobility services: Ex post analysis of Kutsuplus pilot

Kutsuplus was a novel, flexible micro transit service (FMTS) operating in Helsinki during 2012 to 2015. The service included a range of new technological development, ranging from routing algorithm to marketing and user interface. However, at the end of 2015, the service ceased due to budgetary constraints. In the context of service discontinuation, and the lack of in-depth understanding of user perspectives about urban FMTS, this paper aims to uncover the perspectives of the users of the service, users that discontinued using the service during its operation, and persons who did not use the service. The methodological approach is based on a questionnaire, with mapping capabilities enabling collection of georeferenced data. Questionnaire results are validated using actual Kutsuplus trip analysis. The results show that Kutsuplus users were a diverse group both when considering socio-economic status and travel behavior. In addition, the results include detailed analysis of stated trip characteristics, including spatial analysis of trip origins and destinations. Furthermore, the results include qualitative analysis of respondents' opinions and recommendations about positive and lacking FMTS features. The paper ends with a summary of positive Kutsuplus features, followed by the discussion of aspects for future deployment, including end-user and service area analysis, marketing strategy, and service usability. Finally, the paper provides recommendations for further research on FMTS.

Evidence of directional price discrimination in the U.S. airline industry

This paper explores possible determinants that may affect an airline’s decision to charge passengers different roundtrip fares depending on trip origin, a case of directional price discrimination. Such fare differences cannot be the result of differences in cost, as the cost of flying a roundtrip passenger does not significantly differ depending on direction. It is argued that directional fare differences result from airlines recognizing that passenger price elasticities differ between route endpoints. A price discriminating airline will then charge a higher roundtrip fare at the endpoint where the passenger price elasticity of demand is comparatively lower. Evidence is found suggesting that airlines do use differences in income to price discriminate when setting roundtrip fares. Fares are found to be $0.18-$0.43 higher on average for each $1000 difference in average per capita income between origin and destination metro areas. This finding is sensible assuming that higher incomes reduce the price elasticity of demand for air travel, with richer passengers being less sensitive to the cost of travel.

Spatial regulation of taxicab services: Measuring empty travel in New York City

Taxicabs are ubiquitous in cities throughout the world, and the industry is going through regulatory change with the growth of app-based services. In the United States, where taxicabs are typically regulated locally, licenses determine where taxis can pick up passengers. This means that for trips that end outside of licensed boundaries taxicabs are prohibited from picking up passengers and are forced to make “deadhead” return trips. This research estimates empty taxi travel associated with spatial restrictions on passenger trip origins in New York City. In 2012, New York introduced a special taxi category intended to improve taxi access in areas of the city considered underserved by taxicabs. The new green taxicabs, as they are called, can drop off passengers anywhere in the city but are restricted from picking up passengers in the central business districts and at any of the region’s airports. Using detailed trip data for each taxi ride, we estimate that up to 500,000 kilometers per week of deadhead travel are associated with restrictions on pick up locations, and more than 20 percent of all green taxicab trips end in an area where the driver is prohibited from picking up a new passenger.

Supervised Land Use Inference from Mobility Patterns

This paper addresses the relationship between land use and mobility patterns. Since each particular zone directly feeds the global mobility once acting as origin of trips and others as destination, both roles are simultaneously used for predicting land uses. Specifically this investigation uses mobility data derived from mobile phones, a technology that emerges as a useful, quick data source on people’s daily mobility, collected during two weeks over the urban area of Malaga (Spain). This allows exploring the relevance of integrating weekday-weekend trip information to better determine the category of land use. First, this work classifies patterns on trips originated and terminated in each zone into groups by means of a clustering approach. Based on identifiable relationships between activity and times when travel peaks appear, a preliminary categorization of uses is provided. Then, both grouping results are used as input variables in a K-nearest neighbors (KNN) classification model to determine the exact land use. The KNN method assumes that the category of an object must be similar to the category of the closest neighbors. After training the models, the findings reveal that this approach provides a precise land use categorization, yielding the best accuracy results for the major categories of land uses in the studied area. Moreover, as a result, the weekend data certainly contributes to finding more precise land uses as those obtained by just weekday data. In particular, the percentage of correctly predicted categories using both weekday and weekend is around 80%, while just weekday data reach 67%. The comparison with actual land uses also demonstrates that this approach is able to provide useful information, identifying zones with a specific clear dominant use (residential, industrial, and commercial), as well as multiactivity zones (mixed). This fact is especially useful in the context of urban environments where multiple activities coexist.

Relationship between train users’ perceptions of walkability with access and egress mode choice

The purpose of this study is to understand whether there is a relationship between train users’ perceptions of walkability in built environment of trip origin with access mode choice and between train users’ perceptions of walkability in built environment of trip destination with egress mode choice. Train users are who ride from Cicalengka station Bandung Regency, West Java, Indonesia. To analyze the relationship is used crosstab method. The perceptual factors about walkability are those perceived by the train users consisting of walking distance, safety, comfort, and secure from crime, both in origin and destination of the built environment. The mode choice consist of walking, paratransit, motorcycle taxi, and own vehicles (or others for egress mode). To better understand the relationship is used several control variables, that are trip purposes, train usage, gender, and age. For access trip there is another control variable, that is vehicle ownership. Train users' perceptions of walkability have a relationship with both the access and the egress mode choice, except for the security aspect. The influence of control variables on the relationship between perceptions of walkability with access/egress mode choice varies for walking distance, safety, and comfort.

Analysis of potential diverted of passenger car to the new toll road (case study: Cileunyi – Sumedang, West Java)

This study aims to determine of potential of passenger car divert from national road to on-construction Cisumdawu Toll Road. The study was conducted by traffic count survey and followed by a roadside interview survey. Stated Preference method was used in order to analyse trip forecasting value. Mode choice model of new trip mode plans (Cisumdawu Toll Road) and current intercity road for Cileunyi – Sumedang is (UJT–UJR) = 0.1079–0.507726x1–0.8953764x2, while Sumedang – Cileunyi is (UJT–UJR) = 0.0790–0.301341x1–0.548446x2. Multiple linear regression analysis was used to obtain the forecasting of private vehicle that diverts to the new toll road (Cisumdawu Toll Road). Trip characteristics such as trip origin and destination, types of trips, occupations, salary, and others become a motive for respondents to choose a new trip mode. Results of the new trip mode forecasting that prefer to divert to the toll road in terms of the value of cost and time for Cileunyi – Sumedang are 74.11% and 86.62% respectively, while for Sumedang – Cileunyi are 69.60% and 76.48% respectively. These results are relatively high compare to toll planning document. The impact of this results can be determined such as lower overall fuel consumption, lower pollution and more important is the maintenance cost of national road will be decrease.

Designing healthy communities: creating evidence on metrics for built environment features associated with walkable neighbourhood activity centres

BackgroundEvidence-based metrics are needed to inform urban policy to create healthy walkable communities. Most active living research has developed metrics of the environment around residential addresses, ignoring other important walking locations. Therefore, this study examined: metrics for built environment features surrounding local shopping centres, (known in Melbourne, Australia as neighbourhood activity centres (NACs) which are typically anchored by a supermarket); the association between NACs and transport walking; and, policy compliance for supermarket provision.MethodsIn this observational study, cluster analysis was used to categorize 534 NACs in Melbourne, Australia by their built environment features. The NACS were linked to eligible Victorian Integrated Survey of Travel Activity 2009-2010 (VISTA) survey participants (n=19,984). Adjusted multilevel logistic regressions estimated associations between each cluster typology and two outcomes of daily walking: any transport walking; and, any ‘neighbourhood’ transport walking. Distance between residential dwellings and closest NAC was assessed to evaluate compliance with local planning policy on supermarket locations.ResultsMetrics for 19 built environment features were estimated and three NAC clusters associated with walkability were identified. NACs with significantly higher street connectivity (mean:161, SD:20), destination diversity (mean:16, SD:0.4); and net residential density (mean:77, SD:65) were interpreted as being ‘highly walkable’ when compared with ‘low walkable’ NACs, which had lower street connectivity (mean:57, SD:15); destination diversity (mean:11, SD:3); and net residential density (mean:10, SD:3). The odds of any daily transport walking was 5.85 times higher (95% CI: 4.22, 8.11), and for any ‘neighborhood’ transport walking 8.66 (95% CI: 5.89, 12.72) times higher, for residents whose closest NAC was highly walkable compared with those living near low walkable NACs. Only highly walkable NACs met the policy requirement that residents live within 1km of a local supermarket.ConclusionsBuilt environment features surrounding NACs must reach certain levels to encourage walking and deliver walkable communities. Research and metrics about the type and quantity of built environment features around both walking trip origins and destinations is needed to inform urban planning policies and urban design guidelines.

Development of railway station choice models to improve the representation of station catchments in rail demand models

ABSTRACTThis paper describes the development of railway station choice models suitable for defining probabilistic station catchments. These catchments can then be incorporated into the aggregate demand models typically used to forecast demand for new rail stations. Revealed preference passenger survey data obtained from the Welsh and Scottish Governments was used for model calibration. Techniques were developed to identify trip origins and destinations from incomplete address information and to automatically validate reported trips. A bespoke trip planner was used to derive mode-specific station access variables and train leg measures. The results from a number of multinomial logit and random parameter (mixed) logit models are presented and their predictive performance assessed. The models were found to have substantially superior predictive accuracy compared to the base model (which assumes the nearest station has a probability of one), indicating that their incorporation into passenger demand forecasting methods has the potential to significantly improve model predictive performance.

The "Residential" Effect Fallacy in Neighborhood and Health Studies: Formal Definition, Empirical Identification, and Correction.

Because of confounding from the urban/rural and socioeconomic organizations of territories and resulting correlation between residential and nonresidential exposures, classically estimated residential neighborhood-outcome associations capture nonresidential environment effects, overestimating residential intervention effects. Our study diagnosed and corrected this "residential" effect fallacy bias applicable to a large fraction of neighborhood and health studies. Our empirical application investigated the effect that hypothetical interventions raising the residential number of services would have on the probability that a trip is walked. Using global positioning systems tracking and mobility surveys over 7 days (227 participants and 7440 trips), we employed a multilevel linear probability model to estimate the trip-level association between residential number of services and walking to derive a naïve intervention effect estimate and a corrected model accounting for numbers of services at the residence, trip origin, and trip destination to determine a corrected intervention effect estimate (true effect conditional on assumptions). There was a strong correlation in service densities between the residential neighborhood and nonresidential places. From the naïve model, hypothetical interventions raising the residential number of services to 200, 500, and 1000 were associated with an increase by 0.020, 0.055, and 0.109 of the probability of walking in the intervention groups. Corrected estimates were of 0.007, 0.019, and 0.039. Thus, naïve estimates were overestimated by multiplicative factors of 3.0, 2.9, and 2.8. Commonly estimated residential intervention-outcome associations substantially overestimate true effects. Our somewhat paradoxical conclusion is that to estimate residential effects, investigators critically need information on nonresidential places visited.