A Unified Framework for Selecting a Travel Demand Forecasting Model for Developing Countries

Abstract

The ability to judge and select a model that is appropriate for a particular application is considered to be one of the most important aspects in contemporary transport planning. However, there is no suitable procedure for the systematic selection of a model that is most appropriate for meeting the needs and requirements of a particular planning task. Although there is little literature on the criteria for model assessment and selection methodologies, none can support systematic evaluation of different models versus quality of obtainable data versus efforts for data provision. Such deficiencies support the need for further guidance on a model selection procedure for developing countries where efforts for data provision are highly susceptible to higher sampling and measurement errors. This study presents a unified framework for the systematic model selection process. Evaluation of the framework for a case study of Dar es Salaam city in Tanzania evidences its benefits and applicability.     

Travel patterns in Dutch metropolitan cities: The importance of external trips

Using a variety of data sources, decentralisation of population and employment in four Dutch urban areas (Amsterdam, Rotterdam, The Hague and Utrecht) over the last 20 years, is analysed. It is found that suburbanisation, plus an ever growing car share, has increased the number of external journeys related to the metropolitan cities enormously. With the use of the 1982 National Travel Survey, current travel patterns in and around the metropolitan cities are studied: the importance of external trips for urban transport planning shows clearly. They account for about half the number of city related car trips, and for nearly three quarters of the total vehicle kilometres of travel within the city.(requests for reprints)     

Environmental impacts of transformative land use and transport developments in the Greater Beijing Region: Insights from a new dynamic spatial equilibrium model

This paper reports the insights into environmental impacts of the ongoing transformative land use and transport developments in Greater Beijing, from a new suite of dynamic land use, spatial equilibrium and strategic transport models that is calibrated for medium to long term land use and transport predictions. The model tests are focused on urban passenger travel demand and associated emissions within the municipality of Beijing, accounting for Beijing’s land use and transport interactions with Tianjin, Hebei and beyond. The findings suggests that background trends of urbanization, economic growth and income rises will continue to be very powerful drivers for urban passenger travel demand across all main modes of transport beyond 2030. In order to achieve the dual policy aims for a moderately affluent and equitable nation and reducing the absolute levels of urban transport emissions by 2030, road charging and careful micro-level coordination between land use, built form and public transport provision may need to be considered together for policy implementation in the near future.     

Uncertainty in traffic forecasts: literature review and new results for The Netherlands

This paper provides a review of transport model applications that not only provide a central traffic forecast (or forecasts for a few scenarios), but also quantify the uncertainty in the traffic forecasts in the form of a confidence interval or related measures. Both uncertainty that results from using uncertain inputs (e.g. on income) and uncertainty in the model itself are treated. The paper goes on to describe the methods used and the results obtained for a case study in quantifying uncertainty in traffic forecasts in The Netherlands.

Workplace travel plans: can they be evaluated effectively by experts?

Employers are regularly involved in transport planning and characteristic workplace-oriented tools include: (1) travel plans for building projects, (2) mandatory travel plans, (3) subsidies to employers with an advanced travel plan and (4) best travel plan awards. In all cases, experts judge the level of car use. We argue that decision-makers might benefit from a multiple regression-based benchmark modelling tool that estimates the expected share of the car. In this paper, we estimate the share of car users in the commuting modal split at workplaces. However, since the amount of information available to experts differs, we gradually add information to the model to measure the impact of data availability. Without historic data on modal split, the current share can only be predicted moderately well, i.e. within a 20% range. Besides adding the past, results improve by using homogenous and regional subsamples. Nevertheless, quantitative analyses do not make expert knowledge obsolete.     

Transport emissions and travel behaviour: A critical review of recent European Union and UK policy initiatives

There are clear signs of a shift in the UK transport policy in response to concerns about the environmental impacts of road transport and anxieties about the implications of the projected future growth in demand.Much of the framework of UK transport policy is now determined at the overall European Union level. To date most European legislation and policy proposals have been concerned with reducing the specific externalities associated with the transport sector, with none of the measures involved likely to have more than a marginal impact on the growth in demand. The emerging research evidence suggests however that the private costs of car use in Europe may fall substantially short of its total social costs and there is an important emerging policy debate about how this gap might be closed.The UK has introduced a policy package designed to reduce the growth of car travel and its environmental impact, within which land-use planning measures feature prominently. The land-use policies, which to some extent represent a reassertion of many traditional UK planning policies, include: an emphasis on focussing new development in urban areas, increasing residential densities, strengthening the role of existing centres and improving provision for walking and cycling.A number of factors will constrain the effectiveness of the package in practice. There are also concerns about its impact on key environmental objectives, including air quality. There are important questions too about the welfare effects of increasing densities and about the wider impacts of the package on economic efficiency.     

Tradable credits for managing car travel: a review of empirical research and relevant behavioural approaches

Recently, there has been a surge of interest in Tradable Credits (TC) as an alternative measure to manage the growth of personal car use. This paper summarises the results and methodologies of studies that have sought to anticipate the behavioural responses to several proposed TC schemes that target personal travel. In a critical reflection on this work and in an attempt to inspire future research, we argue that future empirical studies on TC behaviours can greatly benefit from insights from the fields of behavioural economics and cognitive psychology. Therefore, in the second part of the paper, we bring together behavioural concepts from these fields that are relevant in a TC decision-making context. Based on observations from current TC studies and the behavioural mechanisms identified in the second part of the paper, we propose promising directions for future research on understanding the impact of TC on personal car travel.     

Machine learning applications in activity-travel behaviour research: a review

ABSTRACT

This paper reviews the activity-travel behaviour literature that employs Machine Learning (ML) techniques for empirical analysis and modelling. Machine Learning algorithms, which attempt to build intelligence utilizing the availability of large amounts of data, have emerged as powerful tools in the fields of pattern recognition and big data analysis. These techniques have been applied in activity-travel behaviour studies since the early ’90s when Artificial Neural Networks (ANN) were employed to model mode choice decisions. AMOS, an activity-based modelling system developed in the mid-’90s, has ANN at its core to model and predict individual responses to travel demand management measures. In the dawn of 2000, ALBATROSS, a comprehensive activity-based travel demand modelling system, was proposed by Arentze and Timmermans using Decision Trees. Since then researchers have been exploring ML techniques like Support Vector Machines (SVM), Decision Trees (DT), Neural Networks (NN), Bayes Classifiers, and more recently, Ensemble Learners to model and predict activity-travel behaviour. A large number of publications over the years and an upward trend in the number of published articles over time indicate that Machine Learning is a promising tool for activity-travel behaviour analysis and prediction. This article, first of its kind in the literature, reviews these studies and explores the trends in activity-travel behaviour research that apply ML techniques. The review finds that mode choice decisions have received wide attention in the literature on ML applications. It was observed that most of the studies identify the lack of interpretability as a serious shortcoming in ML techniques. However, very few studies have attempted to improve the interpretability of the models. Further, some studies report the importance of feature engineering in ML-based studies, but very few studies adopt feature engineering before model development. Spatiotemporal transferability of models is another issue that has received minimal attention in the literature. In the end, the paper discusses possible directions for future research in the area of activity-travel behaviour modelling using ML techniques.     

Car use,commuting and urban form in a rapidly growing city: evidence from Beijing

The links between urban form and travel behaviour have been widely studied in the field of travel demand management. However, the existing literature is dominated by case studies from the developed countries. A study of a city in a developing and industrialising country can add some fresh evidence to the debate on the impacts of urban form on travel patterns. Using household survey data from Beijing, this paper finds that aspects of urban form have significant effects on workers' car use and the duration of travel by car in journeys to work, while controlling for socio-economic factors and households’ preferences related to residential location. The sprawling patterns of land development play a negative role in reducing motorised commuting trips and shortening vehicle hours travelled in the current processes of rapid urban expansion and motorisation. Since urban sprawl is greatly influenced by growing market forces, the findings in this paper reveal the negative effects of regulation–liberation of land development management on travel behaviour modification.     

Big data in public transportation: a review of sources and methods

ABSTRACT

The collection of big data, as an alternative to traditional resource-intensive manual data collection approaches, has become significantly more feasible over the past decade. The availability of such data, coupled with more sophisticated predictive statistical techniques, has contributed to an increase in attention towards the application of these data, particularly for transportation analysis. Within the transportation literature, there is a growing emphasis on developing sources of commonly collected public transportation data into more powerful analytical tools. A commonly held belief is that application of big data to transportation problems will yield new insights previously unattainable through traditional transportation data sets. However, there exist many ambiguities related to what constitutes big data, the ethical implications of big data collection and application, and how to best utilize the emerging data sets. The existing literature exploring big data provides no clear and consistent definition. While the collection of big data has grown and its application in both research and practice continues to expand, there is a significant disparity between methods of analysis applied to such data. This paper summarizes the recent literature on sources of big data and commonly applied methods used in its application to public transportation problems. We assess predominant big data sources, most frequently studied topics, and methodologies employed. The literature suggests smart card and automated data are the two big data sources most frequently used by researchers to conduct public transit analyses. The studies reviewed indicate that big data has largely been used to understand transit users’ travel behavior and to assess public transit service quality. The techniques reported in the literature largely mirror those used with smaller data sets. The application of more advanced statistical methods, commonly associated with big data, has been limited to a small number of studies. In order to fully capture the value of big data, new approaches to analysis will be necessary.     

Peak period tolls: Precepts and prospects

This article presents the economic rationale for road pricing and provides some scale on the magnitude of peak period tolls that might be justified. It discusses the impacts of such tolls on congestion, air quality and economic development and suggests a long term strategy towards areawide implementation of peak period pricing. It discusses current trends which are increasing the likelihood for implementation of congestion pricing and toll roads in the future. In particular, it discusses some aspects of the 1991 Intermodal Surface Transportation Efficiency Act (ISTEA) which will eliminate some of the current restraints on congestion pricing and toll highways.Abbreviations ETC Electronic toll collection - FHWA Federal Highway Administration - HOV High occupancy vehicle - ISTEA Intermodal Surface Transportation Efficiency Act - LOS Level of service - TCM Transportation control measure - V/C Volume-to-capacity ratio - VMT Vehicle mile(s) of travel - vphpl Vehicles per hour per lane     

A traffic assignment model for a ridesharing transportation market

A nascent ridesharing industry is being enabled by new communication technologies and motivated by the many possible benefits, such as reduction in travel cost, pollution, and congestion. Understanding the complex relations between ridesharing and traffic congestion is a critical step in the evaluation of a ridesharing enterprise or of the convenience of regulatory policies or incentives to promote ridesharing. In this work, we propose a new traffic assignment model that explicitly represents ridesharing as a mode of transportation. The objective is to analyze how ridesharing impacts traffic congestion, how people can be motivated to participate in ridesharing, and, conversely, how congestion influences ridesharing, including ridesharing prices and the number of drivers and passengers. This model is built by combining a ridesharing market model with a classic elastic demand Wardrop traffic equilibrium model. Our computational results show that (i) the ridesharing base price influences the congestion level, (ii) within a certain price range, an increase in price may reduce the traffic congestion, and (iii) the utilization of ridesharing increases as the congestion increases. Copyright © 2014 John Wiley & Sons, Ltd.     

Strava Metro data for bicycle monitoring: a literature review

ABSTRACT

Monitoring bicycle trips is no longer limited to traditional sources, such as travel surveys and counts. Strava, a popular fitness tracker, continuously collects human movement trajectories, and its commercial data service, Strava Metro, has enriched bicycle research opportunities over the last five years. Accrued knowledge from colleagues who have already utilised Strava Metro data can be valuable for those seeking expanded monitoring options. To convey such knowledge, this paper synthesises a data overview, extensive literature review on how the data have been applied to deal with drivers’ bicycle-related issues, and implications for future work. The review results indicate that Strava Metro data have the potential—although finite—to be used to identify various travel patterns, estimate travel demand, analyse route choice, control for exposure in crash models, and assess air pollution exposure. However, several challenges, such as the under-representativeness of the general population, bias towards and away from certain groups, and lack of demographic and trip details at the individual level, prevent researchers from depending entirely on the new data source. Cross-use with other sources and validation of reliability with official data could enhance the potentiality.     

Determinants of new vehicle registrations in EU countries: a panel cointegration analysis

This paper investigates the determinants of new vehicle registrations in European Union (EU) countries by focusing on four particular segments – passenger cars, light commercial vehicles, commercial vehicles, and heavy commercial vehicles. A panel cointegration analysis for a panel of 13 EU countries during the period from January 1999 to August 2010 shows that new vehicle sales have long-run cointegration relations with vehicle prices, consumer confidence, income, interest rates, fuel prices, industrial production, and trade. More effective factors in determining new vehicle sales appear to be trade, interest rates, and industrial production.     

A traffic analysis zone definition: a new methodology and algorithm

This paper develops a comprehensive approach to the definition of transportation analysis zones (TAZ), and therein, presents a new methodology and algorithm for the definition of TAZ embedded in geographic information systems software, improves the base algorithm with several local algorithms, and comprehensively analyses the obtained results. The results obtained are then compared to these presently used in the transportation analysis process of the Lisbon Metropolitan Area. The proposed algorithm presents a new methodology for TAZ design based on a smoothed density surface of geocoded travel demand data. The algorithm aims to minimise the loss of information when moving from a continuous representation of the origin and destination of each trip to their discrete representations through zones, and focuses on the trade-off between the statistical precision, geographical error, and the percentage of intra-zonal trips of the resulting OD matrix. The results for the Lisbon Metropolitan Area case study suggest a significant improvement in OD matrix estimates compared to current transportation analysis practises based on administrative units.

Transportation planning for special events: a review of expo 86 in Vancouver

The authors examine the problems of transportation planning for special events such as Worlds Fairs, Olympic Games etc., and use as a case study the experiences gained at EXPO 86 in Vancouver. Results indicate that sufficient flexibility exists in the urban infrastructure to accommodate the transport access and parking requirements of major, short‐term special events.     

Time taken for residents to adopt a new public transport service: examining heterogeneity through duration modelling

When a new public transport service is introduced it would be valuable for public authorities, financing organisations and transport operators to know how long it will take for people to start to use the service and what factors influence this. This paper presents results from research analysing the time taken for residents living close to a new guided bus service to start to use (or adopt) the service. Data was obtained from a sample of residents on whether they used the new service and the number of weeks after the service was introduced before they first used it. Duration modelling has been used to analyse how the likelihood of starting to use the new service changes over time (after the introduction of the service) and to examine what factors influence this. It is found that residents who have not used the new service are increasingly unlikely to use it as time passes. Those residents gaining greater accessibility benefits from the new service are found to be quicker to use the service, although the size of this effect is modest compared to that of other between-resident differences. Allowance for the possibility that there existed a proportion of the sample that would never use the new service was tested using a split population model (SPD) model. The SPD model indicates that 36% of residents will never use the new service and is informative in differentiating factors that influence whether Route 20 is used and when it is used.

Toward regional transportation governance: a case study of Greater Vancouver

This paper discusses the evolving institutional structure and governance of transportation planning, policy development and transit delivery within one major North American city-region, the Greater Vancouver area. Various methods of transportation governance are explored from complete independence to full regional integration. The move away from a direct provincial role in transportation management to a greater regional transit authority is discussed and critiqued. This revised version was published online in June 2006 with corrections to the Cover Date.     

Parking management for promoting sustainable transport in urban neighbourhoods. A review of existing policies and challenges from a German perspective

ABSTRACT

The organisation of parking is a key challenge to more sustainable mobility in urban areas, as its pricing and availability affect the rates of private car ownership and use. However, changing parking policies is a challenging issue for local politicians and planners because residents frequently oppose changes or restrictions to conditions they have taken for granted such as on-street parking in a public space. The aim of this paper is firstly to assess how the parking policy of an urban neighbourhood can be structured to contribute to more sustainable mobility and to increase liveability in the neighbourhood. The second aim is to apply the policies reviewed to an example neighbourhood. For this purpose, we systematically reviewed academic literature and identified five types of relevant parking policies: (i) maximum parking requirements, (ii) physical detachment of residence and parking space, (iii) residential parking permits and the limitation of available parking space, (iv) performance-based pricing and (v) parking as a demand management strategy. We discovered that most research focuses on econometric models about parking and that studies rarely address the effects of parking on the quality of life in neighbourhoods. Therefore, we need further research regarding the relationship of parking and liveability. We conclude that for the implementation of such parking policies in an example neighbourhood, the municipality needs to develop a mobility vision for its city. It has to understand parking as a tool for transportation demand management to increase the acceptance of parking policy concepts and to avoid spillover problems. Finally, in the German case, as in most other countries, states and municipalities need to redesign their legal frameworks to be able to manage parking supply better and to react to changes related to digital developments and parking. The findings have implications for other European neighbourhoods regarding the transfer from research to local circumstances and applications for the whole city.     

Locating refuelling stations for alternative fuel vehicles: a review on models and applications

The recent concerns on environmental issues have expedited the technological development of alternative fuel vehicles (AFVs), but the deployment of AFVs still remains at the initial stage mainly because of the lack of refuelling facilities. Recognising this, researchers have conducted various studies, proposing a variety of approaches to strategically locating refuelling stations. This paper presents a comprehensive review of the approaches, focusing more on applications than computational issues. The review identifies two main elements of the approaches: location modelling and refuelling demand estimation. Examining how the elements were handled in refuelling location studies, this paper suggests that future refuelling location models should properly reflect the intricate and various perspectives of three major AFV stakeholders: drivers, government agencies and refuelling service providers. This study is expected to help researchers efficiently set up their refuelling location problems and identify critical factors for seeking the solutions.