The demand for reliable transit service: New evidence using stop level data from the Los Angeles Metro bus system

This study explores the role of service reliability in determining bus transit ridership. Using stop level service supply, demand, and performance data from the Los Angeles Metro bus system, I investigate whether reliability of a directional line serving a stop influences the number of passengers boarding the line at that stop, controlling for various other established factors affecting demand. This cross-sectional analysis of the variation in line boardings across about 1300 sample schedule time point bus stops served by about 300 directional bus lines over a six-month period uses a historical archive of real-time geo-referenced vehicle location data, and focuses on five different time periods, peaks and off-peaks, of a typical weekday. By evaluating two measures that capture different dimensions of bus service reliability, and by estimating a series of regression models, I find systematic evidence that higher average service punctuality (or schedule adherence) and lower variation in schedule deviation over time are associated with greater ridership, all else equal, particularly during the peak periods. This study also provides first empirical evidence that the effect of reliability on peak-period ridership is moderated by headway. The demand for reliability seems to be higher for lines with relatively longer headways. The findings indicate that service reliability influences transit mode choice and/or line/route selection, and suggest that system-wide ridership gains can be expected from reliability improvements. From an urban planning perspective, this study provides more evidence that good service quality can effectively compliment transformations in the urban fabric brought about by coordinated land use — transit plans to promote transit use.     

Exploratory data analysis of activity diary data: a space-time GIS approach

Study of human activities in space and time has been an important research topic in transportation research. Limitations of conventional statistical methods for analysis of individual-level human activities have encouraged spatiotemporal analysis of human activity patterns in a space-time context. Based on Hägerstrand’s time geography, this study presents a space-time GIS approach that is capable of representing and analyzing spatiotemporal activity data at the individual level. Specifically, we have developed an ArcGIS extension, named Activity Pattern Analyst (APA), to facilitate exploratory analysis of activity diary data. This extension covers a set of functions such as space-time path generation, space-time path segmentation, space-time path filter, and activity distribution/density pattern exploration. It also provides a space-time path based multi-level clustering method to investigate individual-level spatiotemporal patterns. Using an activity diary dataset collected in Beijing, China, this paper presents how this Activity Pattern Analyst extension can facilitate exploratory analysis of individual activity diary data to uncover spatiotemporal patterns of individual activities.     

Cost structures of public transit systems: a panel data analysis

Results from numerous cost studies have generated conflicting results on public transit production technologies. Because prior studies have employed various sub-samples of public transit properties, the diverse results may either reflect alternative technologies or sampling differences. Based on a panel of nearly all transit systems reporting for Section 15 (US National Transit Data) purposes from 1986 to 1994, this paper explores whether public transit production technology differs by size and operating characteristics of the system. The results indicate that US transit properties are heterogeneous with different production technologies, which implies that transit cost analyses based upon a set of heterogeneous systems will generate incorrect inferences on public transit cost and production structures.     

The working poor and what GIS reveals about the possibilities of public transit

This study uses GIS to examine the constrained daily geographies of working poor women in order to assist transportation planners in understanding underserved populations and identifying gaps in transit service. Through interviews and travel diaries, I have uncovered constraints on daily travel in a sprawling, medium-size American city (Knoxville, Tennessee). This study undermines the too-optimistic assumptions generated by analyses of aggregate-level data, in that the transition from welfare to work will not be as smooth, nor as uniform, as aggregate data indicate. Based on this research, I recommend increased investment in car ownership and related assistance. Access to cars will not only increase working poor women’s daily mobilities, but also their job opportunities, overall earnings, and – ultimately – their successful and permanent transitions from welfare to sufficient and satisfying work.     

Promises and problems: using GIS to analyse shopping travel

Geographical Information Systems enable spatial analysis of a scale and nature that has never been possible before. However, their practical utilisation in transport research remains limited. This paper describes the specific experience of using the TransCAD GIS to assess different ways of organising food shopping. It concentrates on the role played by the GIS. In doing so, it aims to highlight many general problems that limit the scope of GIS use, as well as the benefits of such systems, and the broader issues which affect research based on GIS. It concludes with recommendations for greater compatibility, standardisation and reliability for both GIS and GIS data, to encourage their use in the future.     

Measuring transit oriented development: a spatial multi criteria assessment approach for the City Region Arnhem and Nijmegen

Transit Oriented Development (TOD) is a planning approach that can stimulate sustainable development by encouraging better land use and transport integration. Arnhem Nijmegen City Region, a regional planning body, in the Netherlands, aims to promote sustainable development in their region and control the current pattern of increased use of cars vis-à-vis transit for longer commutes. Planning for TOD can help achieve this aim. It is believed that measuring the existing levels of TOD is a prerequisite for TOD planning and that it can be done using a TOD Index proposed in this research. A TOD Index measures multiple spatial indicators and aggregates them under the SMCA framework to arrive at a comprehensive value depicting the existing levels of TOD at a location or an area. Using this TOD Index, TOD levels were measured over the entire City Region covering approx. 1000 km². High levels of TOD imply that the urban development’s characteristics, at that location, are ripe for use of transit and these high levels, as expected, were found in the urban areas of Arnhem and Nijmegen. From the results of TOD Index measurement, using hot-spot analysis, those locations were identified that have high TOD levels but poor transit connectivity. These locations are accordingly recommended for better transit connectivity. As a part of our future work, it is intended to use the TOD Index to elevate TOD levels around existing transit nodes.     

Exploring the spatial impacts of human activities on urban traffic crashes using multi-source big data

Traffic crashes are geographical events, and their spatial patterns are strongly linked to the regional characteristics of road network, sociodemography, and human activities. Different human activities may have different impacts on traffic exposures, traffic conflicts and speeds in different transportation geographic areas, and accordingly generate different traffic safety outcomes. Most previous researches have concentrated on exploring the impacts of various road network attributes and sociodemographic characteristics on crash occurrence. However, the spatial impacts of human activities on traffic crashes are unclear. To fill this gap, this study attempts to investigate how human activities contribute to the spatial pattern of the traffic crashes in urban areas by leveraging multi-source big data. Three kinds of big data sources are used to collect human activities from the New York City. Then, all the collected data are aggregated into regional level (ZIP Code Tabulation Areas). Geographically Weighted Poisson Regression (GWPR) method is applied to identify the relationship between various influencing factors and regional crash frequency. The results reveal that human activity variables from multi-source big data significantly affect the spatial pattern of traffic crashes, which may bring new insights for roadway safety analyses. Comparative analyses are further performed for comparing the GWPR models which consider human activity variables from different big data sources. The results of comparative analyses suggest that multiple big data sources could complement with each other in the coverage of spatial areas and user groups, thereby improving the performance of zone-level crash models and fully unveiling the spatial impacts of human activities on traffic crashes in urban areas. The results of this study could help transportation authorities better identify high-risky regions and develop proactive countermeasures to effectively reduce crashes in these regions.     

Perceived accessibility: What it is and why it differs from calculated accessibility measures based on spatial data

Accessibility is usually evaluated using indicators calculated from spatial data. However, perceived accessibility, defined as the perceived potential to participate in spatially dispersed opportunities, is often poorly reflected by these calculated measures. This paper sets out to explain the mechanisms that lead to these mismatches. A conceptual model is constructed to establish what factors shape perceived accessibility. A schematic framework shows that mismatches between a calculated indicator and perceptions can stem from inaccuracies in awareness as well as from inaccuracies in the measure if the measure fails to take account of the subjective evaluations of accessibility components. When evaluating the performance of land-use and transport system configurations, calculated measures based on spatial and transport data only serve as proxies for how accessibility is actually experienced. This paper argues that bringing perceived accessibility to the fore of accessibility-based planning, by acknowledging and evaluating potential mismatches with calculated accessibility indicators, will advance the evolution from mobility-based to accessibility-based planning.     

Using accessibility indicators and GIS to assess spatial spillovers of transport infrastructure investment

This paper proposes a methodology to measure spatial spillovers of transport infrastructure investment and to monetize them by distributing the costs of the infrastructures envisaged according to the regional distribution of the potential accessibility benefits. We use a transport master plan (the Spanish “Plan Estratégico de Infraestructuras y Transporte” 2005–2020, PEIT) as a case study for applying our methodology. In order to calculate and map regional spillovers, economic potential values are computed using network routines in a Geographic Information System (GIS) by comparing two scenarios: firstly, the scenario PEIT 2020; and secondly the scenario which includes the improvements envisaged for the year 2020 in all the regions except the region whose spillover effects are being analyzed. The differences between these two scenarios represent the potential spatial spillover effects of this region on the rest of the regions. This procedure is repeated for each of the Spanish regions in order to calculate a matrix of inter-regional spillovers in economic potential units. In a second step, this matrix is monetized by distributing the costs of the investment in infrastructures envisaged in the region according to the regional distribution of the economic potential benefits. This inter-regional matrix of investments flows characterizes the “inner”, “export”, and “import” values of each of the regional road investments. Subtracting from the direct investment the exports to other regions and adding the imports from other regions, an estimation of the real investment of the plan in each region taking into account all the spillover effects is obtained. This value can be compared with the direct investment in the region, analyzing whether one region has more or less direct investment than real. The proposed methodology makes it transparent which regions benefit more from national transport investment irrespective of where the investment occurs. The spillover matrix can be a valid instrument, especially in federal states or in the case of transnational projects, in the field of regional economics because it offers very useful information for both planners and policy makers.     

Integrated land use and transportation interaction: a temporal GIS exploratory data analysis approach

Land use and transportation interaction is a complex, dynamic process. Many models have been used to study this interaction process during the past several decades. Empirical studies suggest that land use and transportation interaction patterns can be highly variable between geographic areas and at different spatial and temporal scales. This paper presents a temporal geographic information systems (GIS) design that offers exploratory data analysis capabilities to interactively examine land use and transportation interaction at user-specified spatial and temporal scales. A spatiotemporal interaction framework, implemented with temporal GIS databases, provides a foundation for the development of spatiotemporal analysis functions to systematically explore land use and transportation interaction.     

Combined impacts of highways and light rail transit on residential property values: a spatial hedonic price model for Phoenix,Arizona

This study analyzes the positive and negative relationships between housing prices and proximity to light rail and highways in Phoenix, Arizona. We hypothesize that the accessibility benefits of light rail transit (LRT) and highways accrue at nodes (stations and highway exits specifically), while disamenities emanate from rail and highway links as well as from nodes. Distance decay of amenities and disamenities is captured using multiple distance bands, and hypotheses are tested using a spatial hedonic model using generalized spatial two-stage least-squares estimation. Results show that proximity to transport nodes was associated significantly and positively with single-family detached home values. As a function of distance from highway exits and LRT stations, the distance-band coefficients form an inverted-U pattern consistent with a positive longer-range distance–decay accessibility effect minus a smaller and shorter-range distance–decay disamenity effect. The positive accessibility effect for highway exits extends farther than for LRT stations. Coefficients for the distance from highway and LRT links, however, were not significant. We also test the effect of highway design on home values and find that below-grade highways have relatively positive impacts on nearby houses compared to those at ground level or above.     

Evaluating the European added value of TEN-T projects: a methodological proposal based on spatial spillovers, accessibility and GIS

This paper develops a methodology for calculating the European value added value (EVA) generated by transport infrastructure projects. This approach is particularly useful for evaluating projects in the framework of Trans-European Transport Networks (TEN-T), although it may also be used in trans-national projects in other geographical areas. The methodology is based on the appraisal of spatial spillovers generated by trans-national projects by using accessibility indicators (access to markets) and Geographical Information Systems (GIS). Projects are split into sections and spillover effects of each section are then computed. The sections that produce a high proportion of spillovers in relation to internal benefits generate a high EVA. Additionally, indicators are obtained of the effects of each section in terms of spatial concentration on the different countries affected, efficiency (general improvement in accessibility) and territorial cohesion (reduction in accessibility disparities between regions). The validity of this approach is verified by applying it to TEN-T priority project 25. This methodology does not seek to replace existing project appraisal methodologies (particularly the cost-benefit analysis); rather it provides complementary data for decision-making. Sections which are scarcely profitable from the cost-benefit analysis perspective but which have high European value added should receive more European funding than more profitable sections of markedly national interest.     

Profiling road transport activity: Emissions from 2000 to 2005 in Ireland using national car test data

This work describes a methodology for determining the average vehicle kilometres travelled by the private national car fleet in Ireland and estimating the disaggregated CO₂ and NO_x emissions from private vehicles in the Irish road transport sector for the period 2000–2005 using national car test records. The developed methodology facilitates the calculation of greatly improved estimates for vehicle kilometres under a range of constraint variables and thereby enables the disaggregated analysis of specific vehicle fleet groups and their associated activity patterns to support evidence-based policy development. The results indicate that while older vehicles are contributing significantly to car NO_x emissions; newer cars produce a higher share of CO₂ emissions than older cars in the vehicle fleet.     

Traffic incidents in motorways: An empirical proposal for incident detection using data from mobile phone operators

This paper proves that mobile phone usage data is an easy to use, cheap and most importantly, reliable predictor of motorway incidents. Using econometric modelling, this paper provides a proof of concept of how mobile phone usage data can be utilised to detect motorway incidents. Greater Amsterdam is used here as a case study and the results suggest that mobile phone usage data can be utilised for the development of an early warning system to support road traffic incident management.     

Calculating load factors for the transatlantic airline market using supply and demand data – A note on the identification of gaps in the available airline statistics

This paper takes a critical view of the verification of load factors for the direct transatlantic airline market by combining supply and demand-data. The supply-related data originate from the Official Airline Guide, a well-known data source that contains information on scheduled flights. The demand-related data originate from the Marketing Information Data Transfer database, a data set containing information on actual airline bookings. Combining both data sets enables us to calculate the seat occupancy of direct flights between North-West Europe and the US for 2001. Based on the results, we assess the utility of the joint use of these data sources for aviation economic research, and identify various gaps in the available airline statistics.     

The spatial characteristics of inland transport hubs: evidences from Southern India

This paper investigates the spatial characteristics of inland transport hubs with evidence from the users’ choice of dry ports in cargo exportation in Southern India. The findings indicate that the current solution, where shippers often choose dry ports located closest to their production base, is not the optimal solution in terms of the minimisation of transport cost, mainly due to government policies and dry port’s inability in providing value-added services to shippers. This study provides important insight on the major attributes in explaining the spatial characteristics of inland transport hubs, especially in developing countries.     

Urban rail transit PPPs: Survey and risk assessment of recent strategies

The proliferation of urban rail transit public–private partnerships (PPPs) in Latin America and Southeast Asia is a recent phenomenon. This paper first reviews the theoretical literature on the public procurement versus PPP decision in the context of rail transit and assesses the risks involved in entering these partnerships. The urban rail transit PPP approaches adopted in Bangkok, Kuala Lumpur, Buenos Aires, Rio de Janeiro, Singapore, Hong Kong, and London are described and classified into four broad approaches: (i) the development of new systems through Design-Build-Finance-Operate (DBFO), (ii) the concessioning of rail and subway services, (iii) the sale of state-owned operators through share issue privatization, and (iv) PPPs for infrastructure maintenance and upgrading. The different risk allocation strategies adopted under each of the above approach are analyzed for the extent to which they correspond to the theoretical recommendations. The concluding section provides a summary of the trade-offs that policy makers make when deciding between alternative strategies.     

Examining commuting patterns using Floating Car Data and circular statistics: Exploring the use of new methods and visualizations to study travel times

In this paper, we focus on the spatial distribution of travel time differences between car and public transport during peak and off-peak hours using geospatial methods and circular statistics. To that end, we combine two origin-destination matrices: one contains the number of simulated commuting trips and the other contains accurate travel times measured using either Floating Car Data or transit data. The combination of both matrices reveals that differences in travel time during peak and off-peak hours are high for intra-city commuting and low for inter-city commuting.     

Discovering temporal and spatial patterns and characteristics of pavement distress condition data on major corridors in New Mexico

Roadway networks, as part of transportation infrastructure, play an indispensable role in regional economies and community development. The high-quality pavement serviceability of these networks is essential to ensure safe, cost-effective daily traffic operations. In-depth analyses of network-wide pavement surface condition data are necessary inputs for optimal pavement design and maintenance, traffic safety enhancement, and sustainable traffic infrastructure system development. This study aims to investigate various pavement distress condition performance measurements and their correlations to better understand temporal–spatial characteristics of roadway distress based on pavement distress condition data collected in New Mexico from 2006 to 2009. Eight major corridors across various urban and rural areas were selected for analyzing pavement surface-distress conditions and discovering their intrinsic characteristics and patterns across both temporal and spatial domains. The results show that there are not strong correlations among different distress measurements, implying the rationality of the current pavement performance measurement protocol used by the state transportation agencies. Regression models were established and GIS-based spatial analyses were performed to extract temporal and spatial patterns of Distress Rate (DR) data. The model results illustrate significant correlations of the DR data on the same route between two consecutive years, which can be partially characterized by a Markov process. GIS-based spatial investigations also show unique features of pavement condition deterioration attributed to diverse geometric characteristics and traffic conditions, such as vehicle compositions and volumes and urban and rural areas. The research findings are helpful to understand the characteristics of pavement distress conditions more clearly and to optimize traffic infrastructure design and maintenance.