Integrated land use — transport models

This paper is a review of computer models of the interrelationships between land use and transport, particularly of the long‐term effects of changes in transport costs on cities and the consequent effects on travel demand. The nature of this relationship is examined in terms of empirical evidence, and a set of criteria against which the models can be evaluated is defined. Four major types of model are examined: regression, mathematical programming, aggregate spatial interaction and individual choice. Each type is considered in terms of operational examples and the strengths and weaknesses of each approach are identified. However, it is recognized that few of the models are capable of representing the major social and technological changes that are currently influencing urban development, and that this is where emphasis should be put if this type of model is to be useful for policy‐making in the future.     

Modelling the impact of rail fare increases

Rail fares in South-East England have been increasing in real terms for several years, and are expected to continue to do so. In this paper, the impact of such increases is examined in terms of the choices of mode of travel, home and job location, and residential migration. Forecasts are made using a model in which the population is partitioned into four sets according to whether they have changed home and/ or job over the forecast period. The model allocates population to homes and workers to jobs, and commuters to the three modes of travel considered. The impact of an increase of 25% in real fares over a five-year period is examined and a number of conclusions are drawn. The model shows that rail patronage will decline even if transport costs remain constant in real terms, because of decentralisation of jobs and rising car ownership. The overall long-term rail fare elasticity is found to be –0.7, but this is the mean of a wide range of values for different parts of the study area. People ceasing to commute by rail would divide almost equally between car and bus, the latter being used particularly to Central London. Those people who commute to London who are seeking new homes would tend to choose to live nearer London than they would have otherwise. The paper concludes with a discussion of the findings in terms of the assumptions implied in the model.     

Long-term impacts of transport infrastructure networks on land-use change: an international review of empirical studies

Improvements in geographical information systems, the wider availability of high-resolution digital data and more sophisticated econometric techniques have all contributed to increasing academic interest and activity in long-term impacts of transport infrastructure networks (TINs) on land use (LU). This paper provides a systematic review of recent empirical evidence from the USA, Europe and East Asia, classified regarding the type of transport infrastructure (road or rail), LU indicator (land cover, population or employment density, development type) and outcome (significance, relationship’s direction) as well as influential exogenous factors. Proximity to the rail network is generally associated with population growth (particularly soon after the development of railway infrastructure), conversion to residential uses and the development of higher residential densities. Meanwhile, proximity to the road network is frequently associated with increases in employment densities as well as the conversion of land to a variety of urban uses including commercial and industrial development. Compared with road infrastructure, the impact of rail infrastructure is often less significant for land cover or population and employment density change. The extent of TINs’ impact on LU over time can be explained by the saturation in TIN-related accessibility and LU development.     

The impact of transport policies on railroad intermodal freight competitiveness – The case of Belgium

This paper discusses the impact of three freight transport policies aiming to promote railroad intermodal transport in Europe, and examines the case of Belgium as a testing ground. These policies consist in subsidizing intermodal transport operations (such as in Belgium, to stimulate rail transport), internalizing external costs (as recommended by the European Union in order to foster cleaner modes), and adopting a system perspective when optimizing the location of inland intermodal terminals. The study proposes an innovative mixed integer intermodal freight location-allocation model based on hub-location theory and deals with non-linear transport costs in order to replicate economies of distance. Our analysis suggests that subsidizing has a significant impact on the volumes transported by intermodal transport, and, to a lesser extent, that optimizing terminal location increases the competitiveness of intermodal transport. On the other hand, according to our assumptions, internalizing external costs can negatively impact the promotion of intermodality. This finding indicates that innovative last-mile transports are needed in order to reduce the external impacts of drayage operations.     

Distinguishing the land use effects of road pricing based on the urban form attributes

This paper studies the effects of road pricing on land use under different development scenarios (business as usual scenario and transit oriented development scenario) by a quantitative method, which combines the integrated land use and transport interaction model (TRANUS model) with the scenario-planning techniques. Moreover, in order to further analyze the differences of the land use effects of road pricing on traffic analysis zones (TAZs) with different urban form attributes, a quantitative classification method combining factor analysis and cluster analysis is then used to quantitatively classify TAZs. The results demonstrate that the effects of road pricing on the land use of a specific region depend on the urban form attributes of the region. The higher the densities of employments and population, and better street design (high densities of street and intersections) and public transportation condition, the less the region is negatively affected by road pricing, and vice versa. More importantly, rail transit can alleviate the negative impact of road pricing on commercial development and population concentration of the region. Therefore, before introducing a road pricing policy, it is necessary to develop public transport system, especially rail transit.     

Modeling residential location choice in relation to housing location and road tolls on congested urban highway networks

We present a reformulation of the residential location submodel of the Integrated Model of Residential and Employment Location as a network equilibrium problem, thereby making travel costs by auto endogenous. The location of housing supply is examined as a welfare maximization problem for both user-optimal and system-optimal travel costs using concepts of bilevel programming. Finally, we briefly discuss how the employment submodel can be reformulated, and the entire model solved as a variational inequality problem.     

Using structural equations modeling to unravel the influence of land use patterns on travel behavior of workers in Montreal

This paper addresses the relations between travel behavior and land use patterns using a Structural Equations Modeling (SEM) framework. The proposed model structure draws on two earlier models developed for Lisbon and Seattle which show significant effects of land use patterns on travel behavior. The travel behavior variables included here are multifaceted including commuting distance, car ownership, the amount of mobility by mode (car, transit and non-motorized modes), both in terms of total kilometers travelled and number of trips. The model also includes a travel scheduling variable, which is the total time spent between the first and last trips to reflect daily constraints in time allocation and travel.The modeled land use variables measure the levels of urban concentration and density, diversity, both in terms of types of uses and the mix between jobs and inhabitants/residents, the transport supply levels, transit and road infrastructure, and accessibility indicators. The land use patterns are described both at the residence and employment zones of each individual included in the model by using a factor analysis technique as a data reduction and multicollinearity elimination technique. In order to explicitly account for self selection bias the land use variables are explicitly modeled as functions of socioeconomic attributes of individuals and their households.The results obtained show that people with different socioeconomic characteristics tend to work and live in places of substantially different urban environments. But besides these socioeconomic self-selection effects, land use variables significantly affect travel behavior. More precisely the effects of land use are in great part passed thru variables describing long term decisions like commuting distance, and car ownership. These results point to similar conclusions from the models developed for Lisbon and Seattle and thus give weight to the use of land use policies as tools for changing travel behavior.     

Longer and heavier vehicles in Belgium: A threat for the intermodal sector?

To achieve transport cost reductions and to reduce the environmental impact of road transport, different European countries are allowing or testing longer and heavier vehicles on their road network. In Belgium, the Flanders region started a trial in 2015 allowing a limited number of longer and heavier vehicles on a selection of approved routes. A concern among intermodal operators is however that an allowance of longer and heavier vehicles could trigger a reverse modal shift away from rail and inland waterways container transport. Starting from experiences in other European countries, this paper discusses the potential spatial impact of allowing longer and heavier vehicles on the market areas of intermodal transhipment terminals using a geographic information systems-based location analysis model. In a second step, external transport costs are incorporated in this model, to quantify the spatially diversified societal costs of a potential reverse modal shift.     

The effect of complex models of externalities on estimated optimal tolls

Transport externalities such as costs of emissions and accidents are increasingly being used within appraisal and optimisation frameworks alongside the more traditional congestion analysis to set optimal transport policies. Models of externalities and costs of externalities may be implemented by a simple constant cost per vehicle-km approach or by more complex flow and speed dependent approaches. This paper investigates the impact of using both simple and more complex models of CO₂ emissions and cost of accidents on the optimal toll for car use and upon resulting welfare levels. The approach adopted is to use a single link model with a technical approach to the representation of the speed-flow relationship as this reflects common modelling practice. It is shown that using a more complex model of CO₂ emitted increases the optimal toll significantly compared to using a fixed cost approach while reducing CO₂ emitted only marginally. A number of accident models are used and the impact on tolls is shown to depend upon the assumptions made. Where speed effects are included in the accident model, accident costs can increase compared to the no toll equilibrium and so tolls should in this case be reduced compared to the congestion optimal toll. Finally it is shown that the effect of adding variable CO₂ emission models along with a fixed cost per vehicle-km for accidents can increase the optimal toll by 44% while increasing the true welfare gained by only 8%. The results clearly demonstrate that model assumptions for externalities can have a significant impact on the resulting policies and in the case of accidents the policies can be reversed.

Cordon tolls and competition between cities with symmetric and asymmetric interactions

The aim of this paper is to model the impacts of competition between cities on both the optimal welfare generating tolls and upon longer-term decisions such as business and residential location choices. The research uses a dynamic land use transport interaction model of two neighbouring cities and analyses the impacts by setting up a game between the two cities to maximise the welfare of their own residents. The work builds on our earlier research which studied competition in a small network using a static equilibrium approach for private car traffic without accounting for the land use responses to the change in accessibility. This paper extends the earlier work by setting up a dynamic model which includes active modes of travel and the more usual car and public transport in a realistic twin city setting and assesses the longer term relocation responses. This paper firstly sets out the competition between two hypothetical identical cities i.e. the symmetric case; and then sets out the real world asymmetric case in which the cities are of different size representative of Leeds and Bradford in the UK but equally applicable elsewhere too. We found that the level of interaction between the two cities is a key determinant to the optimal tolls and welfare gains. Our findings show that the competition between cities could lead to a Nash Trap at which both cities are worse off in terms of welfare gains. On the other hand, we found that cities, if regulated, would gain in terms of welfare and yet charge only half the toll compared with tolls under competition. We then show that the effect of competition increases with increased interaction between cities. In terms of residential location, cities with higher charges benefit from an increase in residents, though as with other studies, the relative change in population in response to cordon charging is small. The policy implications are threefold—(i) while there is an incentive to cooperate at local authority level, this is not achieved due to competition; (ii) where cities compete they may fall into a Nash Trap where both cities will be worse off compared to the regulated solution; and (iii) regulation is recommended when there is a strong interaction between the cities but that the benefits of regulation decrease as interaction between cities decreases and the impact of competition is lessened.     

The impact of high-speed rail investment on economic and environmental change in China: A dynamic CGE analysis

This study investigates the impact of high-speed rail investment on the economy and environment in China using a computable general equilibrium (CGE) model. The analysis is implemented in a dynamic recursive framework capturing long-run capital accumulation and labor market equilibrium. A national level impact was simulated through direct impact drivers including land use conversion, output expansion, cost reduction, productivity increase, transport demand substitution and induced demand. The results suggest that rail investment in China over the past decade has been a positive stimulus to the economy, while the effect on CO₂ emissions generation has been large. Overall, the economic impacts of rail investment are achieved primarily through induced demand and output expansion, whereas the contribution from a reduction of rail transportation costs and rail productivity increases were modest. In addition, negligible negative impacts were found from land use for rail development and the substitution effect among other modes. Emissions reduction from substitution of rail for other modes was small and offset by output expansion due to lowered rail transport costs and induced demand.     

Assessing the employment agglomeration and social accessibility impacts of high speed rail in Eastern Australia

There is growing interest in establishing additional evidence, under the umbrella of the wider economy impacts of transport infrastructure projects, to support transport projects in general and public transport projects in particular that struggle to obtain benefit–cost ratios sufficient to gain the support of financial agencies. This paper focuses on one element of wider economy impacts, often referred to as effective economic (employment) density or employment agglomeration impacts, and another, less usually identified, social accessibility impact (SAI) which we refer to as effective social density, which in broad terms provide, correspondingly, evidence of the potential gains in work-related output (often referred to as productivity gains) and potential gains in non-work-related outputs. Both are associated with gains in individual and household benefit attributable to improved accessibility to services linked with populations and particular locations. The SAIs may capture some of the induced benefits in those jurisdictions where these are included routinely in benefit–cost analysis, and the methodology here is most appropriate to those settings where an existing calibrated demand curve may not be available. Using the proposed high speed rail (HSR) project between Sydney and Melbourne as the empirical setting, we identify economic agglomeration and social accessibility benefits for work and non-work related activity respectively. We find the former to be relatively small compared to the significant gains associated with non-work related travel activity, suggesting the greatest benefits associated with HSR, especially for those residents outside of the major metropolitan areas, will be non-work related travel activity.     

Environmental and transport effects of warehouse relocationing: evidence from Norway

Reducing traffic volumes and CO2-emissions from freight transport has proven difficult in many countries. Although the increasing suburbanization of warehouses is seen as a relevant land use trend, comprehensive analyses of their impact remain scarce. This study uses real data in modeling transport, costs, environmental and modal effects from warehouse relocations around Oslo and Trondheim (Norway). Results indicate that for Oslo, traffic performance (ton-km), CO2-emissions, and transport costs increase following warehouse suburbanization. For Trondheim, transport performance and CO2-emissions increase less, while transport costs decrease marginally. We conclude that specific case characteristics (geography and trade patterns) are important in determining the strength and direction of effects, and expect that common concomitant developments (warehouse centralization and consolidation) would lead to more pronounced results. Our findings confirm some, but challenge other, findings from the relatively scarcely literature available. Finally, the study's more general insights and observations can help advance similar analyses beyond Norway.     

Improvement actions for reducing transport’s impact on climate: A shipper’s perspective

The purpose of this paper is to compare improvement actions for reducing transport’s impact on climate from the shipper’s perspective. To that end, it introduces an evaluation tool for comparing improvement actions in transport systems in terms of transport costs, impact on climate, and barriers to implementation. Within the context of five international flows involving a food producer, three actions—namely, engaging intermodal transport, increasing load factors by double-stacking pallets, and using high-capacity vehicles—were evaluated. Shipment data were collected to calculate reductions in transport costs and impact on climate, whereas interviews with the food producer were conducted to identify barriers. Results showed that reductions in transport costs and impact on climate attributed to the improvement actions differed among the five flows. Engaging intermodal transport reduced the system’s impact on climate by 27–53%, double-stacking pallets by 0–23%, and using high-capacity vehicles by 7–15%, with differences primarily due to different freight densities. Concerning barriers to implementation, the improvement actions also varied by flow. Altogether, unlike other papers, which have examined improvement actions separately, this paper offers an evaluation tool for comparing several improvement actions at once, as applied to a particular empirical case. Shippers with multiple flows and several possible improvement actions can use the evaluation tool to efficiently reduce their systems’ impact on climate.     

A decision analysis framework for intermodal transport: Comparing fuel price increases and the internalisation of external costs

This paper presents the impact of fuel price increases on the market area of intermodal transport terminals. Aim of this research is to determine whether an increase in fuel prices is sufficient enough to raise the market area of intermodal transport to the same degree that would be accomplished by stimulating intermodal transport through policy instruments. Therefore, several fuel price scenarios are analysed in order to verify the impact of different fuel price evolutions on the market area of unimodal road transport compared to intermodal transport in Belgium. The LAMBIT-model (Location Analysis for Belgian Intermodal Terminals), which is a GIS-based model (Macharis and Pekin, 2008), is used to analyse the different fuel price increases and enables a visualisation of the impact on the market area. The LAMBIT model incorporates the different network layers for each transport mode by setting up a GIS network that includes four different layers: the road network, the rail network, the inland waterways network and the final haulage network. The geographic locations of the intermodal terminals and the port of Antwerp are added as nodes in the network and the Belgian municipality centres are defined and connected to the different network layers. Based on the different fuel price scenarios representing respectively a fuel price increase with 10% (low price case), 50% (business as usual case) and 90% (high price case), the results of the LAMBIT model show that the market areas rise in favour of intermodal barge/road and intermodal rail/road. Depending on the scenario, the degree of modal shift however differs. Additionally, in order to compare policy measures with the effect of a fuel price increase, the internalisation of the external costs is analysed with the LAMBIT model. For some years, the European Commission is supporting the idea that transportation costs should reflect the true impacts on environment and society, and is relentlessly pushing towards the so called ‘internalisation of external costs’ as a policy instrument in order to establish fair and efficient pricing of different transport modes. This requires monetarizing the external effects of transport and adding them to the already internalized costs in order to give the correct price signals. Results of this comparative analysis performed with the LAMBIT model are also presented in this paper.     

Evaluation and implications of environmental charges on commercial flights

Environmental charges are one of the economic instruments for controlling externalities. Their application to commercial flights has become a preferred method of encouraging the sustainable development of the air transport industry. Two kinds of externalities, aircraft noise and engine emissions, both generating profound impacts on human beings and on the environment, are considered here. The hedonic price method is applied to calculate the social cost of aircraft noise during the landing and take-off stages of the flight. The marginal impact of each flight with specific aircraft/engine combinations is derived for the allocation of aggregate noise social costs. In contrast, the dose - response method is applied to estimate the social cost of each engine exhaust pollutant during different flight modes. The combination of aircraft noise and engine emissions social costs is then evaluated on the basis of several environmental charge mechanism scenarios, using Amsterdam Airport Schiphol as a case study. It is shown that the current noise or engine emissions related charges at airports are lower than the actual social costs of their respective externalities. The implications of charge mechanism scenarios are subsequently discussed and evaluated in terms of their impacts on airline costs, airfares and passenger demand.     

Modelling the full costs of an intermodal and road freight transport network

This paper develops a model for calculating comparable combined internal and external costs of intermodal and road freight transport networks. Internal costs consist of the operational-private costs borne by the transport and intermodal terminal operators, and the time costs of goods tied in transit. The external costs include the costs of the impacts of both networks on society and the environment such as local and global air pollution, congestion, noise pollution, and traffic accidents. The model is applied to the simplified configurations of both networks using the inputs from the European freight transport system. The objective is to investigate some effects of European Union policy, which aims to internalise the external costs of transport, on the prospective competition between two networks from a social perspective.     

Joint optimization of freight facility location and pavement infrastructure rehabilitation under network traffic equilibrium

Establishment of industry facilities often induces heavy vehicle traffic that exacerbates congestion and pavement deterioration in the neighboring highway network. While planning facility locations and land use developments, it is important to take into account the routing of freight vehicles, the impact on public traffic, as well as the planning of pavement rehabilitation. This paper presents an integrated facility location model that simultaneously considers traffic routing under congestion and pavement rehabilitation under deterioration. The objective is to minimize the total cost due to facility investment, transportation cost including traffic delay, and pavement life-cycle costs. Building upon analytical results on optimal pavement rehabilitation, the problem is formulated into a bi-level mixed-integer non-linear program (MINLP), with facility location, freight shipment routing and pavement rehabilitation decisions in the upper level and traffic equilibrium in the lower level. This problem is then reformulated into an equivalent single-level MINLP based on Karush–Kuhn–Tucker (KKT) conditions and approximation by piece-wise linear functions. Numerical experiments on hypothetical and empirical network examples are conducted to show performance of the proposed algorithm and to draw managerial insights.     

Impacts of trade related sustainability strategies on freight transportation: Modelling framework and application for France

The circular and functional economies are being presented in the literature as potential strategies for future sustainable societies. In terms of the consequences for supply chains, they will promote a much more dispersed and diversified, local and network based usage of goods than the current economy, which is comparatively linear, concentrated, long distance oriented and scale economy based. A gap in the literature is the assessment of the effects of these systems on freight transport flows. In our paper, we present a first attempt at estimating this impact using freight transport scenario building and quantitative modelling. In order to translate the main parameters that characterize these systems into factors determining freight transportation volumes, we develop a framework based on a typology of goods categories describing functional and spatial proximity between producers and consumers. In order to simulate changes in the economy, we develop scenarios for the shifting of goods from one category to another and, additionally, include internalization policies that should guide their realization. We calculate the impacts on freight flows using a new interregional transport model for France that includes distribution chains and produces estimates of external costs of transport. Our results show that circular and functional economies could lead to a 2–5% reduction of air pollutant emissions and up to a 14–26% reduction if combined with the internalization of external costs. The scenario with ongoing mass production for differentiated demand is found to lead to a 5% increase of environmental impacts compared to the baseline.     

Determination and Applications of Environmental Costs at Different Sized Airports – Aircraft Noise and Engine Emissions

With the increasing trend of charging for externalities and the aim of encouraging the sustainable development of the air transport industry, there is a need to evaluate the social costs of these undesirable side effects, mainly aircraft noise and engine emissions, for different airports. The aircraft noise and engine emissions social costs are calculated in monetary terms for five different sized airports, ranging from hub airports to small regional airports. The number of residences within different levels of airport noise contours and the aircraft noise classifications are the main determinants for accessing aircraft noise social costs. The environmental impacts of aircraft engine emissions include both aircraft landing and take-off and 30-minute cruise. The social costs of aircraft emissions vary by engine type and aircraft category, depending on the damage caused by different engine pollutants on the human health, vegetation, materials, aquatic ecosystem and climate. The results indicate that the relationship appears to be curvilinear between environmental costs and the traffic volume of an airport. The results and methodology of environmental cost calculation could be applied to the proposed European wide harmonised noise charges as well as the social cost benefit analysis of airports.