Shared taxis: modelling the choice of a paratransit mode in Santiago de Chile

The shared taxi is a special public transport mode, typical of Chilean cities. It operates with cars offering a maximum capacity of four seats, a predefined coverage area and a route that is fixed in principle, but can be adapted to meet passengers’ needs. During a normal day in Santiago, almost 700,000 trips use shared taxis during one of their stages. This represents about 4% of the total trips made in the city, and this modal share increases in zones and periods with low Metro and bus coverage. This study is a first attempt at studying shared taxis as a relevant transport alternative, analysing its main attributes and modelling its demand. With this purpose, after an analysis of the network and its operation, a revealed preference survey (including perceptual indicators) was applied to public transport users in Santiago who had shared taxi as a feasible alternative. Results show a positive evaluation of the mode’s unique attributes, such as the possibility of travelling seated, reducing transfers and alighting at a convenient destination. The subjective valuation of the attributes derived from the models confirm the strong penalty assigned by Chilean users to alternatives implying transfers or increased walking times. The analysis also shows that studying the characteristics of shared taxi users is relevant in a discussion about its regulation and modernization, considering that, while it is desirable to preserve its positive attributes, this should be done in a context of efficient integration with the rest of the transport system.

     

Understanding variability,habit and the effect of long period activity plan in modal choices: a day to day,week to week analysis on panel data

Understanding variability in individual behaviour is crucial for the comprehension of travel patterns and for the development and evaluation of planning policies. But, with only one notable exception, there are no studies on the intrinsic variability in the individual preferences for mode choices in absence of external changes in the transport infrastructures. This requires using continuous panel data. Few papers have studied mode choice with continuous panel data but mainly focused on the panel correlation. In this work we use a six-week travel diary survey to study the intrinsic variability in the individual preferences for mode choices, the effect of long period plans and habitual behaviour in the daily mode choices. Mixed logit models are estimated that account for the above effects as well as for systematic and random heterogeneity over individual preferences and responses. We also account for correlation over several time periods. Our results suggest that individual tastes for time and cost are fairly stable but there is a significant systematic and random heterogeneity around these mean values and in the preferences for the different alternatives. We found that there is a strong inertia effect in mode choice that increases with (or is reinforced by) the number of time the same tour is repeated. The sequence of mode choice made is influenced by the duration of the activity and the weekly structure of the activities     

Interactive travel choices and traffic forecast in a doubly dynamical system with user inertia and information provision

This study models the joint evolution (over calendar time) of travelers’ departure time and mode choices, and the resulting traffic dynamics in a bi-modal transportation system. Specifically, we consider that, when adjusting their departure time and mode choices, travelers can learn from their past travel experiences as well as the traffic forecasts offered by the smart transport information provider/agency. At the same time, the transport agency can learn from historical data in updating traffic forecast from day to day. In other words, this study explicitly models and analyzes the dynamic interactions between transport users and traffic information provider. Besides, the impact of user inertia is taken into account in modeling the traffic dynamics. When exploring the convergence of the proposed model to the dynamic bi-modal commuting equilibrium, we find that appropriate traffic forecast can help the system converge to the user equilibrium. It is also found that user inertia might slow down the convergence speed of the day-to-day evolution model. Extensive sensitivity analysis is conducted to account for the impacts of inaccurate parameters adopted by the transport agency.     

A parking model hierarchy

The last decade has seen considerable developments in computer assisted design procedures which enable planners to investigate the impacts of changes in the transport system. These developments have become more available to analysts through the introduction of microcomputers and computer graphics. Unfortunately, the impacts of parking on the transport have not been incorporated explicitly in many of these models since their prime concern is the movement of traffic. Parking system design and policy analysis can, however, benefit greatly from these developments in computer technology and availability. The design of parking systems can be improved and the investigation of policy impacts can be trialed or refined prior to their introduction using microcomputer packages. This paper outlines some developments in these areas. More specifically, it outlines a hierarchy or microcomputer models and information systems that can investigate parking policy and study the level of service provided by parking systems.     

Choice of mode of transport for long-distance trips: Solving the problem of sparse data

Transport planning is usually based on models’ forecasts, but the reliability of their outputs depends so much on the quality of input-data they are fed with. Discrete-choice models are used to characterise travellers’ behaviour in choosing their transport mode. Their calibration process is usually based on data stemming from household survey campaigns. However, the modelling in multimodal and intermodal transport on an interurban level is far more complicated and costly than in the case of an urban area. An alternative way to reduce costs is achieved by designing a choice-based sampling strategy where household surveys are replaced by specific surveys for each transport mode. This strategy generates a non-random sample that has to be treated correctly during the estimation process. In principle, the sample does not represent population market quotas for each different transport option. Moreover, as a result of both physical and functional constraints, the survey period cannot cover all origin–destination pairs (O–D pairs) in an optimal way and, consequently, the above-mentioned bias also affects each different individual O–D pair or, at least, group of pairs. In order to overcome this problem, this study presents a new procedure derived from the introduction of maximum likelihood estimators. These estimators assume the original mode options in terms of population quotas and in terms of O–D groups of pairs. The procedure is based on the optimisation of an objective-function to correct the above-mentioned bias in a way similar to the estimators of samples based on different choice options. The method named DWELT estimates the parameters corresponding to each explanatory variable using mode shares for each O–D pair or group of pairs. DWELT has been successfully validated in the case study of the Madrid–Barcelona interurban corridor in Spain. This result allows to achieve a more flexible cheaper survey procedure for interurban transport planning activities. Therefore transport policy strategies could be better designed and tested with lower costs.     

The private and social cost efficiency of port hinterland container distribution through a regional logistics system

Increasingly, the debate on freight transport and logistics involves the challenge of sustainable development. Key objectives of sustainable or “green” freight logistics systems are the mitigation of negative environmental and human health effects of distribution operations and the realization of a major modal shift in transport preferences, while at the same time achieving internal generalized cost efficiency and quality of services. Pursuing these goals requires the introduction of a range of measures. These measures call for private and public actors to take up various initiatives and adopt policies. Usually, it is more effective to combine different actions into an integrated package of measures than to introduce single instruments in isolation.This article explores the nexus between sustainability and port hinterland container logistics. In particular, the methodology and results of an empirical analysis based on applications of a network programming tool called the “interport model” are presented and discussed. The model enables an examination of all possible effects on inland container flows and their associated internal and external costs due to public and private initiatives in the field of port hinterland container logistics. The empirical analysis aims to evaluate the impact of a set of simultaneous policy options and operational measures on the competitiveness and sustainability of hinterland multimodal distribution of import and export containers handled at the seaports of the Campania region located in Southern Italy. The loading units can transit through the dry port facilities (the so called “interports”) located in the same region and/or through extra regional railway terminals, before reaching their ultimate inland destinations or the seaports. The integrated package of measures simulated by means of the model includes: (i) infrastructure policy, (ii) improvements of rail services, (iii) regulatory changes in terms of customs authorizations and procedures, (iv) removal of technical and legal barriers to fair and non-discriminatory competition in the market of rail traction between regional seaports and interports, (v) new business models integrating container logistics operations between seaports and interports, and (vi) social marginal cost charging of transport operations. Once this package of instruments is introduced, higher private and social cost efficiency of port hinterland container distribution through the investigated regional logistics system can be achieved. For instance, it has been estimated an annual saving of the order of about 12,660 tonnes of CO₂ equivalent emissions from transport corresponding to an external cost reduction of 0.27 million euros from the observed real life situation, whereas the estimated saving in terms of air pollution (CO, NO_x, PM, SO₂, VOC) from transport is approximately 220 tonnes per year corresponding to an external benefit of 1.31 million euros.The most immediate priority appears to be the customs and intermodal logistics integration of seaports and interports by means of full implementation of the “extended gateway” concept as a way to increase the rail share of modal split and improve the overall cost efficiency of the system. In addition, the simultaneous introduction of a social marginal cost charging policy can contribute to make the regional interports a viable solution to expand the hinterland reach of the regional seaport cluster.     

Weather,transport mode choices and emotional travel experiences

With climate change high on the political agenda, weather has emerged as an important issue in travel behavioural research and urban planning. While various studies demonstrate profound effects of weather on travel behaviours, limited attention has been paid to subjective weather experiences and the psychological mechanisms that may (partially) underlie these effects. This paper integrates theoretical insights on outdoor thermal comfort, weather perceptions and emotional experiences in the context of travel behaviour. Drawing on unique panel travel diary data for 945 Greater Rotterdam respondents (The Netherlands), this paper aims to investigate how and to what extent weather conditions affect transport mode choices, outdoor thermal perceptions and emotional travel experiences. Our findings point out that observed dry, calm, sunny and warm but not too hot weather conditions stimulate cycling over other transport modes and – via mechanisms of thermal and mechanical comfort – lead to more pleasant emotions during travel. Overall, public transport users have less pleasant emotional experiences than users of other transport modes, while active mode users appear most weather sensitive. The theoretical contributions and empirical findings are discussed in the context of climate change and climate-sensitive urban planning.     

Urban public transport in Europe: Technology diffusion and market organisation

Technological change and incremental technology, at various levels, are believed to have played an important role in the success of urban public transport in Europe. In this paper, a historical overview of the evolution of different transport modes across different European cities is presented. Our major concern is with the processes of diffusion of urban transport modes in European cities and, in particular, with the factors, mainly of an economic nature, that may explain their rates of adoption across Europe. Among these factors, special attention is given to the role played by the dimension and organisation of public transport markets in the rates of adoption of different public transport modes. The main conclusion of the paper is that the success of the introduction of a new transport mode appeared to be mainly related to its ability to provide cheaper and more reliable transport services compared with previous transport modes, and that, in the case of the electric tram, this was achieved by transforming of the structure of the market relating to this urban transport mode into monopolies.     

Applying behavioural theories to studying the influence of climate change on young people’s future travel intentions

Transport policy in the UK is seeking to promote the development of low carbon transport technology and to encourage people to choose to use low carbon travel options. This paper draws on existing behavioural theories to study young people’s travel behaviour intentions and the influence on these from their knowledge of, and willingness to act on, climate change. The study involved a series of focus groups with young people aged 11-18 years, where attitudes to transport modes, attitudes towards climate change and travel behaviour intentions were discussed. Knowledge and values are established as the key determinants of young people’s attitudes and behaviour intentions towards transport in the context of climate change. More specifically it is established that young people’s values emphasise speed and freedom and that it is important to young people that the mode of transport they choose is reflective of the image they want to portray.     

Middle‐class Travel Patterns,Predispositions and Attitudes,and Present‐day Transport Policy in Bangkok,Thailand

Abstract

Middle‐class expansion and new consumption patterns have increasingly become an important focus of studies of the development and change in newly industrialized and middle‐income‐developing East and South East Asian countries. However, there is still a dearth of studies in the literature particularly focusing on middle‐class travel patterns, predispositions and transport policy preferences. Nor have the implications of these factors on current transport and land development policy been examined. The present exploratory study addresses this gap by examining three cases in Bangkok, Thailand, which in recent decades witnessed dramatic middle‐class expansion, an increase in private motor vehicle population, and spatial diffusion of middle‐class residences into lower‐density zones in the suburbs. By mainly employing a survey method of data‐gathering and quantitative research analysis, the paper discusses the following findings: (1) that middle‐class travel behaviour is characterized by a high dependence on private motor vehicle travel and ‘inward commuting’; (2) that middle‐class preferences for transport mode and attitudes about remedial policy options are generally protective of their members’ car‐dependence and ownership; and (3) that present policy measures of the Thai government on Bangkok transport perfectly fit and support exclusively middle‐ and upper‐class predispositions and stakes in mobility. These findings in a developing country city basically follow a similar profile to be found in middle‐class‐dominant transport patterns and urban form in a number of North American cities. This paper further argues that in a developing country city such as Bangkok, where marked social differentiation and the combined population of poor and low‐income classes still comprise almost half of the urban social landscape despite an expanding middle‐class, an adequate and good public transport system that also meets the former’s need for efficient mobility is an imperative.     

Evaluation of green wave policy in real-time railway traffic management

In order to face the expected growth of transport demand in the next years, several new traffic control policies have been proposed and analyzed both to generate timetables and to effectively manage the traffic in real-time. In this paper, a detailed optimization model is used to analyze one such policy, called green wave, which consists in letting trains wait at the stations to avoid speed profile modifications in open corridors. Such policy is expected to be especially effective when the corridors are the bottleneck of the network. However, there is a lack of quantitative studies on the real-time effects of using this policy. To this end, this work shows a comparison of the delays obtained when trains are allowed or not to change their speed profile in open corridors. An extensive computational study is described for two practical dispatching areas of the Dutch railway network.     

Longer-term changes in mode choice decisions in Chennai: a comparison between cross-sectional and dynamic models

The rapid and continuing changes in travel and mobility needs in India over the last decade necessitates the development and use of dynamic models for travel demand forecasting rather than cross-sectional models. In this context, this paper investigates mode choice dynamics among workers in Chennai city, India over a period of five years (1999–2004). Dynamics in mode choice is captured at four levels: exogenous variable change, state-dependence, changes in users’ sensitivity to attributes, and unobserved error terms. The results show that the dynamic models provide a substantial improvement (of over 500 log-likelihood points and ρ² increases from 44% to 68%) over the cross-sectional model. The performance was compared using two illustrative policy scenarios with important methodological and practical implications. The results indicate that cross-sectional models tend to provide inflated estimates of potential improvement measures. Improving the Level of Service (LOS) alone will not produce the anticipated benefits to transit agencies, as it fails to overcome the persistent inertia captured in the state-dependence factors. The results and models have important applications in the context of growing motorization and congestion management in developing countries.

The treatment of traffic in the Dutch environmental outlooks: the role of science in policy making and policy evaluation

The Dutch National Institute of Public Health and Environmental Protection publishes Environmental Outlooks in which 25‐year projections are made. These Outlooks quantifying the environmental problems, form the scientific basis for Dutch environmental policy. Traffic and transport is one of the main sectors causing environmental problems. The emissions and energy use of all relevant categories (road traffic, non‐road traffic) are based on model simulations with models. This paper describes the main models used.

If present policy is implemented only a minority of the environmental targets will be met.

If a sustainable transport system for the Netherlands means a large reducton in CO₂ emissions and energy use after 2010 a stronger emphasis on both technical and non‐technical measures (such as land‐use planning combined with public transport improvements) for the period until 2010 is needed than proposed in the Second Transport Structure Plan, unless a sustainable energy source becomes available.     

TRESIS: A transportation,land use and environmental strategy impact simulator for urban areas

The Institute of Transport Studies has developed a Transportation and Environment Strategy Impact Simulator (TRESIS) as a decision support system to assist planners to predict the impact of transport strategies and to make recommendations based on those predictions. A key focus of the simulator is the richness of policy instruments such as new public transport, new toll roads, congestion pricing, gas guzzler taxes, changing residential densities, introducing designated bus lanes, implementing fare changes, altering parking policy, introducing more flexible work practices, and the introduction of more fuel efficient vehicles. The appropriateness of mixtures of policy instruments is gauged in terms of a series of performance indicators such as impacts on greenhouse gas emissions, accessibility, equity, air quality and household consumer surplus. In this paper we introduce TRESIS to the research community, focussing on the structure of the system and the diversity of applications. Applications are presented to illustrate the diversity and richness of TRESIS as a policy advisory tool.     

The demand for public transport. part II. supply and demand factors of public transport

Abstract

This two‐part article, concerned with the way public transport ridership is affected by the various relevant factors, is based on the Executive Summary of The Demand for Public Transport (Webster and Bly 1980), the report of the TRRL‐sponsored International Collaborative Study on Factors Affecting Public Transport Patronage. Part I of the article, which was concerned with the social and economic conditions in which public transport operates, showed the importance of the background factors such as income, car ownership and land use on public transport usage: it also indicated how the longer‐term impacts of the more direct demand factors (fares, service levels) often show themselves in changes in car ownership levels, activity patterns (i.e. where people live, work, shop, socialize, etc) and land‐use development.

Part II reviews the current state of knowledge on the effects of changes in fare levels and quality of service and of the introduction of various traffic and transport measures (traffic restraint, bus priority, etc): it outlines current methodology on costing public transport services and draws the supply and demand sides together in a consideration of particular strategies which are at the disposal of the operator, the planner and the policy maker.     

Understanding transport mode choice for commuting: the role of affect

This study examines the relationship between positive and negative user valence and transport mode choice behaviour. We integrate latent attitudes ‘affect’ and ‘salience’ into transport mode choice models using the framework of integrated choice and latent variable modelling and simultaneous maximum likelihood estimation methods. The results are consistent with findings in similar travel behaviour and behavioural economics literature. The study extends the findings of previous research and has demonstrated that user sentiments about public transport mode and salient public transport experiences have a significant impact on travel mode choice behaviour. It was found that private motorised users are more sensitive to overcrowding and anti-social behaviours on PT than active and PT travellers. Key attitudinal indicators influencing individual transport choice behaviour are established to guide public policy. The key indicators of Affect and Salience must be analysed and addressed through public policy to enhance PT user experience and develop services and facilities to increase the utility of PT in-vehicle travel time.     

A zonal inference model based on observed smart-card transactions for Santiago de Chile

The collection of origin–destination data for a city is an important but often costly task. This way, there is a need to develop more efficient and inexpensive methods of collecting information about citizens’ travel patterns. In this line, this paper presents a generic methodology that allows to infer the origin and destination zones for an observed trip between two public transport stops (i.e., bus stops or metro stations) using socio-economic, land use, and network information. The proposed zonal inference model follows a disaggregated Logit approach including size variables. The model enables the estimation of a zonal origin–destination matrix for a city, if trip information passively collected by a smart-card payment system is available (in form of a stop-to-stop matrix). The methodology is applied to the Santiago de Chile’s morning peak period, with the purpose of serving as input for a public transport planning computational tool. To estimate the model, information was gathered from different sources and processed into a unified framework; data included a survey conducted at public transport stops, land use information, and a stop-to-stop trip matrix. Additionally, a zonal system with 1176 zones was constructed for the city, including the definition of its access links and associated distances. Our results shows that, ceteris paribus, zones with high numbers of housing units have higher probabilities of being the origin of a morning peak trip. Likewise, health facilities, educational, residential, commercial, and offices centres have significant attraction powers during this period. In this sense, our model manages to capture the expected effects of land use on trip generation and attraction. This study has numerous policy implications, as the information obtained can be used to predict the impacts of changes in the public transport network (such as extending routes, relocating their stops, designing new routes or changing the fare structure). Further research is needed to improve the zonal inference formulation and origin–destination matrix estimation, mainly by including better cost measures, and dealing with survey and data limitations.     

Well-being and Transport: Taking Stock and Looking Forward

ABSTRACT

It is only recently that researchers have attempted to directly link transport to models of well-being and in turn try to map transport's linkages to well-being outcomes. This paper seeks to add to this new literature by introducing a dynamic model of well-being, which highlights the different domains that make up well-being, and in turn — through providing one of the most holistic and comprehensive discussions of the current well-being literature — provide an evaluation of our current understanding of transport's relationship to well-being. The paper also seeks to highlight the different dimensions and complexities of seeking to monitor and improve well-being through transport policy. It will in turn be argued that the varied and complex sets of outcomes that arise from transport policy interventions, and the multiple ways in which they affect well-being, make a well-being approach (that measures policy outcomes in terms of units of well-being) of particular value for policy-makers. However, due to the complexities in comparing positive well-being outcomes, it is argued that the best use of well-being evidence for the transport sector may be to try to minimise the negative effects on well-being caused by policy outcomes.     

Modelling users’ behaviour in inter-urban carsharing program: A stated preference approach

In this paper, the effects of a inter-urban carsharing program on users’ mode choice behaviour were investigated and modelled through specification, calibration and validation of different modelling approaches founded on the behavioural paradigm of the random utility theory. To this end, switching models conditional on the usually chosen transport mode, unconditional switching models and holding models were investigated and compared. The aim was threefold: (i) to analyse the feasibility of a inter-urban carsharing program; (ii) to investigate the main determinants of the choice behaviour; (iii) to compare different approaches (switching vs. holding; conditional vs. unconditional); (iv) to investigate different modelling solutions within the random utility framework (homoscedastic, heteroscedastic and cross-correlated closed-form solutions). The set of models was calibrated on a stated preferences survey carried out on users commuting within the metropolitan area of Salerno, in particular with regard to the home-to-work trips from/to Salerno (the capital city of the Salerno province) to/from the three main municipalities belonging to the metropolitan area of Salerno. All of the involved municipalities significantly interact each other, the average trip length is about 30 km a day and all are served by public transport. The proposed carsharing program was a one-way service, working alongside public transport, with the possibility of sharing the same car among different users, with free parking slots and free access to the existent restricted traffic areas. Results indicated that the inter-urban carsharing service may be a substitute of the car transport mode, but also it could be a complementary alternative to the transit system in those time periods in which the service is not guaranteed or efficient. Estimation results highlighted that the conditional switching approach is the most effective one, whereas travel monetary cost, access time to carsharing parking slots, gender, age, trip frequency, car availability and the type of trip (home-based) were the most significant attributes. Elasticity results showed that access time to the parking slots predominantly influences choice probability for bus and carpool users; change in carsharing travel costs mainly affects carpool users; change in travel costs of the usually chosen transport mode mainly affects car and carpool users.     

Policy packages for modal shift and CO2 reduction in Lille,France

This paper proposes different policy scenarios to cut CO₂ emissions caused by the urban mobility of passengers. More precisely, we compare the effects of the ‘direct tool’ of carbon tax, to a combination of ‘indirect tools’ – not originally aimed at reducing CO₂ (i.e. congestion charging, parking charges and a reduction in public transport travel time) in terms of CO₂ impacts through a change in the modal split. In our model, modal choices depend on individual characteristics, trip features (including the effects of policy tools), and land use at origin and destination zones. Personal “CO₂ emissions budgets” resulting from the trips observed in the metropolitan area of Lille (France) in 2006 are calculated and compared to the situation related to the different policy scenarios. We find that an increase of 50% in parking charges combined with a cordon toll of €1.20 and a 10% travel time decrease in public transport services (made after recycling toll-revenues) is the winning scenario. The combined effects of all the policy scenarios are superior to their separate effects.