Bus congestion, optimal infrastructure investment and the choice of a fare collection system in dedicated bus corridors

Microeconomic optimisation of scheduled public transport operations has traditionally focused on finding optimal values for the frequency of service, capacity of vehicles, number of lines and distance between stops. In addition, however, there exist other elements in the system that present a trade-off between the interests of users and operators that have not received attention in the literature, such as the optimal selection of a fare payment system and a designed running speed (i.e., the cruising speed that buses maintain in between two consecutive stops). Alternative fare payment methods (e.g., on-board and off-board, payment by cash, magnetic strip or smart card) have different boarding times and capital costs, with the more efficient systems such as a contactless smart card imposing higher amounts of capital investment. Based on empirical data from several Bus Rapid Transit systems around the world, we also find that there is a positive relationship between infrastructure cost per kilometre and commercial speed (including stops), achieved by the buses, which we further postulate as a linear relationship between infrastructure investment and running speed. Given this context, we develop a microeconomic model for the operation of a bus corridor that minimises total cost (users and operator) and has five decision variables: frequency, capacity of vehicles, station spacing, fare payment system and running speed, thus extending the traditional framework. Congestion, induced by bus frequency, plays an important role in the design of the system, as queues develop behind high demand bus stops when the frequency is high. We show that (i) an off-board fare payment system is the most cost effective in the majority of circumstances; (ii) bus congestion results in decreased frequency while fare and bus capacity increase, and (iii) the optimal running speed grows with the logarithm of demand.     

A dense water outflow from the Ross Sea, Antarctica: Mixing and the contribution of tides

We use hydrographic, current, and microstructure measurements, and tide-forced ocean models, to estimate benthic and interfacial mixing impacting the evolution of a bottom-trapped outflow of dense shelf water from the Drygalski Trough in the northwestern Ross Sea. During summer 2003 an energetic outflow was observed from the outer shelf ( 500 m isobath) to the  1600 m isobath on the continental slope. Outflow thickness was as great as  200 m, and mean speeds were  0.6 m s^− 1 relative to background currents exceeding  1 m s^− 1 that were primarily tidal in origin. No outflow was detected on the slope in winter 2004, although a thin layer of dense shelf water was present on the outer shelf. When the outflow was well-developed, the estimated benthic stress was of order one Pascal and the bulk Froude number over the upper slope exceeded one. Diapycnal scalar diffusivity (K_z) values in the transition region at the top of the outflow, estimated from Thorpe-scale analysis of potential density and measurements of microscale temperature gradient from sensors attached to the CTD rosette, were of order 10^− 3−10^− 2 m² s^− 1. For two cases where the upper outflow boundary was particularly sharply defined, entrainment rate w_e was estimated from K_z and bulk outflow parameters to be  10^− 3 m s^− 1 ( 100 m day^− 1). A tide-forced, three-dimensional primitive equation ocean model with Mellor-Yamada level 2.5 turbulence closure scheme for diapycnal mixing yields results consistent with a significant tidal role in mixing associated with benthic stress and shear within the stratified ocean interior.     

The sharing economy and the job market: the case of ride-hailing drivers in Chile

Transportation - Ride-hailing (ridesourcing) companies such as Uber, Lyft, and Didi Chuxing have been a disruptive force in the urban mobility landscape around the world during the past decade. In...     

Choosing Public Transport—Incorporating Richer Behavioural Elements in Modal Choice Models

The development of behaviourally richer representations of the role of well-established and increasingly important influences on modal choice, such as trip time reliability and accounting for risk attitude and process rules, has moved forward at a fast pace in the context of automobile travel. In the public transport setting, such contributions have, with rare exception, not been considered. In this paper, we discuss and empirically illustrate the merits of advanced modelling developments aimed at improving our understanding of public transport choice, namely the inclusion of reliability in extended expected utility theoretic forms, to recognize risk attitude and perceptual conditioning, the consideration of passenger crowding and its inclusion in linear additive models, and the role of multiple heuristics in representing attribute processing as a way of conditioning modal choice. We illustrate the mechanics of introducing these behaviourally appealing extensions using a modal choice data set collected in Sydney.     

Comparing operator and users costs of light rail, heavy rail and bus rapid transit over a radial public transport network

A model to compare three alternative forms of public transport - light rail, heavy rail and bus rapid transit - is developed for an urban network with radial lines emanating from the borders to the city centre. The theoretical framework assumes an operation aimed at minimising the total cost associated with public transport service provision, which encompasses both operator and users costs. The decision variables are the number of lines (network density) and the frequency per period for each mode. This approach has no prejudices a priori in respect of whether a specified delivery scenario is aligned with existing modal reputation. Rather, we establish the conditions under which a specific transit mode should be preferred to another in terms of the operator (supply) and user (demand) side offerings. The model is applied using data from Australian cities, suggesting that in most of the scenarios analysed a high standard bus service is the most cost-effective mode, because it provides lower operator costs (infrastructure, rolling stock and operating cost), access time costs (due to a larger number of lines) and waiting time cost (due to larger frequencies of operation). A rail mode, such as light rail or heavy rail, may have a lower total cost only if it is able to run faster than bus rapid transit, and the difference in speed is enough to outweigh the bus advantage on operator cost and access and waiting times.     

Studying the relationship between activity participation,social networks,expenditures and travel behavior on leisure activities

Transportation - In the context of an increasing interest in understanding travel for non-mandatory activities, such as recreation and socializing, this work focuses on studying the relationships...     

Investigating the effects of psychological factors on commuting mode choice behaviour

This paper utilizes socio-psychometric survey data to investigate the influence of attitudes, affective appraisal and habit formation on commuting mode choice. The data-set was collected in 2009–2010 in Edmonton, Alberta. In addition to conventional socio-economic, demographic and modal attributes, the survey gathered psychological information regarding habitual behaviour, affective appraisal and personal attitudes. Different psychometric tools were used to capture psychological factors affecting mode choice. Habitual behaviour was measured using Verplanken's response-frequency questionnaire. Affective appraisal was indirectly estimated using the Osgood's semantic differential. Five-point Likert scales were used to measure attitude. The structural equation modelling (SEM) approach was used to investigate the effects of psychological factors on mode choice behaviour. SEM captures the latent nature of psychological factors and uses path diagrams to identify the directionality as well as intensity of the relationships. The investigation reveals that passengers have positive emotions towards their chosen mode. Further, evidence of the superiority of the car as a travel alternative was established in terms of strong habit towards it, such that passengers would use the car for almost every single trip.     

Effect of attitudes, habit and affective appraisal on mode choice: an application to university workers

Traditionally, car use and modal choice, in general, have been studied under the random utility framework, assuming that individuals choose a particular mode based on their own socio-economic characteristics and the attributes describing the available options. This approach has originated useful models which have been able to explain modal split. However, at the same time, it has received critics because of its poor characterization of human behaviour and the weakness of its assumptions. Research has suggested that socio-psychological factors could help to understand better the choice process. In this paper, attitudinal theory and its link to human behaviour were used to select attitudes, habit and affective appraisals as explanatory variables. They were measured using ad-hoc instruments, which were combined with a revealed preference questionnaire, in order to obtain information about the traveller and the chosen mode. This instrument was applied to a sample extracted from staff members of the University of Concepcion, Chile. Analyses of attitudinal variables showed that car use habit was positively correlated to attitude and positive emotions towards car, implying that breaking the vicious circle of car use through persuasive techniques might be difficult. Estimation of discrete choice models showed that attitudinal variables presented a significant contribution to modal utility, and helped to improve both fitness and statistical significance. Results showed that choice can be influenced by factors related to attitudes and affective appraisal, and that their study is necessary in order to achieve an effective car use reduction.

Accounting for travel time variability in the optimal pricing of cars and buses

A number of studies have shown that in addition to travel time and cost as the common influences on mode, route and departure time choices, travel time variability plays an increasingly important role, especially in the presence of traffic congestion on roads and crowding on public transport. The dominant focus of modelling and implementation of optimal pricing that incorporates trip time variability has been in the context of road pricing for cars. The main objective of this paper is to introduce a non-trivial extension to the existing literature on optimal pricing in a multimodal setting, building in the role of travel time variability as a source of disutility for car and bus users. We estimate the effect of variability in travel time and bus headway on optimal prices (i.e., tolls for cars and fares for buses) and optimal bus capacity (i.e., frequencies and size) accounting for crowding on buses, under a social welfare maximisation framework. Travel time variability is included by adopting the well-known mean–variance model, using an empirical relationship between the mean and standard deviation of travel times. We illustrate our model with an application to a highly congested corridor with cars, buses and walking as travel alternatives in Sydney, Australia. There are three main findings that have immediate policy implications: (i) including travel time variability results in higher optimal car tolls and substantial increases in toll revenue, while optimal bus fares remain almost unchanged; (ii) when bus headways are variable, the inclusion of travel time variability as a source of disutility for users yields higher optimal bus frequencies; and (iii) including both travel time variability and crowding discomfort leads to higher optimal bus sizes.     

Exploring the links between personal networks, time use, and the spatial distribution of social contacts

Although the study of the role of the social context in travel behavior and activity patterns has recently gained attention, the empirical evidence supporting the relationship between social networks and the temporal and spatial characteristics of social activities is still limited. With this motivation, this paper studies the link between “longer term” (social networks) and “shorter term” (social activities) social decisions, by exploring the intertwined relationship between the individuals’ personal networks attributes, and the spatiotemporal characteristics of their daily social activities. The paper contributes to the literature by adding two key aspects to the study of the role of social networks on travel behavior: the social networks’ structure, and the spatiality of all individuals participating on the social activities. Based on data which link people’s personal networks and time use, and using a structural equation modeling approach, the paper studies the influence of individual and interactional attributes on the duration, distance, and number of people involved in social daily activities. The results show that aspects such as tie social closeness, gender and age similarity, and network density, help to understand social activity duration and distance, complementing traditional socio-demographic aspects such as income, occupation, and accessibility to services. In this way, socio-demographic attributes are not enough to explain the spatiotemporal dimension of daily activities which makes necessary to include variables related to the social context to explain with a higher level of accuracy both the duration and distance traveled to the activity.