Spatio-temporal analysis of rail station ridership determinants in the built environment

The development of new routes and stations, as well as changes in land use, can have significant impacts on public transit ridership. Thus, transport departments and governments should seek to determine the level and spatio-temporal dependency of these impacts with the aim of adjusting services or improving planning. However, existing studies primarily focus on predicting ridership, and pay relatively little attention to analyzing the determinants of ridership from temporal and spatial perspectives. Consequently, no comprehensive cognition of the spatio-temporal relationship between station ridership and the built environment can be obtained from previous models, which makes them unable to facilitate the optimization of transportation demands and services. To rectify this problem, we have employed a Bayesian negative binomial regression model to identify the significant impact factors associated with entry/exit ridership at different periods of the day. Based on this model, we formulated geographically weighted models to analyze the spatial dependency of these impacts over different periods. The spatio-temporal relationship between station ridership and the built environment was analyzed using data from Beijing. The results reveal that the temporal impacts of most ridership determinants are related to the passenger trip patterns. Furthermore, the spatial impacts correspond with the determinants’ spatial distribution, and the results give some implications on urban and transportation planning. This analysis gives a common analytical framework analyzing impacts of urban characteristics on ridership, and extending researches on how we capture the impacts of urban and other factors on ridership from a comprehensive perspective.

     

Preliminary results of an analysis of areas of influence in Shanghai

The main deficiency of most current modeling approaches to transportation can be identified as neglect of the integration of existing geographical knowledge in regard to the ex ante transport/land use modeling approaches, with its focus on territorial dynamics and theory development. This paper addresses this aspect of the problem by introducing a theoretical and methodological framework for the analysis of the interrelationship between land uses. The analysis attempts to determine to what extent the functional land use in a city can be considered an ordered pattern. The order sought does not rely on purely spatial configurations, but on the correlation of transportation and land use. The first section of this paper focuses on theoretical considerations. It stresses the fact that conventional approaches do not apply in the present context. It then suggests an alternative based on areas of influence and measured in terms of level of attractance of land uses. The second describes a procedure based on this alternative following the remarkable contribution of Hanjoul, Beguin and Thill. An application of this procedure to the analysis of Shanghai is then examined. Finally, an evaluation of the strategies for optimizing the interrelationship between land uses is presented. The paper concludes with a possible research agenda.     

The impact of transit station areas on the travel behaviors of workers in Denver,Colorado

Transit development is one planning strategy that seeks to partially overcome limitations of low-density single use car oriented development styles. While many studies focus on how residential proximity to transit influences the travel behaviors of individuals, the effect of workplace proximity to transit is less understood. This paper asks, does working near a light rail transit station influence the travel behaviors of workers differently than workers living near a station? We begin by examining workers’ commute mode based on their residential and workplace proximity to transit station areas. Next, we analyze the ways in which personal travel behaviors differ between those who drive to work and those who do not. The data came from a 2009 travel behavior survey in the Denver, Colorado metropolitan area, which contains 8000 households, 16,000 individuals, and nearly 80,000 trips. We measure sustainable travel behaviors as reduced mileage, reduced number of trips, and increased use of non-car transportation. The results of this study indicate that living near a transit station area by itself does not increase the likelihood of using non-car modes for work commutes. But if the destination (work) is near a transit station area, persons are less likely to drive a car to work. People who both live and work in a transit station area are less likely to use a car and more likely to take non-car modes for both work and non-work (personal) trips. Especially for persons who work near a transit station area, the measures of personal trips and distances show a higher level of mobility for non-car commuters than car commuters – that is, more trips and more distant trips. The use of non-car modes for personal trips is most likely to occur by non-car commuters, regardless of their transit station area relationship.     

The Bid-rent Land Use Model of the simple,efficient, elegant,and effective model of land use and transportation

Integrated land use/transportation forecasting models add significant policy and infrastructure alternatives analysis capabilities to the urban planning process. The financial, time, and staff requirements to develop these models has put them beyond the reach of most small to medium sized urban areas. This paper presents the land use allocation submodel of the Simple, Efficient, Elegant, and Effective model of land use and transportation (SE³M), an integrated land use and transportation forecasting model founded upon Economic Base Theory and Bid-rent Theory. The Bid-rent Land Use Model (BLUM) is an agent based, spatial competition model utilizing unique utility curves for willingness to pay and incomes for budget constrained abilities to pay for each agent. The model structure, estimation, calibration, implementation, and validation are presented. With a single year of land use data available, the validation approach used the Kappa Index of Agreement to spatially check model outputs against base year control data while controlling for agreement by chance. The U.S. territory of Guam is used as the case study/proof of concept implementation for this model framework. Once calibrated, BLUM could solve the spatial competition problem on Guam in less than two minutes of processing time with over 90% accuracy.     

Estimating bike-share trips using station level data

Bicycle sharing systems (BSS) have increased in number rapidly since 2007. The potential benefits of BSS, mainly sustainability, health and equity, have encouraged their adoption through support and promotion by mayors in Europe and North America alike. In most cases municipal governments desire their BSS to be successful and, with few exceptions, state them as being so. New technological improvements have dramatically simplified the use and enforcement of bicycle return, resulting in the widespread adoption of BSS. Unfortunately little evaluation of the effectiveness of differently distributed and managed BSS has taken place. Comparing BSS systems quantitatively is challenging due to the limited data made available. The metrics of success presented by municipalities are often too general or incomparable to others making relative evaluations of BSS success arduous. This paper presents multiple methodologies allowing the estimation of the number of daily trips, the most significant measure of BSS usage, based on data that is commonly available, the number of bicycles available at a station over time. Results provide model coefficients as well as trip count estimates for select cities. Of four spatial and temporal aggregate models the day level aggregation is found to be most effective for estimation. In addition to trip estimation this work provides a rigorous formalization of station level data and the ability to distinguish spatio-temporal rebalancing quantities as well as new characteristics of BSS station use.     

Appraising large-scale investments in a metropolitan transportation system

A package of large-scale investments in the transportation infrastructure in the Stockholm metropolitan region is currently being proposed. It contains new investments in the railway and subway systems as well as new links in the road system. This paper deals with the issue of appraising this kind of investment program. One major problem is the lack of a unique standard method, and it is argued that several tools should be used in a practical evaluation of large-scale investments in the transportation system.Four different approaches are presented and related to each other. First, one study uses a network-based mode-split/assignment model with a fixed trip matrix. The second study is complementary, as its aim is to also trace the impacts on the spatial distribution of population and jobs by applying an integrated transportation and land use model. Third, the long-run effects of the investments on regional economic growth are discussed within the framework of regional production functions. Fourth, an alternative approach is used, in which benefits from the investments are assessed through their estimated influence on aggregate land values.Abbreviations RA Reference Alternative - IP Investment Proposal - IMREL Integrated Model of Residential and Employment Location - RPFM Regional Production Function Model An earlier version of this paper was presented at the 31th European Congress of the Regional Science Association, Lisbon, August 1991.     

Land use around suburban transit stations

Land use change in some form is cited by both supporters and critics of rapid transit deployment. This paper examines and categorizes land use around twenty stations located in suburban Washington, D.C. and San Francisco/Oakland through the use of aerial photographs and field investigations. As a case study of local economic development, it documents the land use pattern associated with two modern heavy rail, rapid transit networks — BART and METRO.Both BART and METRO impact land use around suburban stations. The primary contributors to station area development are residential and commercial developers in addition to the transportation providers themselves. The trend toward more intense development away from the regional CBD toward suburban station areas indicates a wave of influence moving into the hinterland via transit lines. While trends of land use are apparent, individual station areas seem to be dictated by local conditions such as markets, land use restrictions, accessibility, population, and physical geography.     

Hierarchal assessment of noise pollution in urban areas – A case study

Noise pollution in urban areas has many harmful effects on the citizens. There are varieties of noise generation sources of which the traffic noise could be a major source. The point which is perhaps less noticed is that sound level is not the only parameter to indicate the extent and intensity of noise pollution. Situation of urban land uses, distribution of population centers and types of passages can deeply affect the concern on this environmental issue but not with a similar ratio. This article presents an overlaying technique to define noise prone areas using all different factors involved. A case study was carried out in the District 14 of Tehran Metropolitan City where there are busy streets and highways. For this purpose, the share of each criterion in noise pollution intensity was determined using Analytical Hierarchy Process (AHP). Afterwards, the map layers were overlaid based upon the relative importance of the criteria to get the final map on which the noise prone areas are specified. The developed method could be used as a tool for indirect estimation of noise pollution by which instead of direct measurement of the equivalent sound level, it would be possible to predict noise susceptible areas considering the most important influential factors.     

Measuring the completeness of complete streets

A tool for measuring the “completeness” of a complete street has applications in developing policy, prioritising areas for infrastructure investment for a network, and solving the right-of-way allocation problem for individual streets. A literature review was conducted on the state-of-art in the assessment complete street designs. Complete streets assessment requires a context-sensitive approach, thus context-sensitive standards of “completeness” must first be established by combining a street classification system with sets of priorities and target performance levels for the different types of streets. Performance standards should address a street’s fulfilment of the movement, environmental, and place functions, and be flexible enough to account for the many ways that these functions of a street can be fulfilled. Most frameworks reviewed are unsuitable for evaluating complete streets because, with few exceptions, they guide street design by specifying the design elements for inclusion on the street. Secondly, the performance of a street can be assessed according to transportation, environmental, and place criteria, and compared to the target performance levels specified by the street’s classification. As there are many different impacts to consider on a street, additional work is required to define the priorities and performance objectives for different types of streets.     

A new method for evaluation of level of service in pedestrian facilities

Safe and comfortable walking is essential for pedestrian movement in modern urban transportation systems. Since pedestrian traffic cannot be restricted in some specified streets, some measures for pedestrians have to be taken everywhere in urban areas. This research describes a way to evaluate ordinary sidewalks, and two different methods are proposed. One is an evaluation based on pedestrian behaviour and the other is an evaluation based on pedestrian opinion. Using the indices of pedestrian density and sidewalk width, we can estimate the level of service of sidewalk usage. But generally speaking, since it is not often that a sidewalk is insufficient to deal with pedestrian flow, another approach is necessary for its evaluation, that is, pedestrian awareness of sidewalks must be taken into account. The former method is recommended for all sidewalks, especially with comparatively heavy pedestrian traffic, and the latter method is recommended for ones with light pedestrian traffic.     

Transit oriented development and retail: Is variation in success explained by a gap between theory and practice?

Central to the concept of Transit Oriented Development (TOD) is a retail core situated around stations. However, successful retail near light rail transit stations has been elusive. Despite significant implications for land use, transportation, and economic development planning, little research exists to explain the gap between TOD concept and reality. We hypothesize that the density, diversity, and design characteristics central to the theory of TODs drive retail success. We implement a TOD Index proposed in the literature to score 474 light rail station areas in 11 metropolitan areas according to the presence and magnitude of those density, diversity, and design characteristics. A series of robustly-developed multilevel models support our hypothesis: TOD Index scores significantly predict station area retail employment, ceteris paribus. An evaluation of its subcomponents individually (block size, which relates to walkability; land use mix; and activity density) suggests activity density may be the driving force in this relationship. Our research works to move the conversation away from an assumption that transit stations and retail naturally co-exist and toward more intentional station area design choices demonstrated to drive retail employment.     

Conflict-minimising traffic patterns: A graph-theoretic approach to efficient traffic circulation in urban areas

The paths followed by vehicles in urban areas are densely interwoven, and some of the accidents and congestion that occur in city centres can be attributed to the ‘conflicts’ that arise where these paths intersect. Hence, it is desirable to encourage traffic patterns in which the frequency and severity of conflicts are minimised. At present, neither signal optimisation programs nor traffic simulation programs allow the user to experiment freely with different combinations of one-way streets and turn restrictions, which might otherwise help to disentangle conflicting movements. There is no accepted formula or philosophy for organising traffic into a coherent spatial pattern. The aim of this paper is to consider some idealised networks and circulation systems that have simple geometrical configurations, and to identify those systems that are relatively efficient in terms of path crossings, as compared with a theoretical yardstick derived from graph theory. The results provide some pointers towards a general strategy for efficient traffic circulation in urban areas.     

Incorporating land use in metropolitan transportation planning

In current practice, very few Metropolitan Planning Agencies attempt to capture the effects of transportation system changes on land use, and the consequent feedback effects on transportation system performance, despite substantial evidence that these effects may be significant. In this paper, we present a case study on the application of UrbanSim, a detailed land use simulation model system, and its integration with a regional travel demand model in the Greater Wasatch Front area of Utah. Like several other metropolitan areas, this region has recently been confronted with legal challenges to proposed highway projects, drawing substantial scrutiny to the land use-transportation connection. We describe the UrbanSim model specification, results from model estimation, and sensitivity analyses conducted with the combined land use and travel model system. The results of the sensitivity analysis suggest that accounting for the land use effects of a regional transportation plan may produce significant shifts in key transportation evaluation measures such as vehicle miles traveled, vehicle hours traveled, and hours of congestion delay.     

The transportation systems of Buenos Aires, Chicago and São Paulo: City centers, infrastructure and policy analysis

We compare the passenger transportation systems of Buenos Aires, Chicago and São Paulo. The selected cities represent distinctive combinations of land-use, infrastructure, and evolution of transport policy. Analysis is centered on accessibility to downtown areas, where transportation processes converge in an environment where space is scarce. In two of the three cities institutional arrays that legally establish unified decision making have shown little capacity to launch fare or physical coordination between modes. In two of the three cities the concentration of public transportation supply to historical downtowns has not been an attraction factor, and downtown uses have expanded to less accessible areas. Gentrification in Chicago is also another process showing that land use changes are related to many factors, transportation being only one of them, and not always a necessary one. In all three cases the use of railways, as a set of inherited infrastructures, has seen an increase whose magnitude suggests a link to modal reassignment due to increasing congestion. Scarcity of space in old downtown areas is being counteracted through more intense use, or through the expansion of vertical space for transportation operations.     

Integrated models of land use and transportation for the autonomous vehicle revolution

ABSTRACT

The advent of the autonomous vehicle (AV) will affect not only the transportation system, but also future patterns of land development. Integrated land use and transportation models will be critical tools in assessing the path forward with this technology. Key questions with respect to land use impacts of AVs arise from potential changes in sensitivity to travel and reduced demand for parking. It is an open question whether AVs will induce urban sprawl, or whether spatial economies of agglomeration will mitigate any reductions in travel time sensitivity. The deployment of shared fleets of AVs would likely reduce parking demand, producing yet to be explored impacts on property development within existing urban footprints. We perform a critical assessment of currently operational models and their ability to represent the adoption of AVs. We identify the representation of time in such models as a vital component requiring additional development to model this new technology. Existing model applications have focused on the discrete addition of new infrastructure or policy at a fixed point in time, whereas AV adoption will occur incrementally through time. Stated adaptation surveys are recommended as tools to quantify preferences and develop relevant model inputs. It is argued that existing models that assume comparatively static equilibrium have been convenient in the past, but are insufficient to model technology adoption. In contrast, dynamic model frameworks lack sufficient structure to maintain reasonability under large perturbations from base conditions. The ongoing advancement of computing has allowed models to move away from being mechanistic aggregate tools, towards behaviourally rich depictions of individual persons and firms. However, much work remains to move from projections of existing conditions into the future, to the evolution of the spatial economy as it evolves through time in response to new technologies and exogenous stresses. Principles from complex and evolutionary systems theory will be important in the development of models with the capacity to consider such dynamics.     

Instantaneous multihop connectivity of one-dimensional vehicular ad hoc networks with general distributions of communication nodes

Connected and automated vehicle technologies hold great promises for improving the safety, efficiency, and environmental impacts of the transportation sector. In this study we are concerned with multihop connectivity of instantaneous vehicular one-dimensional ad hoc networks (VANETs) formed by connected vehicles along a communication path in a road network with given either vehicle locations or traffic densities, market penetration rates, and transmission ranges. We first define a new random variable for the location of the end node of a communication chain, which is a discrete random variable with given vehicle locations and a mixed random variable with given traffic densities. Then recursive, iterative, or differential equation models of instantaneous multihop connectivity between two communication nodes are derived from the relationships between end node probability mass or density function and connectivity. Assuming a simple communication model, the new models are applicable for general distribution patterns of vehicles and communication nodes, including non-evenly placed vehicles and nonhomogeneous Poisson distributions of nodes. With given vehicle locations, the computational cost for this new model is linear to the number of vehicles; with given traffic densities, we derive a new closed-form connectivity model for homogeneous Poisson distributions of communication nodes and an approximate closed-form model when distribution patterns of communication nodes are given by spatial renewal processes. We then apply the models to evaluate impacts on connectivity of traffic patterns, including shock waves, and road-side stations. The connectivity model could be helpful for designing routing protocols in VANETs and developing their applications in transportation systems.     

Analyzing commuter train user behavior: a decision framework for access mode and station choice

The purpose of the current research effort is to develop a framework for a better understanding of commuter train users’ access mode and station choice behavior. Typically, access mode and station choice for commuter train users is modeled as a hierarchical choice with access mode being considered as the first choice in the sequence. The current study proposes a latent segmentation based approach to relax the hierarchy. In particular, this innovative approach simultaneously considers two segments of station and access mode choice behavior: Segment 1—station first and access mode second and Segment 2—access mode first and station second. The allocation to the two segments is achieved through a latent segmentation approach that determines the probability of assigning the individual to either of these segments as a function of socio-demographic variables, level of service (LOS) parameters, trip characteristics, land-use and built environment factors, and station characteristics. The proposed latent segment model is estimated using data from an on-board survey conducted by the Agence Métropolitaine de Transport for commuter train users in Montreal region. The model is employed to investigate the role of socio-demographic variables, LOS parameters, trip characteristics, land-use and built environment factors, and station characteristics on commuter train user behavior. The results indicate that as the distance from the station by active forms of transportation increases, individuals are more likely to select a station first. Young persons, females, car owners, and individuals leaving before 7:30 a.m. have an increased propensity to drive to the commuter train station. The station model indicates that travel time has a significant negative impact on station choice, whereas, presence of parking and increased train frequency encourages use of the stations.     

Electric vehicle charging station locations: Elastic demand,station congestion,and network equilibrium

Battery-only electric vehicles (BEVs) generally offer better air quality through lowered emissions, along with energy savings and security. The issue of long-duration battery charging makes charging-station placement and design key for BEV adoption rates. This work uses genetic algorithms to identify profit-maximizing station placement and design details, with applications that reflect the costs of installing, operating, and maintaining service equipment, including land acquisition. Fast electric vehicle charging stations (EVCSs) are placed across a congested city's network subject to stochastic demand for charging under a user-equilibrium traffic assignment. BEV users’ station choices consider endogenously determined travel times and on-site charging queues. The model allows for congested-travel and congested-station feedback into travelers’ route choices under elastic demand and BEV owners’ station choices, as well as charging price elasticity for BEV charging users.Boston-network results suggest that EVCSs should locate mostly along major highways, which may be a common finding for other metro settings. If 10% of current EV owners seek to charge en route, a user fee of $6 for a 30-min charging session is not enough for station profitability under a 5-year time horizon in this region. However, $10 per BEV charging delivers a 5-year profit of $0.82 million, and 11 cords across 3 stations are enough to accommodate a near-term charging demand in this Boston-area application. Shorter charging sessions, higher fees, and/or allowing for more cords per site also increase profits generally, everything else constant. Power-grid and station upgrades should keep pace with demand, to maximize profits over time, and avoid on-site congestion.     

Discrete choice with spatial correlation: A spatial autoregressive binary probit model with endogenous weight matrix (SARBP-EWM)

Discrete choice modeling is widely applied in transportation studies. However, the need to consider correlation between observations creates a challenge. In spatial econometrics, a spatial lag term with a pre-defined weight matrix is often used to capture such a correlation. In most previous studies, the weight matrix is assumed to be exogenous. However, this assumption is invalid in many cases, leading to biased and inconsistent parameter estimates. Although some attempts have been made to address the endogenous weight matrix issue, none has focused on discrete choice modeling. This paper fills an existing gap by developing a Spatial Autoregressive Binary Probit Model with Endogenous Weight Matrix (SARBP-EWM). The SARBP-EWM model explicitly considers the endogeneity by using two equations whose error terms are correlated. Markov Chain Monte Carlo (MCMC) method is used to estimate the model. Model validation with simulated data shows that the model parameters can converge to their true values and the endogenous weight matrix can be reliably recovered. The model is then applied to a simplified firm relocation choice problem, assuming that similar size firms influence one another. The model quantifies the peer effect, and takes into consideration other independent variables including industry type and population density. The estimation results suggest that peer influence among firms indeed affect their relocation choices. The application results offer important insights into business location choice and can inform future policy making. The sample size for applying the model is currently limited to hundreds of observations. This paper contributes to the existing literature on discrete choice modeling and spatial econometrics. It provides a new tool to discover spatial correlations that are hidden in a wide range of transportation issues, such as land development, location choice, and various travel behavior. Those hidden spatial correlations are otherwise difficult to identify and estimation results may be biased. Establishing a new model that explicitly considers endogenous weight matrix and applying the model to a real life transportation issue represent a significant contribution to the body of literature.