Land Use Transport Interaction Research Articles

Estimating time-saving benefits and mode shifts from improvements of sustainable transport modes in Cambridge, UK

This paper compares the impacts of sustainable transport alternatives to cars for small cities, in terms of mode shifts and time-saving benefits. This paper develops a new land use-transport interaction model with a detail multi-modal network, which can be quickly set up and used for small cities and their low-density exurbs. Whilst many existing models for small cities tend to focus on car traffic, treating non-car modes as a side-show, this model tests all modes on an equal footing. We use this model in a case study area that includes the city of Cambridge and its environs, a fast-growing low-density area. Three groups of sustainable transport alternatives under public discussion are tested, including Cambridge Autonomous Metro, demand responsive buses, and improving cycling and walking infrastructure. We find that in the case study area improving walking and cycling infrastructure is by far the most effective for modal shift from the car and accruing the highest time-saving benefits, as it reduces car commuting mode share from 56% to 49% for the suburbs of Cambridge. Demand responsive buses appear to be the second most effective option in reducing car trips. Metros, contrary to existing expectations, would achieve the least.

A review of the housing market-clearing process in integrated land-use and transport models

The land-use/transport interaction (LUTI) modeling framework has become the current state of best practice for analyzing the interdependency between the land-use and transportation systems. This paper presents a comprehensive review of the housing market-clearing mechanisms used in operational LUTI models. Market clearing is a critical component of modeling housing markets, but a systematic review and critique of the current state of the art have not previously been undertaken. In the review paper, the theoretical foundations for modeling household location choice are reviewed, including bid-rent and random utility theories. Five LUTI models are discussed in detail: two equilibrium models, MUSSA and RELU-TRAN, and three dynamic disequilibrium models, UrbanSim, ILUTE, and SimMobility. The discussion focuses on the following key points: the assumptions embedded in the models, the aggregation level of households and locations, computational cost and operationalization of the models. One of the challenges is that there are rarely any empirical studies that compare the performance of equilibrium and dynamic models in the same study context. Future research is recommended to empirically investigate the pros and cons of the two modeling approaches and compare the model performances for their representativeness of real-world behavior, computational efficiencies, and abilities for policy analysis. More sophisticated studies about the impacts of agents’ behavior on the housing market-clearing process are also recommended.

A land-use transport-interaction framework for large scale strategic urban modeling

We introduce a family of land use transportation interaction (LUTI) models which enable future employment, population and flows or trips between these activities to be explained and predicted. We begin by focusing on the generic spatial interaction model, noting the ways in which its components reflect demand and supply at different locations measured in terms of employment and working population. This suggests an equilibrium structure which is our starting point in developing a simplified version of the model which we extend to deal with four different activity sectors – housing, retail activities, schools, and health facilities. We use this generic structure to develop four related versions of the generic LUTI model equations for residential populations, retailing, education and hospitals which are all driven by employment in terms of where people live and work. This constitutes our integrated framework that we use in calibrating, that is fine-tuning the model to three urban areas (cities) in Europe: to Oxford and its county, Turin and its region, and Athens in its hinterland of Attica reflecting population volumes from 700,000, 1.7 million and 3.8 million persons respectively. In each case, we use the models to predict the impact of different scenarios – new housing developments in Oxfordshire, new universities and metro lines in Turin, and economic development in the Athens region. We describe the details of these scenarios in Supplementary Information (SI) which shows the versatility of using the models to examine such impacts and we conclude with directions for improving the various models and nesting them at different scales within the land use-transport planning process.

Land use change in Dhaka City Corporation Area and its impact on transportation: A way forward towards integration into national policies

Land use and transport integration has been highlighted as one of the most important policy objectives considering the interrelationship between the two concepts and can be used as a means of planning through intervention. From the standpoint of revealing the interplay, the study's objective is to assess the land use change of Dhaka City Corporation Area and determine its impact on transportation to assist the national policymaking and achieve Sustainable Development Goals (SDGs). The methodology directed the determination of the land use change from 2010 to 2018, and then the consequent change in traffic flow while the necessary data in this regard were collected from secondary sources. The study shows that mixed-use development generates fewer trips. This is the study's finding in regard to integration among the national policies regarding land use and transport planning. This study is a methodological approach to analyse the impact of land use change on transportation and can be a role model for solving complex urban problems, e.g., traffic congestion by integrating the Land Use-Transport interaction. The study provides a background of the policymakers in their policymaking process, and an integrated policy will enable the nation to fulfil its Sustainable Development Goals.

Transport Infrastructure and Regional Development: A Survey of Literature on Wider Economic and Spatial Impacts

The main purpose of the paper is to provide an overview of methods used to research the relationship between transport infrastructure investments and regional development, with a focus on wider impacts both in the traditional economic context (wider economic impacts or WEIs) and—which is a methodological novelty proposed by this paper—in the spatial context (wider spatial impacts or WSIs). In terms of methodology, research may be conducted using the following methods: cost benefit analysis (CBA) and multi-criteria analysis (MCA), accessibility and potential models, econometric production function estimates, regional modelling, trade and input-output (IO) modelling, Land Use-Transport Interaction (LUTI) or spatial computable general equilibrium (SCGE) models. In the European Union, approaches based on cost-benefit analysis (CBA), or possibly multi-criteria analysis (MCA), continue to prevail. Notwithstanding the availability of a wide range of methods for quantifying socio-economic impacts, the European Union recommends that wider economic impacts at the regional and national levels be assessed by means of qualitative approaches. This being the case, it is recommendable for the European Commission to take broad-ranging action towards ensuring that the effects of transport infrastructure investments are assessed by means of a broader range of approaches.

Interactive mapping for public transit planning: Comparing accessibility and travel-time framings

As transport planners increasingly frame project impacts in accessibility terms, it is worth considering how this foundational land-use transport interaction concept can shape stakeholder attitudes. In this paper, we test whether framing the benefits of public transit projects in terms of increased accessibility better fosters enthusiasm among advocates, as compared to framing benefits in terms of travel-time savings. We test two versions of an interactive mapping tool in small workshops examining upgraded bus services. One version shows isochrones and accessibility indicators, and the other shows paths and travel time indicators. Results from pre- and post-surveys suggest that framing impacts in accessibility terms may encourage broader thinking and stronger dialog than framing impacts in time-savings terms. In particular, the accessibility version seems to mitigate skepticism and car users’ predispositions against upgrading bus service. An unexpected result is that many workshop participants report decreased overall enthusiasm for the bus upgrades after using either version of the tool. This disappointment may stem from an unrealistic baseline, which assumes perfect schedule adherence not aligned with lived experiences. Future research should consider tools that help stakeholders understand and deliberate about actual service and network-level reliability, and testing such tools with wider audiences.

Framework to generate virtual cities as sandboxes for land use-transport interaction models

One of the major critiques of land use-transport interaction (LUTI) models over the ages has been their over-dependence on individualized software and context. In an effort to address some of these concerns, this study proposes a framework to construct "virtual cities" that can act as sandboxes for testing different features of a LUTI model, as well as provide the capability to compare different LUTI models. We develop an approach to translate any prototypical transportation infrastructure network into a plausible land use zoning plan and synthetic population that are suitable for spatially detailed LUTI microsimulation of the virtual city. Disaggregate units of spatial geometry, like parcels and post codes, are generated using geospatial techniques applied to the transportation network. Households and jobs are randomly sampled from an actual city, and allocated in the virtual city based on matching density gradients. Students are matched with schools and workers are matched with jobs to complete the calibration of a synthetic population for the virtual city. Following the adjustment of behavioral models to complement the reduced scale of the virtual city, we demonstrate the integration between the land use and transportation simulation components in our LUTI model, SimMobility. The benefits of faster convergence times and shorter simulation times are clearly demonstrated through this exercise. We hope that this study, and the open-source releases of the SimMobility software with the virtual city database, can accelerate experimentation with LUTI models and aid the transition from individualized LUTI models to a common shared integrated urban modeling platform.

A new framework for very large-scale urban modelling

The generation of ever-bigger data sets pertaining to the distribution of activities in cities is paralleled by massive increases in computer power and memory that are enabling very large-scale urban models to be constructed. Here we present an effort to extend traditional land use–transport interaction (LUTI) models to extensive spatial systems so that they are able to track increasingly wide repercussions on the location of population, employment and related distributions of spatial interactions. The prototype model framework we propose and implement called QUANT is available anywhere, at any time, at any place, and is open to any user. It is characterised as a set of web-based services within which simulation, visualisation and scenario generation are configured. We begin by presenting the core spatial interaction model built around the journey to work, and extend this to deal with many sectors. We detail the computational environment, with a focus on the size of the problem which is an application to a 8436 zone system comprising England, Scotland and Wales generating matrices of around 71 million cells. We detail the data and spatial system, showing how we extend the model to visualise spatial interactions as vector fields and accessibility indicators. We briefly demonstrate the implementation of the model and outline how we can generate the impact of changes in employment and changes in travel costs that enable transport modes to compete for travellers. We conclude by indicating that the power of the new framework consists of running hundreds of ‘what if?’ scenarios which let the user immediately evaluate their impacts and then evolve new and better ones.

Impact of land use on bicycle usage: A big data-based spatial approach to inform transport planning

Bicycling is an alternative of urban transport mode, which is significantly influenced by land use. This paper makes an effort to quantify the magnitude and direction of the impact. We first develop a theoretical framework to establish links between land use and bicycle usage. Then, trip data is crawled from Mobike, one of the largest newly emerging, free-floating bike sharing operators in Shenzhen (China), for a total of more than 7.8 million records over 191 consecutive days. And bicycling frequency, travel duration, and riding distance are obtained to be proxies of bicycle usage. Land-use characteristics regarding bicycling are comprehensively indicated by a set of standardized variables including three dimensions, land-use type, land-use mix, land-use connections, and 12 concrete indices. Panel spatial model is applied to quantify the associations at the district level with socioeconomics controlled. Results show that the percentage of green land has a remarkable impact on bicycle usage outcomes and land-use mix is positively associated with bicycling frequency. Density of intersections contributes to longer trip duration. Bicycle lane is a positive facilitator on workdays, while the number of stations is positively related to bicycle usage, especially frequency and distance. These findings provide insight into land use-transport interaction and could be of value to policymakers, planers and practitioners for transport planning while incorporating bicycling-friendly principles.

Planning car-lite neighborhoods: Examining long-term impacts of accessibility boosts on vehicle ownership

Transformative technologies like automated vehicles, and emerging services like mobility-on-demand and ride-sharing, are changing the ecosystem of urban mobility. Land use-transport interaction (LUTI) models provide appropriate platforms to test the impacts of such services on cities. Although these services are purported to have mixed effects on cities, there is a general consensus that these services will increase accessibility. We approach the ‘car-lite’ policy through this lens of increased accessibility, and base this study in the city-state of Singapore. Different study areas are chosen in a manner similar to the differences-in-differences approach, in order to tease out the effects of initial neighborhood vacancy rate, vehicle-free behavior, and tight markets on policy impacts. We also design different scenarios that represent varying market reactions to the policy, and compare them to a baseline where the car-lite policy is never implemented. Study areas that are initially less ‘tight’ (i.e., have higher vacancy rates and lower vehicle-free rates) are found to have significantly larger transitions to vehicle-free behavior. Additionally, our finding of accessibility-induced gentrification speaks to the importance of considering the endogeneity in housing and mobility choices while formulating policies that may seemingly feel relevant only to the transportation realm. Providing appropriate mixes of housing typologies with adequate affordable housing, in addition to restricting car use for higher-income car-owning households, are suggested as strategies for designing car-lite neighborhoods.

A conceptual LUTI model based on neural networks

This paper deals with Land-use-Transport-Interaction (LUTI) and presents a conceptual model of a data driven LUTI modelling tool based on neural networks. A starting point is the general opinion of experts on the state of the art LUTI models; currently used land use transportation models are too aggregate in substance. Therefore to enhance the interaction between transport and land-use, researchers propose the refinement of the models; internalising more comprehensive relationships. However, the lack of a good theoretical framework impedes the development and consequently the use of these models on a large scale. This fact has fuelled questions: (i) does transport planning need these comprehensive descriptions of land use; (ii) is it necessary to disaggregate and refine the models further in order to be able to do consistent transport planning; (iii) which land use characteristics should at least be internalised; and (iv) which modelling method is suitable for implementation. Based on literature, the hypothesis is that the first question can be answered by ’no’ and no further refinements are needed. Literature shows that the main drivers for land-use changes are the location choice of both households and firms. Therefore only these two building blocks are used in relation with the transport component. Artificial neural networks (ANNs) will be used as the modelling technique. ANNs are data driven techniques that find relationships in data during an auto calibration process. Therefore ANNs can work without having a sound theoretical framework. This characteristic offers possibilities for LUTI modelling that lacks a sound theoretical framework. The research leads to a conceptual model. A literature review shows that the individual building blocks of the conceptual LUTI model can be modelled using neural networks. However, an integration of the building blocks has not been established yet. Further research has to result in the actual implementation of the proposed model.

Land-use, transport and vehicle technology futures: An air pollution assessment of policy combinations for the Cambridge Sub-Region of the UK

This paper reports on an investigation of the impact on air-quality of combinations of urban form development scenarios and vehicle fleet technology changes. The scenarios combine policies affecting urban land-use plans within the Cambridge Sub-Region of the UK, alongside technological changes within the projected vehicle fleet. Broadly, the scenarios consist of the ‘Trend’ for urban form policy and vehicle technology and the urban form policy options of ‘Planned expansion’, ‘Market-led development’ and ‘Urban compaction’, each combined with form-appropriate technological scenarios addressing the uptake of current, and future, technologies in the vehicle fleet. The framework developed for environmental assessment is described, from land-use transport interaction, through traffic assignment and emissions modelling, through to dispersion calculations.The urban form-vehicle technology combinations have been assessed in terms of overall vehicle kilometres travelled (VKT), greenhouse gas (CO2) emissions, and local air quality (NOx, NO2, PM, HC). Results are presented for 2021 and show that overall network emissions change from −13% (Compaction) to +8% (Market-led) relative to the Trend, but effects on emissions in individual districts (NOx) may much greater, −40% to +50%. Annual mean concentrations of NO2 at the street level may vary by −7 to 8 μg/m3. The use of electric vehicles in the ‘Urban compaction’ scenario aids mitigation of air quality issues in the city centre. The results are discussed with respect to the feasibility of scenario implementation, current approaches to planning, and trends in vehicle technology. Limitations of the modelling framework are also identified, and future developments outlined.

Modelling urban spatial impacts of land-use/ transport policies

China is now experiencing rapid urbanization. Powerful tools are required to assess its urban spatial policies before implemented toward a more competitive and sustainable development paradigm. This study develops a Land Use Transport Interaction (LUTI) model to evaluate the impacts of urban land-use policies on urban spatial development. The model consists of four sub-models, i.e., transport, residential location, employment location and real estate rent sub-models. It is then applied to Beijing metropolitan area to forecast the urban activity evolution trend based on the land-use policies between 2009 and 2013. The modeling results show that more and more residents and enterprises in the city choose to agglomerate on outskirts, and new centers gradually emerge to share the services originally delivered by central Beijing. The general trend verifies the objectives of the government plan to develop more sub-centers around Beijing. The proposed activity-based model provides a distinct tool for the urban spatial policy makers in China. Further research is also discussed at the end.

Future mobility and land use scenarios: impact assessment with an urban case study

In recent years the interest in urban mobility has grown considerably, not only due to the local increase in negative externalities generated by transport, but also because recent technological innovations are offering effective solutions especially in urban context. In particular, the introduction of Connected and Automated Vehicles (CAVs) could radically change the mobility scenario allowing, on the one hand, a widespread diffusion of shared vehicles that could feed the stations of the mass rapid transit network, improving the attractiveness of Public Transportation (PT), and on the other, the implementation of Travel Demand Management (TDM) measures on large areas of the most densely urbanized (and congested) territory of a city, without reducing accessibility and creating social exclusion. The present study aims at evaluating, through a system of Land-Use Transportation Interaction (LUTI) models, the impacts on transport demand and on population and activities location, of transportation policies oriented to both enhancing PT and restricting the individual use of the car. The case study analyzed is represented by the urban area of Rome. Several scenarios have been simulated and compared by means of sustainability indicators. Preliminary results show that the improvement of PT services, combined with the introduction of car use restriction and car free areas, do induce not only a significant modal shift towards more sustainable transportation modes, but also a limitation of urban sprawl.

Does the accessibility measure influence the results of residential location choice modelling?

Accessibility is essential in land-use transport interaction frameworks. For residential location choices in particular, it has always been important at the theoretical level. At the empirical level, the place of accessibility is questioned in some works, considering other more important location characteristics, like the social environment and the neighbourhood amenities. However, this result can be caused by the measurement of accessibility. In view of the wealth of approaches, this paper examines whether different accessibility measures can lead to divergent results. Using a residential location choice model for the Lyon urban area in France, we test various accessibility indicators and we compare the results. We conclude that accessibility is an indispensable variable. Without it, the model gives inconsistent results. Complex accessibility measures give better results but simple measures are also relevant for residential location choices modelling. The choice highly depends on the objectives of the application especially if the model is to be used for simulation.

Sustainable approach to land development opportunities based on both origin-destination matrix and transportation system constraints, case study: Central business district of Isfahan, Iran

Given that there are restrictions on expanding the infrastructure for the purpose of fulfilling future transportation demand, it is critical to consider the capacity of the existing transportation system and the sustainable extent of development, in order to avoid problems such as traffic congestion and air pollution. In this study, by applying the inverse of conventional transportation planning, which is different from the land-use transportation interaction modeling, land-use limits for each Traffic Analysis Zone (TAZ) are determined as a function of the transportation system capacity. Indeed, this method is applied to examine the trip generation capacity of each TAZ with respect to its trip end values. Comparing the indicated capacity with the current demand for each zone can act as a key tool for urban policy makers and planners to define the spatial distribution of new activities based on the present capacity of the transportation system in the studied area. For this purpose, after selecting the transportation network of the central business district in the City of Isfahan as a case of study, the artificial neural networks solution is used to solve the inverse transportation planning problem.

Study on the substantiation of location equilibrium in the CUE model

In the Computable Urban Economic (CUE) Model, one land-use transport interaction (LUTI) model, improving the accuracy of the Location Choice Model is important to evaluate the effects of introducing urban transportation policies. However, our previous study revealed that the substantiation of the indirect utility function by a linear expenditure system has not been verified and that location choice behaviors estimated using the logit model depends on the adjustment factor. Therefore, in this study, we first examined the logical meaning of the utility function by a linear expenditure system, and then focused on identifying major constituent factors of the adjustment factor and statistically verified the adjustment factor and urban amenities. As a result, we have identified the following facts: that the conventional indirect utility function may underestimate the effect of introducing urban transportation policies; that if effects are estimated using WLS after adding housing supply factors to the indirect utility function, the estimation accuracy will be improved; and that the major constituent factors of the adjustment factor are those expressing local characteristics of cities and wards.

: (Development of the Russian Transport Sector: Current State and Development Prospects)

Russian Abstract: В работе проведен анализ существующих особенностей развития транспортного комплекса России, его текущих характеристик, а также внешних и внутренних факторов, которые могут оказывать влияние на развитие транспортного комплекса, а также анализ существующих подходов к постановке целей развития транспортного комплекса РФ в основных стратегических документах. Проведен обзор существующих теоретических и прикладных подходов к моделированию транспортных потоков и услуг транспортного комплекса (Input-Output-Models, Spatial Computable General Equilibrium Models, Land-use Transport Interaction Models и др.). Построена теоретическая и эмпирическая модели для анализа взаимного влияния развития российской экономики и транспортной системы, проведена ее эмпирическая оценка. English Abstract: The following tasks were solved in the paper: analysis and systematization of the existing theoretical and empirical approaches to assess the degree import price rigidity with respect to exchange rate fluctuations; analysis and systematization of the existing theoretical and empirical approaches to assess the degree import price rigidity with respect to importing firm characteristics; an empirical analysis and assessment of the degree of import price rigidity with respect to exchange rate fluctuations and importing firm characteristics in Russian economy. To solve these above stated problems, we used data on customs declaration and the currency data and other indicators, published by the Central Bank of the Russian Federation and the Federal State Statistics Service.

A strategic and dynamic land-use transport interaction model for Bogotá and its region

ABSTRACTThis paper presents an integrated and strategic model to simulate the dynamic interaction processes between land-use and transport at an aggregate level in Bogotá region. The model uses Causal Loop Diagrams from Systems Dynamics to explain cause and effect relations and incorporates a calibration for the base-year. This model is inspired by the basic hypothesis of the MARS model, although due to the particular characteristics of the study area, it was necessary to make changes. In cities like Bogotá, there is a lack of understanding of the importance of land-use and transport integration challenges, a focus mainly on the short term, a limited knowledge about quantification of the impact of integrated policies, and uneven information availability. Data limitation has been identified as a significant limitation. Consequently, innovative approaches are required in developing cities to adapt to situations where limited information is available. This paper describes the basis, capabilities, and potential uses of LUTI-Bogotá model.

Models of Coupled Settlement and Habitat Networks for Biodiversity Conservation: Conceptual Framework, Implementation and Potential Applications

Worldwide, the expansion of settlement and transport infrastructure is one of the most important proximate as well as ultimate causes of biodiversity loss. As much as every modern human society depends on a network of settlements that is well-connected by transport infrastructure (i.e. settlement network), animal and plant species depend on networks of habitats between which they can move (i.e. habitat networks). However, changes to a settlement network in a region often threaten the integrity of the region’s habitat networks. Determining plans and policy to prevent these threats is made difficult by the numerous interactions and feedbacks that exist between and within the settlement and habitat networks. Mathematical models of coupled settlement and habitat networks can help us understand the dynamics of this social-ecological system. Yet, few attempts have been made to develop such mathematical models. In this paper, we promote the development of models of coupled settlement and habitat networks for biodiversity conservation. First, we present a conceptual framework of key variables that are ideally considered when operationalising the coupling of settlement and habitat networks. In this framework, we first describe important network-internal interactions by differentiating between the structural (i.e. relating to purely physical conditions determining the suitability of a location for living or movement) and functional (i.e. relating to the actual presence, abundance or movement of people or other organisms) properties of either network. We then describe the main one-way influences that a settlement network can exert on the habitat networks and vice versa. Second, we give several recommendations for the mathematical modelling of coupled settlement and habitat networks and present several existing modelling approaches (e.g. habitat network models and land-use transport interaction models) that could be used for this purpose. Lastly, we elaborate on potential application of models of coupled settlement and habitat networks in the development of complex network theory, in the assessment of system resilience and in conservation, transport and urban planning. The development of coupled settlement and habitat network models is important to gain a better system-level understanding of biodiversity conservation under a rapidly urbanising and growing human population.