Modelling inter-urban transport flows in Italy: A comparison between neural network analysis and logit analysis

In the present paper a modal split problem is analysed by means of two competing statistical models, the traditional logit model and the new technique for information processing, viz. the feedforward neural network model. This study aims to explore the modal split between rail and road transport modes in Italy in relation to the introduction of a new technological innovation, the new High-Speed Train. The paper is sub-divided into two major parts. The first part offers some general considerations on the use of neural networks in the light of the increasing number of empirical applications in the specific area of transport economics. The second part describes the Italian case study by using the two above mentioned statistical models. The results highlights the fact that the two adopted models, although methodologically different, are both able to provide a reasonable spatial forecasting of the phenomenon studied. In particular, the neural network model turns out to have a slightly better performance, even though there are still critical problems inherent in its application.     

Modal split in offshore supply network under the objective of emissions minimization

We study modal split under the objective of emissions minimization in the transportation of cargo from centralized vendors in the oil and gas industry to decentralized supply bases on the Norwegian coast. The supply network includes direct road transport and a sea route along the coast. To gain insight into modal split decisions between road and sea transport from the shipper’s perspective multi-period mixed integer optimization models are formulated. Particularly the models give possibilities to examine how weekly demand patterns at supply bases, cargo commitments to sea transport, storage possibilities at supply bases, and shipper’s responsibility for a certain share of vessel capacity may effect the emissions and the modal split. Experiments on real data from an oil and gas company operating offshore show that the size of the share of vessel capacity and the possibility for storage at supply bases are the major determinants for a larger shift to environmentally friendly sea transport. The models can be used as means for making decisions regarding how a shipper can commit to sea transport to achieve less emissions.     

Determinants of modal choice in freight transport

In the next few years, exciting developments in the field of freight transport are likely to occur. The Channel Tunnel will be perceived as giving railways much greater distance of operation, compared to the current train ferry to/from Great Britain. The further development of swap-body technology will allow easier modal transfer and the creation, in 1992, of a single market in Europe will transform the pattern of trade. All of these are likely to have significant impacts on modal choice, and hence modal split, in freight transport. Reappraisal by many firms of the modes of transport used is likely but will it result in a net transfer of freight from road to rail and, if so, to what extent? To answer such questions, an accurate and reliable method of predicting modal split is required. Research in the past has concentrated on the development of modal split models based on generalised costs. These fail to explain adequately the prevalence of road freight in the UK. From surveys of freight managers within industry, it is clear that models to date rely too heavily on the economic cost factor and too little on behavioural factors (Jeffs 1985). This paper derives from a recent study of freight transport modal choice from the standpoint of the transport decision-maker within the firm. It attempts to shed light on the actual parameters which should be incorporated into a modal split model. Many variables appear to exert an influence on modal choice decision-making process. However, it is possible to categorise them into six main groups, namely: customer-requirements; product-characteristics; company structure/organisation; government interventions; available transport facilities; and perceptions of the decision-maker him/herself. It is the interactions and inter-relationships between these which ultimately determine freight modal split. This study has shown that the relationship between the outcome of the transport decision process and the values of particular determinants of modal split is not straight-forward, due to the complexity and variety of interactions involved. Perhaps one of the main reasons for researchers' failure hitherto to develop a successful modal-split model has been the preoccupation with techniques that rely on the development of common metric (e.g. generalised cost), which has led to the exclusion of some important explanatory variables along quite different dimensions. Another important issue concerns the appropriate level of aggregation. In order not to reduce the explanatory power of the key variables, it is important to work at a disaggregate level, although this does make substantial demands on data. The use of factor analysis enables both the aggregation of information without loss of behavioural reality and the specification of variables in terms of a common metric. In conclusion, freight transport has usually been examined within too narrow a framework. It must be placed firmly within the context of the total industrial process. The demand for freight transport is directly influenced by the level, composition and geographical distribution of production and consumption activities. Freight flows are complex and so it is highly unlikely that a universal mode-choice model can ever be developed. Future research should, therefore, be directed towards developing partial models in response to specific needs of those involved in decision-taking in the freight sector.     

A simulation tool for bicycle sharing systems in multimodal networks

This paper presents a methodology for modelling an urban transport system, integrating public bicycles in a multi-modal network. A bike cost function that reproduces the effect of slopes on cycling speeds is proposed. Also, the effect of traffic levels on the attractiveness of cycling routes is taken into account. The model applies the modal split and network assignment phases in a multimodal network with different classes of users. It has been verified over a test network and then validated by applying it to a real case in the city of Santander in Spain. The results obtained make this model a useful decision-making tool to encourage the use of the public bicycle from a sustainable development point of view.     

Achieving transport modal split targets at intermodal freight hubs using a model predictive approach

The increase of international freight commerce is creating pressure on the existing transport network. Cooperation between the different transport parties (e.g., terminal managers, forwarders and transport providers) is required to increase the network throughput using the same infrastructure. The intermodal hubs are locations where cargo is stored and can switch transport modality while approaching the final destination. Decisions regarding cargo assignment are based on cargo properties. Cargo properties can be fixed (e.g., destination, volume, weight) or time varying (remaining time until due time or goods expiration date). The intermodal hub manager, with access to certain cargo information, can promote cooperation with and among different transport providers that pick up and deliver cargo at the hub. In this paper, cargo evolution at intermodal hubs is modeled based on a mass balance, taking into account hub cargo inflows and outflows, plus an update of the remaining time until cargo due time. Using this model, written in a state-space representation, we propose a model predictive approach to address the Modal Split Aware – Cargo Assignment Problem (MSA–CAP). The MSA–CAP concerns the cargo assignment to the available transport capacity such that the final destination can be reached on time while taking into consideration the transport modality used. The model predictive approach can anticipate cargo peaks at the hub and assigns cargo in advance, following a push of cargo towards the final destination approach. Through the addition of a modal split constraint it is possible to guide the daily cargo assignment to achieve a transport modal split target over a defined period of time. Numerical experiments illustrate the validity of these statements.     

A bi-level programming for bus lane network design

This paper proposes a bi-level programming model to solve the design problem for bus lane distribution in multi-modal transport networks. The upper level model aims at minimizing the average travel time of travelers, as well as minimizing the difference of passengers’ comfort among all the bus lines by optimizing bus frequencies. The lower level model is a multi-modal transport network equilibrium model for the joint modal split/traffic assignment problem. The column generation algorithm, the branch-and-bound algorithm and the method of successive averages are comprehensively applied in this paper for the solution of the bi-level model. A simple numerical test and an empirical test based on Dalian economic zone are employed to validate the proposed model. The results show that the bi-level model performs well with regard to the objective of reducing travel time costs for all travelers and balancing transit service level among all bus lines.     

Impact assessment of extreme weather events on transport networks: A data-driven approach

The present paper presents a data-driven method for assessing the resilience of the European passenger transport network during extreme weather events. The method aims to fill in the gap of current research efforts regarding the quantification of impacts attributed to climate change and the identification of substitutability opportunities between transport modes in case of extreme weather events (EWE). The proposed method consists of three steps concerning the probability estimation of an EWE occurring within a transportation network, the assessment of its impacts and the passengers’ flow shift between various transport modes. A mathematical formulation for the proposed data-driven method is provided and applied in an indicative European small-scale network, in order to assess the impacts of EWE on modal choice. Results are expressed in passenger differentiated flows and the paper concludes with future research steps and directions.     

Reducing average comprehensive travel cost by rationally allocating trips to different travel modes

To study the effect of different transport policies on reducing the average comprehensive travel cost (CTC) of all travel modes, by increasing public transport modal share and decreasing car trips, an optimization model is developed based on travel cost utility. A nested logit model is applied to analyze trip modal split. A Genetic Algorithm is then used to determine the implementation of optimal solutions in which various transport policies are applied in order to reduce average CTC. The central urban region of Beijing is selected as the study area in this research. Different policies are analyzed for comparison, focusing on their optimal impacts on minimizing the average CTC utility of all travel modes by rationally allocating trips to different travel modes in the study area. It is found that the proposed optimization model provides a reasonable indication of the effect of policies applied.     

Effects of built environment on walking at the neighbourhood scale. A new role for street networks by modelling their configurational accessibility?

The hypothesis of this paper is that some features of the built environment, particularly those concerned with the accessibility of the street network, could be associated with the proportion of pedestrians on all trips (modal split) found in different parts of a city. Quantitative analysis (bi-variate correlation and a multiple regression model) was used to establish the association between variables. The study area covered a substantial part of the metropolitan area in Madrid, Spain. Results showed a consistent influence of five particular indexes in the multi-variate model. Not surprisingly for this kind of research, four of them described density and mix of land uses. But perhaps more interestingly, the first one was a measure of the accessibility of the public space network, a less prominent variable in literature to date. This variable is called herein configurational accessibility, calculated using Space Syntax, an urban morphology theory. The relevance of configurational accessibility is probably related to its surprising ability to synthesize global and perceived properties of street networks at the same time. The findings introduce the idea that the configuration of the urban grid can influence the proportion of pedestrians (as a part of total trips in any transport mode) who choose to walk on single-journey trips. The discussion links with the current debate about walkability indexes and the need of empirical support for the chosen variables and also with transport planning. Because the relevance of the street network’s role is not so easy to grasp, inputs from configurational theory and the pedestrian potential underlying this fact are also discussed at the end of the paper.     

Patterns of car usage and restraint modelling

Transport demand forecasting procedures have traditionally employed household based modal split models implicitly assuming a selection of mode for each trip based on relative generalised cost. A detailed examination of the trip patterns of a sample of household in West Yorkshire shows that in fact there is little discretionary choice of public transport; public transport trips in car owning households generally being explained in terms of the specific unavailability of the car for such trips. Two versions of a category analysis model for modal split are based on this observation and applied to household data for Glamorgan and Monmouthshire to show that such a procedure is workable and produces results comparing favourably with traditional approaches. The likely implications of three types of restraint policy are examined and it is concluded that the existing interdependence in trip patterns and modal choice within the household is of great significance in determining their effects. In particular it appears that positive attempts to increase vehicle occupancy at the peak are likely to be more favourable to public transport finances than the more negative policies to restrain use of the car for journey to work, or second car ownership.     

Transport in Tokyo

This paper gives a review of the historical and geographical preconditions as well as of the population and economic development which led to the unique and complex transport systems of Tokyo. Tokyo Metropolis, one of the most populous cities in the world, is located in the National Capital Region of Japan where 32 million people are living today. The special transport problems deriving from this high population density are described in context with the development of employment, transport infrastructure and motorization. Due consideration is given to the influence exerted by the structure of the whole region on the overall traffic behaviour.

Several transport phenomena and problem solutions which are typical of the traffic systems in Tokyo are described, such as the change of rush hour congestion rates depending on subway extension, modal split for different trip purposes in the inner urban area, or information via local radio broadcasts with very short range of transmission.

The main current transport issues are discussed. Though the transport networks in Tokyo are some of the most developed in the world, there is still heavy congestion in rush hours. The basic policy therefore is the further strengthening and improvement of the public transport network.     

Impacts of combining partial and general equilibrium modelling in freight transport analyses – a forest sector case study from Norway

Abstract

The forest sector in Norway is very transport intensive, accounting for approximately 14% of total domestic freight transport traffic on Norwegian roads. This paper presents an analysis linking a general equilibrium freight transport modelling tool with a partial equilibrium model of the forest sector. The freight transport model predicts transport costs, modal split and transport patterns, and the results are treated as inputs to the forest sector model. The objective of the paper is to analyse the modelling effect of taking forest sector model effects back into the freight transport model and treated as new demand. Compared to a base scenario for the year 2020, we compare analyses with and without this new demand from the forest sector model back into the freight transport modelling tool.     

Bottleneck congestion pricing and modal split: Redistribution of toll revenue

The paper examines the question of the redistribution of toll revenue as seen in a bottleneck congestion model. Our objective is to analyse the impact of this redistribution on total cost and on modal split between railroad and road. Following Tabuchi’s two-mode model (Tabuchi, T., 1993. Bottleneck congestion and modal split. Journal of Urban Economics 34, 414-431.), we integrate a redistribution of toll revenue towards public transport into our study. In this context, we investigate two kinds of road toll regimes: a fine toll and a uniform toll. We will consider two types of railroad fare: when it is set equal to the marginal cost and when it is set equal to average cost. These models allow us to show that toll policy to be more efficient as long as toll revenue is directed towards public transport when the railroad fare is equal to average cost.     

Integrating congestion pricing,transit subsidies and mode choice

We model and analyze optimal (welfare maximizing) prices and design of transport services in a bimodal context. Car congestion and transit design are simultaneously introduced and consumers choose based on the full price they perceive. The optimization variables are the congestion toll, the transit fare (and hence the level of subsidies) and transit frequency. We obtain six main results: (i) the optimal car-transit split is generally different from the total cost minimizing one; (ii) optimal congestion and transit price are interdependent and have an optimal frequency attached; (iii) the optimal money price difference together with the optimal frequency yield the optimal modal split; (iv) if this modal split is used in traditional stand-alone formulations – where each mode is priced independently–resulting congestion tolls and transit subsidies and fares are consistent with the optimal money price difference; (v) self-financing of the transport sector is feasible; and (vi) investment in car infrastructure induces an increase in generalized cost for all public transport users.     

Modal-split effects of climate change: The effect of low water levels on the competitive position of inland waterway transport in the river Rhine area

Future climate change is expected to affect inland waterway transport in most main natural waterways in Europe. For the river Rhine it is expected that, in summer, more and longer periods with low water levels will occur. In periods of low water levels inland waterway vessels have to reduce their load factors and, as a result, transport prices per tonne will increase. One possible consequence of these higher transport prices is a deterioration of the competitive position of inland waterway transport compared with rail and road transport, and thus a change in modal split. We study this issue using a GIS-based software model called NODUS which provides a tool for the detailed analysis of freight transportation over extensive multimodal networks. We assess the effect of low water levels on the costs of transport operations for inland waterway transport in North West Europe under several climate scenarios. It turns out, that the effect on the modal split is limited. Under the most extreme climate scenario, inland waterway transport would lose about 5.4% of the quantity that is currently being transported annually in the part of the European inland waterway transport market considered. The very dry year of 2003 can be seen as an analogue for this scenario.     

Breakthrough innovations in intermodal freight transport

Breakthrough innovations, whether technological, organizational or both, are a necessity if the market share of intermodal freight transport is to expand. The main growth potential lies in the markets for flows over short distances, for perishable and high-value commodities, for small consignments, and for flows that demand speed, reliability and flexibility. It will take radical innovations to produce a breakthrough in the modal split and allow these new markets to be conquered. This special issue is based on papers presented at an international conference on freight transport automation and multimodality, held in Delft in May 2002, that are illustrative of the direction of breakthrough research and development (R&D) aimed at increasing the market share for intermodal transport.     

Excess commuting and modal choice

This paper reports results from research conducted to analyse the extent of excess commuting in Dublin, Ireland. The research differs from similar studies on excess commuting in two ways. First, a disaggregate modal choice analysis of excess commuting is undertaken for two time periods – 1991 and 2001. Second, sensitivity analysis is undertaken to explore the impact of changes in the density of the transport network for users of public and private transport. The results suggest that excess commuting is considerably greater for users of private transport implying the greater inefficiency of commuting associated with that mode. By way of contrast, capacity utilisation measures suggest the opposite indicating the difficulty of using these measures for policy-making. The results suggest also that the greater inter-mixing of jobs–housing functions has facilitated reductions in actual commuting costs as well as increasing the range of available trip possibilities over the study period. In terms of the sensitivity analysis, the results suggest that public transport users could achieve dramatic savings on their commute if the density of that network was increased considerably.     

The influence of habit formation on modal choice —a Heuristic model

Most modal split models have been based on the assumption of rational behaviour in an individual's choice evaluation of the generalised costs of modal alternatives. This paper integrates conceptual and empirical information from a wide range of sources and points towards an alternative way of looking at modal choice. The main conclusion is that the car is usually perceived as the superior mode for vehicular travel and that the potential user is committed to its use largely through the act of purchasing it. The conceptual structure of a sequential modal split model is outlined as one that is based on a four-stage decision-making framework which considers the role of learning and habit-formation. In the conclusion, the implications of this approach are considered in terms of the conventional modal split and trip generation submodels, and certain policy measures are assessed.     

A reliability‐based traffic assignment model for multi‐modal transport network under demand uncertainty

In densely populated and congested urban areas, the travel times in congested multi‐modal transport networks are generally varied and stochastic in practice. These stochastic travel times may be raised from day‐to‐day demand fluctuations and would affect travelers' route and mode choice behaviors according to their different expectations of on‐time arrival. In view of these, this paper presents a reliability‐based user equilibrium traffic assignment model for congested multi‐modal transport networks under demand uncertainty. The stochastic bus frequency due to the unstable travel time of bus route is explicitly considered. By the proposed model, travelers' route and mode choice behaviors are intensively explored. In addition, a stochastic state‐augmented multi‐modal transport network is adopted in this paper to effectively model probable transfers and non‐linear fare structures. A numerical example is given to illustrate the merits of the proposed model. Copyright © 2012 John Wiley & Sons, Ltd.     

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.