Evolution over time of heavy vehicle volume in toll roads: A dynamic panel data to identify key explanatory variables in Spain

Improving the knowledge of demand evolution over time is a key aspect in the evaluation of transport policies and in forecasting future investment needs. It becomes even more critical for the case of toll roads, which in recent decades has become an increasingly common device to fund road projects. However, literature regarding demand elasticity estimates in toll roads is sparse and leaves some important aspects to be analyzed in greater detail. In particular, previous research on traffic analysis does not often disaggregate heavy vehicle demand from the total volume, so that the specific behavioral patterns of this traffic segment are not taken into account. Furthermore, GDP is the main socioeconomic variable most commonly chosen to explain road freight traffic growth over time. This paper seeks to determine the variables that better explain the evolution of heavy vehicle demand in toll roads over time. To that end, we present a dynamic panel data methodology aimed at identifying the key socioeconomic variables that explain the behavior of road freight traffic throughout the years. The results show that, despite the usual practice, GDP may not constitute a suitable explanatory variable for heavy vehicle demand. Rather, considering only the GDP of those sectors with a high impact on transport demand, such as construction or industry, leads to more consistent results. The methodology is applied to Spanish toll roads for the 1990–2011 period. This is an interesting case in the international context, as road freight demand has experienced an even greater reduction in Spain than elsewhere, since the beginning of the economic crisis in 2008.     

On the distribution of urban road space for multimodal congested networks

Transport systems in real cities are complex with many modes of transport sharing and competing for limited road space. This work intends to understand how space distributions for modes and interactions among modes affect network traffic performance. While the connection between performance of transport systems and general land allocation is the subject of extensive research, space allocation for interacting modes of transport is an open research question. Quantifying the impact of road space distribution on the performance of a congested multimodal transport system with a dynamic aggregated model remains a challenge. In this paper, a multimodal macroscopic fundamental diagram (MFD) is developed to represent the traffic dynamics of a multimodal transport system. Optimization is performed with the objective of minimizing the total passenger hours traveled (PHT) to serve the total demand by redistributing road space among modes. Pricing strategies are also investigated to provide a higher demand shift to more efficient modes. We find by an application to a bi-modal two-region city that (i) the proposed model captures the operational characteristics of each mode, and (ii) optimal dynamic space distribution strategies can be developed. In practice, the approach can serve as a physical dynamic model to inform space distribution strategies for policy makers with different goals of mobility.     

Comparison of road freight transport trends in Europe. Coupling and decoupling factors from an Input–Output structural decomposition analysis

Decoupling road freight transport from economic growth has been acknowledged by the European Union as a key means to improving sustainability. It is therefore important to identify both the coupling and decoupling drivers of road freight transport demand in order to determine possible factors that may contribute to reduce road transport in the future without curbing economic development. This research proposes an Input–Output (IO) structural decomposition analysis (SDA) to explain road freight transport in terms of a set of key factors that have strongly influenced road freight demand in recent decades in European countries—such as economic growth, economic structure and the evolution of road transport intensity (including improvements in both supply and transport systems). This methodological approach allows us to quantify and compare their contribution in different European countries to either increase or decrease road freight transport demand. The empirical basis for this analysis is a dataset of nine European countries which have IO tables and road transport data available from 2000 to 2007, comprising data on domestic production, imports and exports as well as tonne-kms for 11 types of commodity classes. The results show that, as a whole, aggregate road transport demand has grown—driven mainly by economic activity—but this growth has been strongly curbed in some countries by changes in road freight transport intensity and moderately by the dematerialization of the economy. International transport has been also proven to be a key factor driving road freight transport volumes. Moreover, the increased penetration of foreign operators in national haulage markets appears to have reinforced the final decoupling levels observed in some cases.     

Modelling mode choice for freight transport using advanced choice experiments

In this paper we use advanced choice modelling techniques to analyse demand for freight transport in a context of modal choice. To this end, a stated preference (SP) survey was conducted in order to estimate freight shipper preferences for the main attributes that define the service offered by the different transport modes. From a methodological point of view, we focus on two critical issues in the construction of efficient choice experiments. Firstly, in obtaining good quality prior information about the parameters; and secondly, in the improved quality of the experimental data by tailoring a specific efficient design for every respondent in the sample.With these data, different mixed logit models incorporating panel correlation effects and accounting for systematic and random taste heterogeneity are estimated. For the best model specification we obtain the willingness to pay for improving the level of service and the elasticity of the choice probabilities for the different attributes. Our model provide interesting results that can be used to analyse the potential diversion of traffic from road (the current option) to alternative modes, rail or maritime, as well as to help in the obtaining of the modal distribution of commercial traffic between Spain and the European Union, currently passing through the Pyrenees.     

Recent developments in traffic flow modeling using macroscopic fundamental diagram

ABSTRACT

This paper presents an overview of the recent developments in traffic flow modelling and analysis using macroscopic fundamental diagram (MFD) as well as their applications. In recent literature, various aggregated traffic models have been proposed and studied to analyse traffic flow while enhancing network efficiency. Many of these studies have focused on models based on MFD that describes the relationship between aggregated flow and aggregated density of transport networks. The analysis of MFD has been carried out based on experimental data collected from sensors and GPS, as well as simulation models. Several factors are found to influence the existence and shape of MFD, including traffic demand, network and signal settings, and route choices. As MFD can well express the traffic dynamics of large urban transport networks, it has been extensively applied to traffic studies, including the development of network-wide control strategies, network partitioning, performance evaluation, and road pricing. This work also presents future extensions and research directions for MFD-based traffic modelling and applications.     

A systematic analysis of multimodal transport systems with road space distribution and responsive bus service

A smart design of transport systems involves efficient use and allocation of the limited urban road capacity in the multimodal environment. This paper intends to understand the system-wide effect of dividing the road space to the private and public transport modes and how the public transport service provider responds to the space changes. To this end, the bimodal dynamic user equilibrium is formulated for separated road space. The Macroscopic Fundamental Diagram (MFD) model is employed to depict the dynamics of the automobile traffic for its state-dependent feature, its inclusion of hypercongestion, and its advantage of capturing network topology. The delay of a bus trip depends on the running speed which is in turn affected by bus lane capacity and ridership. Within the proposed bimodal framework, the steady-state equilibrium traffic characteristics and the optimal bus fare and service frequency are analytically derived. The counter-intuitive properties of traffic condition, modal split, and behavior of bus operator in the hypercongestion are identified. To understand the interaction between the transport authority (for system benefit maximization) and the bus operator (for its own benefit maximization), we examine how the bus operator responds to space changes and how the system benefit is influenced with the road space allocation. With responsive bus service, the condition, under which expanding bus lane capacity is beneficial to the system as a whole, has been analytically established. Then the model is applied to the dynamic framework where the space allocation changes with varying demand and demand-responsive bus service. We compare the optimal bus services under different economic objectives, evaluate the system performance of the bimodal network, and explore the dynamic space allocation strategy for the sake of social welfare maximization.     

Logistical restructuring and road freight traffic growth

The forecasting of road freight traffic has relied heavily on the close correlation between GDP and road tonne-kilometers. It has not been rooted in an understanding of the causes of freight traffic growth. The research reported in this paper has investigated this process of traffic growth in two ways: first, by analysing official data on the production, consumption and movement of food and drink products, and second, by conducting a survey of the changing freight transport requirements of 88 large British-based manufacturers.The analysis of secondary data shows how, in the food and drink sector, the relationship between the real value of output and road vehicle-kms hinges on four key parameters: value density, handling factor, average length of haul and consignment size. An attempt is made to explain variations in these parameters.The survey of manufacturers suggests that the growth of lorry traffic is the net result of a complex interaction between factors operating at four levels of logistical management: strategic planning of logistical systems, choice of suppliers and distributors, scheduling of product flow and the management of transport resources. Changes in the frequency and scheduling of freight deliveries in response to tightening customer service requirements and just-in-time management appear to have become a more prevalent cause of freight traffic growth than the physical restructuring of logistical systems. Manufacturers anticipate that their road freight demand will broadly increase in line with sales and be largely unaffected by road transport cost increases at the levels currently proposed. The paper concludes by examining their likely reactions to a much sharper increase in the cost of road freight movement.     

Including congestion effects in urban road traffic CO2 emissions modelling: Do Local Government Authorities have the right options?

Tailpipe emissions from vehicles on urban road networks have damaging impacts, with the problem exacerbated by the common occurrence of congestion. This article focuses on carbon dioxide because it is the largest constituent of road traffic greenhouse gas emissions. Local Government Authorities (LGAs) are typically responsible for facilitating mitigation of these emissions, and critical to this task is the ability to assess the impact of transport interventions on road traffic emissions for a whole network.This article presents a contemporary review of literature concerning road traffic data and its use by LGAs in emissions models (EMs). Emphasis on the practicalities of using data readily available to LGAs to estimate network level emissions and inform effective policy is a relatively new research area, and this article summarises achievements so far. Results of the literature review indicate that readily available data are aggregated at traffic level rather than disaggregated at individual vehicle level. Hence, a hypothesis is put forward that optimal EM complexity is one using traffic variables as inputs, allowing LGAs to capture the influence of congestion whilst avoiding the complexity of detailed EMs that estimate emissions at vehicle level.Existing methodologies for estimating network emissions based on traffic variables typically have limitations. Conclusions are that LGAs do not necessarily have the right options, and that more research in this domain is required, both to quantify accuracy and to further develop EMs that explicitly include congestion, whilst remaining within LGA resource constraints.     

Road pricing — an outsider's view of American experiences

Abstract

Substantial changes in urban transport policy have taken place over the past decade. The concern with expanding infrastructure and the preoccupation with providing sufficient road capacity to meet the increasing demand of unrestricted car use, which characterized transport policy in the 1950s and 1960s, has gradually given way to the idea that there is a need to restrain motor traffic if urban society is to function efficiently. A variety of restrictive physical traffic management, land use planning and economic policies have, in consequence, been pursued. One option which has attracted considerable attention in the academic literature, but which has been received more cooly by policy‐makers, is the possibility of optimizing urban traffic congestion through the imposition of road pricing. The introduction and relative success of the area licensing scheme in Singapore has added fuel to the arguments of the advocates of such a policy. This review is not directly concerned with either the experiment with road pricing in Singapore nor the theoretical debates which have taken place concerning the potential merits and defects of such policies but rather looks at the applied work in the United States which has looked into the practical implications of road pricing for its cities. Further, it seeks to explore, again drawing on American experiences, just why there has been so much opposition to the employment of economic pricing principles in the urban road transport market. The author presents the results of an SSRC sponsored study into the practical problems of introducing road pricing to cities in the United States.     

Estimating traffic demand risk – A multiscale analysis

This paper proposes a novel method for estimating the traffic demand risk associated with transportation. Using mathematical properties of wavelets, we develop a statistical measure of traffic demand sensitivity with respect to GDP. This measure can be adapted in a flexible way to capture risk levels relevant for different investment horizons. We demonstrate the timescale decomposition of risk with Swedish traffic demand data for 1950–2005. In general, rail transport shows a stronger co-movement with GDP than road transport. Moreover, we examine the volatility exhibited by traffic demand. Our findings suggest that rail investments are more risky than road investments. Since the findings can be used for optimal investment timing and for choice between public investment alternatives, they are deemed important for public policy in general.     

Do Road Planners Produce More ‘Honest Numbers’ than Rail Planners? An Analysis of Accuracy in Road‐traffic Forecasts in Cities versus Peripheral Regions

Abstract

Based on a review of available data from a database on large‐scale transport infrastructure projects, this paper investigates the hypothesis that traffic forecasts for road links in Europe are geographically biased with underestimated traffic volumes in metropolitan areas and overestimated traffic volumes in remote regions. The present data do not support this hypothesis. Since previous studies have shown a strong tendency to overestimated forecasts of the number of passengers on new rail projects, it could be speculated that road planners are more skilful and/or honest than rail planners. However, during the period when the investigated projects were planned (up to the late 1980s), there were hardly any strong incentives for road planners to make biased forecasts in order to place their projects in a more flattering light. Future research might uncover whether the change from the ‘predict and provide’ paradigm to ‘predict and prevent’ occurring in some European countries in the 1990s has influenced the accuracy of road traffic forecasts in metropolitan areas.     

Road Traffic Demand Elasticity Estimates: A Review

A brief summary of road traffic‐related elasticity estimates as reported in the international literature is given. An indication of the orders of magnitude of these elasticities is outlined and the variation in estimates commonly found is emphasized. The results of previous extensive surveys are collated, but a wider scope of traffic‐related research is provided by reviewing recent work and including research that has received less attention. A variety of elasticity measures related to car travel, car ownership, freight traffic and fuel demand are reported. Based on the review, some important themes underpinning the demand for road traffic are revealed.     

An assessment of the performance of the European long intermodal freight trains (LIFTS)

Intermodal rail/road freight transport has always been considered as a competitive alternative to its road freight counterpart in the European medium- to long-distance corridors (markets). Such consideration has been based on the increasing competitiveness of some innovative rail services and the existing and prospective performance of both modes in terms of the full social – internal or operational and external – costs. The most recent innovation of rail technologies and related services launched by some European railway companies, still at the conceptual level, is the Long Intermodal Freight Train (LIFT). This is supposed to be a block train operating in long-distance corridors (markets) with a substantial and regular freight demand.This paper develops analytical models for assessing the performance of the LIFTs, the already-operating Conventional Intermodal Freight Trains (CIFTs), and their road counterpart as well. The performance consists of the full – internal (private) and external – costs of the door-to-door delivery of loading units – containers, swap-bodies, and semi-trailers. The internal costs embrace the operational costs of the transport (rail and road) and intermodal terminal operators. The external costs include the costs of the impacts of door-to-door delivery of loading units on society and the environment. These negative externalities include noise, air pollution, traffic accidents, and congestion.The models are applied to a simplified version of intermodal and road transport system using inputs from the European freight transport sector. The aims are to compare the full costs of particular modalities in order to investigate the potential of the LIFTs as compared with the CIFTs in improving the internal efficiency of the rail freight sector and its competitiveness with respect to its road counterpart. In addition, the paper attempts to assess some effects on the potential modal shift of EU (European Union) transport policies on internalizing transport externalities.     

Singapore motorisation restraint and its implications on travel behaviour and urban sustainability

The example of Singapore shows that rapid urban and economic growth does not have to bring traffic congestion and pollution. Singapore has chosen to restrain car traffic demand due to its limited land supply. Transport policy based on balanced development of road and transit infrastructure and restraint of traffic has been consistently implemented for the past 30 years. Combined with land use planning, it resulted in a modern transport system, which is free from major congestion and provides users with different travel alternatives. As the economic growth caused a substantial increase in demand for cars, several pricing policies were introduced with the aim of restraining car ownership and usage. Growth of the vehicle population is now controlled and potentially congested roads are subject to road pricing. These measures help to keep the roads free from major congestion, maintain car share of work trips below 25% and keep the transport energy usage low. Although Singapore conditions are in many aspects unique, its travel demand experience can provide useful lessons for other rapidly growing cities in Asia.

Transformation of transport policy in Great Britain

The British Government recently issued a white paper on its future transport strategy. Its central precept is unambiguous: current trends in traffic are unsustainable, from the point of view of the environment, business efficiency, health, and the unfeasibility of providing growth in road capacity that would keep pace with predicted growth in traffic. Much of the policy logic in the white paper stems from the explicit abandonment of `predict-and-provide' as a desirable — or possible — strategy. This leads to a recognition of the importance of a co-ordinated approach to public transport, walking and cycling, together with policies aimed at reducing less necessary travel where possible; ensuring that the costs of congestion and environmental pollution are, as far as practical, met by those who cause them (in which the revenue from new pricing systems would be kept under local control and used for transport improvements); an emphasis on better maintenance and management of the road system rather than increasing its capacity; consideration of the effects on transport of other policies in land-use, health, education etc; development of institutional structures or contractual arrangements able to bring these changes about; and conditions in which people's everyday behaviour and attitudes may be in harmony with policy, finance and environmental constraints. These themes did not arise out of the blue following the general election in 1997. They evolved over many years, especially in nearly ten years of intense discussion connected with the previous two governments' recognition that the 1989 road programme (`Roads to Prosperity'), in spite of its size and expense, would still not be nearly sufficient to keep pace with traffic growth, as well as being environmentally damaging. The process of discussion and argument has not ceased with publication of the white paper. A very interesting feature of the current debate is that its central argument is widely (though not unanimously) accepted in the media, with great emphasis on the problems of implementation. The author argues that the policy shift is genuine and firmly grounded in research, though with a number of real problems in implementation, research and methodology that will have to be addressed.     

Empirical evidence on induced traffic

Disparate evidence indicates that the provision of extra road capacity results in a greater volume of traffic. The amount of extra traffic must be heavily dependent on the context, size and location of road schemes, but an appropriate average value is given by an elasticity of traffic volume with respect to travel time of about –0.5 in the short term, and up to –1.0 in the long term. As a result, an average road improvement has induced an additional 10% of base traffic in the short term and 20% in the long term: individual schemes with induced traffic at double this level may not be very unusual, especially for peak periods. Induced traffic is particularly seen on the alternative routes that road improvements are intended to relieve.     

Assessing the importance of transportation activity data for urban emission inventories

The aim of this research is the implementation of a GPS-based modelling approach for improving the characterization of vehicle speed spatial variation within urban areas, and a comparison of the resulting emissions with a widely used approach to emission inventory compiling. The ultimate goal of this study is to evaluate and understand the importance of activity data for improving the road transport emission inventory in urban areas. For this purpose, three numerical tools, namely, (i) the microsimulation traffic model (VISSIM); (ii) the mesoscopic emissions model (TREM); and (iii) the air quality model (URBAIR), were linked and applied to a medium-sized European city (Aveiro, Portugal). As an alternative, traffic emissions based on a widely used approach are calculated by assuming a vehicle speed value according to driving mode. The detailed GPS-based modelling approach results in lower total road traffic emissions for the urban area (7.9, 5.4, 4.6 and 3.2% of the total PM10, NO_x, CO and VOC daily emissions, respectively). Moreover, an important variation of emissions was observed for all pollutants when analysing the magnitude of the 5th and 95th percentile emission values for the entire urban area, ranging from −15 to 49% for CO, −14 to 31% for VOC, −19 to 46% for NO_x and −22 to 52% for PM10. The proposed GPS-based approach reveals the benefits of addressing the spatial and temporal variability of the vehicle speed within urban areas in comparison with vehicle speed data aggregated by a driving mode, demonstrating its usefulness in quantifying and reducing the uncertainty of road transport inventories.     

Induced traffic: what do transportation models tell us?

Mathematical models of transportation systems have played a prominent role in transportation planning throughout the world since the 1960s. These models are hypotheses of how people use transport systems. They provide a means of extrapolating the necessarily limited empirical evidence of how road users respond to changes in the road system. However, it needs to be recognised that these extrapolations rely for their validity on the realism of the underlying theories; transportation models can only tell us about the relationships actually built into them.This paper reviews the limited number of studies undertaken mainly in the UK in which calibrated transportation models have been used in a systematic way to give some insight into the relative importance of the various components of induced traffic. These studies include analyses of the effects of road schemes using: a theoretical single link model; conventional four-stage transportation models of Cardiff and Belfast; elasticity models in Cardiff, Belfast, West London and Norwich; land-use interaction models in Leeds, Bilbao, Dortmund; and a model of land-use effects in Norwich. The results tell us two things: (a) the scale of the various elements of induced traffic, and (b) the implications for the economic benefits of road schemes.     

Network effects of intelligent speed adaptation systems

Intelligent Speed Adaptation (ISA) systems use in-vehicle electronic devices to enable the speed of vehicles to be regulated automatically. They are increasingly appreciated as a flexible method for speed management and control particularly in urban areas. On-road trials using a small numbers of ISA equipped vehicles have been carried out in Sweden, the Netherlands, Spain and the UK. This paper describes the developments made to enhance a traffic microsimulation model in order to represent ISA implemented across a network and the impact of this on the networks. The simulation modelling of the control system is carried out on a real-world urban network, and the impacts on traffic congestion, speed distribution and the environment assessed. The results show that ISA systems are more effective in less congested traffic conditions. Momentary high speeds in traffic are effectively suppressed, resulting in a reduction in speed variation which is likely to have a beneficial impact on safety. Whilst ISA reduces excessive traffic speeds in the network, it does not affect average journey times. In particular, the total vehicle-hours travelling at speeds below 10 km/hr have not changed, indicating that the speed control had not induced more slow-moving queues to the network. A statistically significant, eight percent, reduction in fuel consumption was found with full ISA penetration. These results are in accordance with those from field trials and they provide the basis for cost-benefit analyses on introducing ISA into the vehicle fleet. However, contrary to earlier findings from the Swedish ISA road trials, this study suggested that ISA is likely to have no significant effect on emission of gaseous pollutants CO, NO_x and HC.     

A dynamic approach to road freight flows modeling in Spain

This paper presents an innovative approach to analyzing road vehicle freight traffic that uses a dynamic panel data specification derived from a gravity model. This dynamic approach, which has recently been employed in international goods trade models in lieu of the traditional static specification, is applied to the case of Spain using data for the countrys 15 NUTS-3 regions between 1999 and 2009. Using the system general method of moments approach, we obtained significant evidence that the flow of vehicles carrying commodities by road has a strong persistence effect when controlling for unobserved heterogeneity. We also found that the quality of road transport infrastructure has a significant impact on vehicle trips. According to our findings, we suggest that this type of specification be employed in distribution models in which fixed effects and lags of the dependent variable are included to account for unobserved heterogeneity and persistence effects, respectively.