Mapping minibuses in Maputo and Nairobi: engaging paratransit in transportation planning in African cities

ABSTRACT

Often called paratransit because of their flexible stops, schedules and routes, minibuses make up the bulk of public transport in African cities. Despite their ubiquity and importance, these systems are poorly understood by transportation planners who tend to focus on large-scale urban infrastructure projects such as highways, commuter rail or bus rapid transit systems. The assumption within much of this planning is that these minibus systems are barriers to change and will become at most secondary “feeder” buses within large-scale projects, but structured plans detailing this vision are lacking. This paper argues that frequent failure to collect data and value important paratransit systems as a critical part of transportation in their own right is deeply problematic from the point of view of equity, access and inclusive and effective planning. We ask whether the growing number of bottom up mapping projects of minibus systems can disrupt this status quo. By comparing two mapping projects, Digital Matatus in Nairobi and the Mapa Dos Chapas in Maputo, we find that inclusive, collaborative mapping can help render these minibuses more visible in planning and provoke more grounded and inclusive “planning conversations” on multi-modal integration, passenger information and minibus upgrading, all key but relatively marginalised aspects of creating accessible, low emission, high quality and safe public transport in African cities.     

Quantifying individuals’ trade-offs between privacy,liberty and security: The case of rail travel in UK

Public transport systems have been targets in several terrorist attacks, notably in recent years, resulting in tight security measures worldwide. However, individuals’ privacy and liberty often conflict with efforts towards safety and security, making it difficult to assess the implications of security measures balanced against the costs (e.g., citizens may be stopped, searched and asked to provide personal identification data to authorities without any particular reason). Henceforth, our research question asks, “to what extent would people sacrifice their right to privacy and liberty in exchange for potentially safer and more secure travel?” This paper uses a stated choice experiment to quantify individuals’ trade-offs between privacy and security within a real-life context, namely rail travel in the UK. Using a nationwide sample, the empirical analysis yields the importance of improvements in the security infrastructure and identifies areas of concern with regard to privacy and liberty controlling for travel related factors. Further, trade-offs across different security measures for rail travel are quantified in terms of individuals’ willingness-to-pay extra on top of the average ticket price.     

GHG-emission models for assessing the eco-friendliness of road and rail freight transports

Intermodal rail/road transportation is an instrument of green logistics, which may help reducing transport related greenhouse gas (GHG) emissions. In order to assess the environmental impact of road and rail transports, researchers have formulated very detailed microscopic models, which determine vehicle emissions precisely based on a vast number of parameters. They also developed macroscopic models, which estimate emissions more roughly from few parameters that are considered most influential. One of the goals of this paper is to develop mesoscopic models that combine the preciseness of micro-models while requiring only little more information than macro-models. We propose emission models designed for transport planning purposes which are simple to calibrate by transport managers. Despite their compactness, our models are able to reflect the influence of various traffic conditions on a transport’s total emissions. Furthermore, contrasting most papers considering either the road or the rail mode, we provide models on a common basis for both modes of transportation. We validate our models using popular micro- and macroscopic models and we apply them to artificial and real world transport scenarios to identify under which circumstances intermodal transports actually effect lower emissions. We find that travel speed and country-specific energy emission factors influence the eco-friendliness of intermodal transports most severely. Hence, the particular route chosen for a transnational intermodal transport is an important but so far neglected option for eco-friendly transportation.     

Role of the Travel Factor Convenience in Rail Travel and a Framework for its Assessment

Abstract

This paper reviews the travel factor convenience with particular regard to rail travel. Past research has shown that convenience is a concept readily associated with the private car and its perceived ability to provide a door‐to‐door journey. Private vehicles such as cars are often key competitors to public transport. However, convenience with regard to public transport has proved to be somewhat of an ambiguous concept, often showing a high degree of overlap with the other main recognized travel factors. This paper shows that it is possible to consider convenience in rail travel as an embodiment of four themes: access/egress, station facilities/environment, frequency of service/scheduling and interchange between train services. A list of physically measurable elements can be produced relating to these four themes in order to assess the convenience of any particular station. A categorization process is proposed based upon the initial findings of a questionnaire designed to obtain a user perspective upon convenience. It is concluded that no definitive measure of convenience can be produced for rail travel, although a proxy measure, based upon categorization, containing some or all of the defined elements should be possible.     

The future mobility of the world population

On average a person spends 1.1 h per day traveling and devotes a predictable fraction of income to travel. We show that these time and money budgets are stable over space and time and can be used for projecting future levels of mobility and transport mode. The fixed travel money budget requires that mobility rises nearly in proportion with income. Covering greater distances within the same fixed travel time budget requires that travelers shift to faster modes of transport. The choice of future transport modes is also constrained by path dependence because transport infrastructures change only slowly. In addition, demand for low-speed public transport is partially determined by urban population densities and land-use characteristics. We present a model that incorporates these constraints, which we use for projecting traffic volume and the share of the major motorized modes of transport—automobiles, buses, trains and high speed transport (mainly aircraft)—for 11 regions and the world through 2050. We project that by 2050 the average world citizen will travel as many kilometers as the average West European in 1990. The average American's mobility will rise by a factor of 2.6 by 2050, to 58,000 km/year. The average Indian travels 6000 km/year by 2050, comparable with West European levels in the early 1970s. Today, world citizens move 23 billion km in total; by 2050 that figure grows to 105 billion.     

Exploring the role of social capital influence variables on travel behaviour

This paper explores the potential role of individual trip characteristics and social capital network variables in the choice of transport mode. A sample of around 100 individuals living or working in one suburb of Madrid (i.e. Las Rosas district of Madrid) participated in a smartphone short panel survey, entering travel data for an entire working week. A Mixed Logit model was estimated with this data to analyze shifts to metro as a consequence of the opening of two new stations in the area. Apart from classical explanatory variables, such as travel time and cost, gender, license and car ownership, the model incorporated two “social capital network” variables: participation in voluntary activities and receiving help for various tasks (i.e. child care, housekeeping, etc.). Both variables improved the capacity of the model to explain transport mode shifts. Further, our results confirm that the shift towards metro was higher in the case of people “helped” and lower for those participating in some voluntary activities.     

Asking the right questions about telecommuting: Avoiding pitfalls in surveying homebased work

In designing travel behavior surveys, the problem is to define “work,” “home,” and similar words that are commonly used in our language but which have acquired a plethora of associated meanings. The difficulty has not been resolved by the many new terms coined to describe non-traditional ways to work. Such words as “telecommuting,” “teleworking,” “at-home work,” “hoteling,” “homebased business,” “road warriors” and “mobile workers,” lack any agreed-upon definitions yet they are used in common parlance as if they did. These new workstyles are of interest to travel planners because they may involve trip reduction. To forecast just how much trip reduction will occur, behavior needs to be measured by objective criteria. To avoid definitional traps, we recommend phrasing questions in terms of measurable variables such as the place of work and the time in days and hours spent at each location. That approach leaves researchers the option of applying their own definitions that fit the context of their analyses. Thus, rather than ask “How many days a week do you telecommute?” the more precise question can be asked: “How many days last week did you work at home instead of going to your usual work location?” This approach has the advantage that information gathered over years can be used unambiguously in various contexts. Definitions can be applied at the point of analysis. This paper illustrates errors and confusion that can arise from casually worded surveys using examples from private and public surveys. The author proposes a set of core questions with four levels of priority for consideration in designing future surveys of travel behavior.     

An investigation into the feasibility of increasing rail use as an alternative to the car

With rail travel largely seen to be a more sustainable method than road-based transport, this paper examines the market segments amongst existing motorists that would be most likely to travel by train in the UK. The analysis is based on a large survey in London and the south-east of England, the area surrounding the routes operated by the train company First Capital Connect. Findings show that train travellers tend to be middle-aged and of a higher social grade, typically taking commuting or business trips. Individuals living within four miles of a station are considerably more likely to travel by rail than those further away. Given the competition from road-based transport, it is of particular interest that the measure highlighted to increase rail use for those living further away from the rail network is to enhance car parking at train stations.     

Dynamic process model of mass effects on travel demand

Whereas transportation planners commonly predict the negative impacts of mass transportation, there is increasing empirical evidence of the existence of positive mass effects, whereby increased use of a mode by the ‘mass’ will generally increase its attractiveness for future travellers. In this paper we consider the dynamic impact of such an effect on the problem of travel demand forecasting, with particular regards to social network effects. Our proposed modelling approach is inspired by literature from social physics, evolutionary game theory and marketing. For simplicity of exposition, our model is specified for a scenario in which (a) there is a binary choice between two mobility lifestyles, referred to as car-oriented and transit-oriented, and (b) there are two population groups, where one is the “leading” or “innovative” population group and the other the “following” or “imitating” population group. This latter distinction follows the rather well-known Bass model from the marketing literature (1969). We develop the transition probabilities and transition dynamics. We illustrate with a numerical case study that despite lower intrinsic utility for the transit lifestyle, significant changes towards this lifestyle can be achieved by considering congestion, service improvements and mass effects. We further illustrate that mass effects can be positive or negative. In all cases we explore the sensitivity of our conclusions to the assumed parameter values.     

Flexible substitution patterns in models of mode and time of day choice: new evidence from the UK and the Netherlands

Modelling the temporal response of travellers to transport policy interventions has rapidly emerged as a major issue in many practical transport planning studies and is recognised to hold particular challenges. The importance of congestion and its variation over the day, together with the emergence of time-dependent road user charging as a policy tool, emphasise the need to understand whether and how travellers will change the timing of their journeys. For practical planning studies, analysts face a major issue of relating temporal changes to other behavioural changes that are likely to result from policy or exogenous changes. In particular, the relative sensitivity of time and mode switching has been difficult to resolve. This paper describes a study undertaken to determine the relative sensitivity of mode and time of day choice to changes in travel times and costs and to investigate whether evidence exists of varying magnitudes of unobservable influences in time of day switching. The study draws on data from three related stated preference studies undertaken over the past decade in the United Kingdom and the Netherlands and uses error components logit models to investigate the patterns of substitution between mode and time of day alternatives. It is concluded that the magnitude of unobserved influences on time switching depends significantly on the magnitudes of the time switches considered. With time periods of the magnitude generally represented in practical modelling, i.e. peak periods of 2–3 hours, time switching is generally more sensitive in these data than mode switching. However, the context of the modelling and the extent to which relevant variables can be measured will strongly influence these results.     

Evaluating choice of traction option for a sustainable Indian Railways

The transport sector is a major contributor of carbon emissions in India. As railways are the most environment-friendly mode of transport we look at the spearheading role of Indian Railway (IR) in bringing about the modal shift from road and airways to rail with a holistic perspective considering India’s development stage and resource situation. India being an emerging economy, faces many other social and developmental challenges, which have to be incorporated in assessing the viability of the solutions. In order to assess the total impact of the transportation sector a ‘wells to wheels’ approach needs to be adopted to quantify the emissions from the production to distribution and final usages alongside its impact to the competing societal goals utilizing the same resources. This study focuses on evaluating IR’s critical policy decision towards providing efficient transport i.e. the choice of traction. It is inferred that until such time the fuel mix of power production in India remains the same, i.e. coal dominated and there is a shortage of electricity in the country, the accumulated carbon footprints of running electric locos will be higher. There should be a judicious mix of both the tractions to achieve a balance in environmental efficacy, sustainability and equity.     

Overcoming barriers to cycling: understanding frequency of cycling in a University setting and the factors preventing commuters from cycling on a regular basis

Much local and regional transport policy is attempting to increase cycling as an everyday mode of travel through infrastructure changes, education initiatives, and safety campaigns. While considerable research has examined the influence of the built form on cycling, less research has examined the barriers that prevent people who wish to cycle more (as part of their routine) from doing so. This study examines several factors influencing the frequency by which people do (and do not) cycle in a campus setting in a large metropolitan area. Mixed methods reveal differences between barriers to cycling as well as the relative strength of these barriers across categories of age, sex, and current mode used. A multinomial logit model, which controls for residential self-selection effects, predicts whether and how often a respondent cycles based on socio-demographic and trip characteristics. The presence of cycle paths is found to be strongly associated with a higher frequency of cycling commutes. Additionally, an analysis of stated barriers reveals effort and a lack of safety as the most important barriers to potential cyclists. Finally, a qualitative analysis of respondents’ open-ended responses confirms the influence of bicycle paths, but reveals other factors such as the importance of improved interactions among various street users. Findings from this research can be of benefit to transportation engineers and planners who are aiming to increase the use of cycling among various groups of commuters.     

Do high income households reduce driving more when living near rail transit?

Transportation planning today requires an understanding of how income and near-rail residence jointly influence household travel behavior. This article fills a gap in the literature by showing how vehicle miles traveled (VMT) and transit trips taken (TT) vary with income and rail transit access by neighborhood type. Results indicate that, when comparing households with similar incomes and examining how the “near-rail” versus “far from rail” VMT and TT gap varies by income, the cross-sectional reduction in nominal VMT and the increase in TT on a percentage basis is generally larger for higher-income households (>$50,000), and particularly so in neighborhoods dense with both jobs and population. These findings offer support for the notion that near-transit housing targeting higher-income households can have both sustainability and transit use benefits. We note, though, that equity considerations are a strong reason to include low-income housing near rail transit, and argue that policies focusing overly singly on either low-income or high-income housing near rail transit will not be as impactful as a robust focus on mixed-income housing developments in rail transit-oriented developments (TODs).     

A modeling approach for matching ridesharing trips within macroscopic travel demand models

State of the art travel demand models for urban areas typically distinguish four or five main modes: walking, cycling, public transport and car. The mode car can be further split into car-driver and car-passenger. As the importance of ridesharing may increase in the coming years, ridesharing should be addressed as an additional sub or main mode in travel demand modeling. This requires an algorithm for matching the trips of suppliers (typically car drivers) and demanders (travelers of non-car modes). The paper presents a matching algorithm, which can be integrated in existing travel demand models. The algorithm works likewise with integer demand, which is typical for agent-based microscopic models, and with non-integer demand occurring in travel demand matrices of a macroscopic model. The algorithm compares two path sets of suppliers and demanders. The representation of a path in the road network is reduced from a sequence of links to a sequence of zones. The zones act as a buffer along the path, where demanders can be picked up. The travel demand model of the Stuttgart Region serves as an application example. The study estimates that the entire travel demand of all motorized modes in the Stuttgart Region could be transported by 7% of the current car fleet with 65% of the current vehicle distance traveled, if all travelers were willing to either use ridesharing vehicles with 6 seats or traditional rail.     

Impacts of highway congestion on freight operations: perceptions of trucking industry managers

To better understand how road congestion adversely affects trucking operations, we surveyed approximately 1200 managers of all types of trucking companies operating in California. More than 80% of these managers consider traffic congestion on freeways and surface streets to be either a “somewhat serious” or “critically serious” problem for their business. A structural equations model (SEM) is estimated on these data to determine how five aspects of the congestion problem differ across sectors of the trucking industry. The five aspects were slow average speeds, unreliable travel times, increased driver frustration and morale, higher fuel and maintenance costs, and higher costs of accidents and insurance. The model also simultaneously estimates how these five aspects combine to predict the perceived overall magnitude of the problem. Overall, congestion is perceived to be a more serious problem by managers of trucking companies engaged in intermodal operations, particularly private and for-hire trucking companies serving airports and private companies serving rail terminals. Companies specializing in refrigerated transport also perceive congestion to be a more serious overall problem, as do private companies engaged in LTL operations. The most problematic aspect of congestion is unreliable travel times, followed by driver frustration and morale, then by slow average speeds. Unreliable travel times are a significantly more serious problem for intermodal air operations. Driver frustration and morale attributable to congestion is perceived to be more of a problem by managers of long-haul carriers and tanker operations. Slow average speeds are also more of a concern for airport and refrigerated operations.     

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.     

High-Speed Rail Operations on an Existing Network: An Assessment Model for China

High-speed rail operations have the potential to reduce the long-term decline in rail passenger travel demand for the medium to long distance inter-urban markets. Such decline has been evident through most of the industrialized countries where air and road transport tend to be the dominant modes. In China, the operations of long distance high-speed rail on fully dedicated track is not very easy to implement, due to the high proportion of passengers who travel between high-speed and conventional railways. An alternative approach would be to allow for mixed operations with trains of various speeds on the same track. This article puts forward a simulation model designed to allow an evaluation of the most efficient distance for high-speed rail operations under mixed train speed scenarios. The model takes into account the main operating parameters such as passenger volumes, train speeds, capital and maintenance costs, train operating costs and energy consumption. The distance of high-speed train running on conventional rail that will yield the most economic benefit can be estimated using the model. The article includes the results of using the model for a specific example. It is concluded that large-scale high-speed trains have the potential to be successfully operated on conventional rail networks.     

New routes on old railways: increasing rail’s mode share within the constraints of the existing railway network

This paper describes an integrated methodology for identifying potential ‘quick wins’ for mode shift from road to passenger rail transport. Firstly, a procedure for analysing rail’s relative competitiveness in the market for passenger transport between large urban areas is developed and then applied to a UK case study. The purpose of such analysis is to allow the identification of flows where rail is currently relatively uncompetitive (in terms of journey time in particular) and to assess the reasons for this poor performance, so that the issues which suppress rail use may be addressed. In parallel, a framework, methodology and tool for the assessment of existing and potential capacity (trains, seats, TEUs, etc.) is developed for both passenger and freight traffic, to identify and address network constraints. An illustrative example of the use of these demand and capacity assessment tools is then presented, with the tools used to identify and evaluate flows where rail demand is suppressed by poor service quality and where spare capacity exists which would allow the passenger rail service to be improved without requiring significant investments in infrastructure. The effects of such improvements on demand are predicted, and the cost implications of operating such additional services are discussed. The analysis suggests that there may be significant potential for increasing rail’s mode share by providing additional inter-urban services where rail currently offers an inferior service.     

Multimodal travel groups and attitudes: A latent class cluster analysis of Dutch travelers

For developing sustainable travel policies, it may be helpful to identify multimodal travelers, that is, travelers who make use of more than one mode of transport within a given period of time. Of special interest is identifying car drivers who also use public transport and/or bicycle, as this group is more likely to respond to policies that stimulate the use of those modes. It is suggested in the literature that this group may have less biased perceptions and different attitudes towards those modes. This supposition is examined in this paper by conducting a latent class cluster analysis, which identifies (multi)modal travel groups based on the self-reported frequency of mode use. Simultaneously, a membership function is estimated to predict the probability of belonging to each of the five identified (multi)modal travel groups, as a function of attitudinal variables in addition to structural variables. The results indicate that the (near) solo car drivers indeed have more negative attitudes towards public transport and bicycle, while frequent car drivers who also use public transport have less negative public transport attitudes. Although the results suggest that in four of the five identified travel groups, attitudes are congruent with travel mode use, this is not the case for the group who uses public transport most often. This group has relatively favorable car attitudes, and given that many young, low-income travelers belong to this group, it may be expected that at least part of this group will start using car more often once they can afford it. Based on the results, challenges for sustainable policies are formulated for each of the identified (multi)modal travel groups.