Assessing the social costs of urban transport infrastructure options in low and middle income countries

ABSTRACT

This paper develops cost models for urban transport infrastructure options in situations where motorcycles and various forms of taxis are important modes of transport. The total social costs (TSCs) of conventional bus, Bus Rapid Transit (BRT), Monorail, Metro (Elevated Rail), car, motorcycle, Taxi and Uber are calculated for an urban corridor covering operator, user and external costs. Based on the parameters for a 7?km corridor in Hanoi, Vietnam, the results show the lowest average social cost (ASC) transport modes for different ranges of demand. Motorcycle might be the best option at low demand levels while conventional bus has advantages with low-medium demand. At medium demand levels, bus-based technologies and Monorail are competitive options while Metro, with a higher person capacity, is the best alternative at the highest demand levels. Compared to other modes, the ASCs of car and Taxi/Uber are greater because of high capital cost (related to vehicles) per passenger and low occupancy. Transport planners and decision makers in low and middle income countries (LMICs) can draw on the findings of this study. However, various limitations are identified and additional research is suggested.     

Modal split and urban public transport management in an Eastern European country

When public transport is the main means of travel in urban areas, management and planning are easy and the main objective can be to minimise costs for the demand available, i.e. maximise profit. However when public transport faces competition from other modes of transport, and activities can be undertaken in a variety of locations, then the management and planning of public transport services is considerably more difficult.This paper examines a methodology for representing consumer behaviour when faced with alternative travel decisions, in order to identify the demand for public transport and to help operators adjust services and prices to maximise demand, when considering people's disposable income, the alternative modes and activity locations available. From this it is possible to devise criteria for maximising consumer surplus in a city, taking into account social benefits.     

Transfer demand prediction for timed transfer coordination in public transport operational control

Timed transfer coordination in public transit reduces passenger transfer time by providing seamless interconnected transfers. The problem arises when a Receiving Vehicle (RV) arrives to the transfer stop before a Feeding Vehicle (FV) carrying transferring passengers. Timed transfer coordination in operational control dynamically decides whether a RV is held at the transfer stop to allow transfers, or departs as scheduled. While transfer demand is essential for implementing timed transfer coordination, this variable is generally not available in public transit because of the lack of passenger transfer plans. The problem of acquiring this variable in real‐time has also received limited attention in the related literature. This paper proposes a new method to dynamically predict the transfer demand. We anticipate the transferring probability from each individual passenger by examining historical travel itineraries. Three different types of models (simple analytical, statistical, and computation intelligence model) are developed to forecast the number of transferring passengers. Numerical experiments using observed Automatic Vehicle Location and Automatic Fare Collection data from South East Queensland, Australia show the accuracy and applicability of the proposed models in timed transfer coordination. Copyright © 2017 John Wiley & Sons, Ltd.     

The asymmetric effects of income and fuel price on air transport demand

Forecasts of passenger demand are an important parameter for aviation planners. Air transport demand models typically assume a perfectly reversible impact of the demand drivers. However, there are reasons to believe that the impacts of some of the demand drivers such as fuel price or income on air transport demand may not be perfectly reversible. Two types of imperfect reversibility, namely asymmetry and hysteresis, are possible. Asymmetry refers to the differences in the demand impacts of a rising price or income from that of a falling price or income. Hysteresis refers to the dependence of the impacts of changing price or income on previous history, especially on previous maximum price or income. We use US time series data and decompose each of fuel price and income into three component series to develop an econometric model for air transport demand that is capable of capturing the potential imperfectly reversible relationships and test for the presence or absence of reversibility. We find statistical evidence of asymmetry and hysteresis – for both, prices and income – in air transport demand. Implications for policy and practice are then discussed.     

Structure and dynamics of non-suburban passenger travel demand in Indian railways

In this paper we derive long run structural relationships for all the three classes, viz. upper, second and ordinary second class, of non-suburban long distance passenger transport demand for Indian railways using annual time series data for 1970–1995. We employ some of the recent developments in multivariate dynamic econometric time series modeling including estimation of long-run structural cointegrating relationships, short-run dynamics and measurement of the effects of shocks and their persistence on evolution of the dynamic passenger transport demand system. The models are estimated using a cointegrating vector autoregressive (VAR) modeling framework, which allows for endogeneity of regressors. The demand systems are found to be stable for all the classes in the long run and they converge to equilibrium in a period of around 2–4 years after a typical system-wide shock. Any disequilibrium in the short-run is corrected in the long-run with adjustments in passenger transport demand and the price variable, i.e. real rate charged per passenger kilometer. Results show that travel demand in all classes would rise with income, although the rise is less than proportionate in the case of ordinary class. High price elasticity in long-run and short-run impulse responses indicate that passenger fare hike could lead to substantial decline in travel demand leading to decline in revenue earnings of the railways. This revised version was published online in June 2006 with corrections to the Cover Date.     

Assessing the cost of transfer inconvenience in public transport systems: A case study of the London Underground

Few studies have adequately assessed the cost of transfers² in public transport systems, or provided useful guidance on transfer improvements, such as where to invest (which facility), how to invest (which aspect), and how much to invest (quantitative justification of the investment). This paper proposes a new method based on path choice,³ taking into account both the operator’s service supply and the customers’ subjective perceptions to assess transfer cost and to identify ways to reduce it. This method evaluates different transfer components (e.g., transfer walking, waiting, and penalty) with distinct policy solutions and differentiates between transfer stations and movements.The method is applied to one of the largest and most complex public transport systems in the world, the London Underground (LUL), with a focus on 17 major transfer stations and 303 transfer movements. This study confirms that transfers pose a significant cost to LUL, and that cost is distributed unevenly across stations and across platforms at a station. Transfer stations are perceived very differently by passengers in terms of their overall cost and composition. The case study suggests that a better understanding of transfer behavior and improvements to the transfer experience could significantly benefit public transport systems.     

Car ownership and public transport use: Revisiting the interaction

At the beginning of the 1980s, it seemed that a consensus was emerging among researchers that public transport service levels, fares or quality had a small but possibly important effect on car ownership, and that this should be taken into account for those purposes where car ownership forecasts are used for developing policy on public transport or roads. Somehow, the findings faded away, and had little effect on policy thinking or on analytical techniques. The results of six surveys carried out in South Yorkshire over the period 1972 to 1991, during which there were extreme changes in public transport policy, tend to support a prima facie case for reopening the question. At the household level, car ownership rates are shown to be more volatile than is often assumed, especially in multiple car households. This volatility provides a context within which the quality of public transport provision appears to influence both the level of car ownership and the relationship between changes in the level of car ownership and changes in public transport use.     

The effect of contract renewal and competitive tendering on public transport costs,subsidies and ridership

In this paper, we aim to estimate the effect of contract renewal as well as competitive tendering on public transport costs, subsidies, and ridership. More specifically, we examine to what extent (multiple) contract renewals and introduction of competitive tendering for long-term public transport contracts affect ridership, operational costs and subsidies in concession areas governed by public transportation authorities from 2001 until 2013 in the Netherlands. Our identification strategy improves on the literature as we are able to control for all time-invariant unobserved factors, such as network and area characteristics by using panel data. We show that when renewing long-term contracts, operational costs are reduced by at least 10%, whereas subsidies fall even stronger. For contracts that are renewed at least twice, the reduction in costs is even more substantial and in the order of 16%. We find that the effect of competitive tendering is completely absent, suggesting that the threat of competitive tendering is sufficient in a market where the majority of concessions is competitive tendered. Contract renewal not only reduces costs and subsidies, but simultaneously increases public transport ridership by 7.7%. Furthermore the vehicle-hours elasticity of operational costs is 0.40, pointing to strong economies of density. The geographical scale elasticity of operational costs is around one, which indicates constant returns to scale with respect to the geographical size of the concession area. This suggest that the current size of the Dutch concession area is optimal with respect to costs.     

Assessing systematic sources of variation in public transport elasticities: Some comparative warnings

There is an extensive and continually growing body of empirical evidence on the sensitivity of potential and actual users of public transport to fare and service levels. The sources of the evidence are disparate in terms of methods, data collection strategy, data paradigms, trip purpose, location, time period, and attribute definition. In this paper, we draw on a data set we have been compiling since 2003 that contains over 1100 elasticity items associated with prices and services of public transport, and car modes. The focus herein is on direct elasticities associated with public transport choice and demand, and the systematic sources of influence on the variations in the mean estimates for fares, in-vehicle time, and headway obtained from 319 studies. The major influences on variations in mean estimates of public transport elasticities are the time of day (peak, all day vs. off-peak), the data paradigm (especially combined SP/RP vs. revealed preference (RP)), whether an average fare or class of tickets is included, the unit of analysis (trips vs. vkm), specific trip purposes, country, and specific-mode (i.e., bus and train) in contrast to the generic class of public transport.     

The effect of financial constraints on the optimal design of public transport services

Recent experience with the design of bus services in Santiago, Chile, seems to confirm Jansson's (1980) assertion regarding observed planned bus frequency and size being too low and too large, respectively. We offer an explanation based upon the relation between cost coverage, pricing and optimal design variables. We recall that average social cost decreases with patronage, which generates an optimal monetary fare below the average operators' cost, inducing an optimal subsidy. Then we compare optimal frequency and bus size—those that minimize total social costs—with those that minimize operators' costs only. We show that an active constraint on operators' expenses is equivalent to diminish the value of users' time in the optimal design problem. Inserting this property back in the optimal pricing scheme, we conclude that a self-financial constraint, if active, always provokes an inferior solution, a smaller frequency and, under some circumstances, larger than optimal buses.

Aggregate expenditure elasticity for transport and communication in Australia

For the purpose of estimating Engel elasticity, one needs to find the best functional form among various alternatives. In this paper, a new function, which is called the double semi-log Engel function turns out to be the best functional form for the transport and communication items in Australia on the basis of the distance function (D²) criterion, and the non-nested hypothesis testing procedure. This function is then used to estimate total expenditure elasticity, and the percentage change in consumer demand due to changes in total expenditure and total expenditure inequalities; using the 1975–76 Household Expenditure Survey data. The results of the analyses demonstrate that transport and communication is a necessary item in Australia on the basis of two criteria, viz., its elasticity is not significantly greater than unity, and the percentage change in demand increases with a decrease of the total expenditure inequality [emphasised by Iyengar (I960)]. Policy implication of the analyses has also been discussed.     

Demi-flexible operating policies to promote the performance of public transit in low-demand areas

The efforts of providing attractive transport service to residents in sparse communities have previously focused on operating flexible transit services. This paper identifies a new category of transit policies, called demi-flexible operating policies, to fill the gap between flexible transit services and conventional fixed-route systems. The passenger cost function is defined as the performance measure of transit systems and the analytic work is performed based on a real-world flag-stop transit service, in which we compare its system performance with another two comparable systems, the fixed-route and flex-route services, at expected and unexpected demand levels in order to be closer to reality. In addition, the dynamic-station policy is introduced to assist the flex-route service to better deal with unexpectedly high demand. Experiments demonstrate the unique advantages of demi-flexible operating policies in providing affordable, efficient, and reliable transport service in low-demand operating environments and this work is helpful to optimize the unifying framework for designing public transit in suburban and rural areas.     

Characterisation of and reflections on the synergy of bicycles and public transport

The bicycle is often understood as a disjointed ‘feeder’ mode that provides access to public transport. We argue that combined use of the bicycle and public transport should be understood in a broader perspective, especially where bicycles link to higher speed and higher capacity public transport, such as the train. Cycling and public transport can have a symbiotic relationship forming a hybrid, distinct transport mode, which should be reflected in transport planning. The bicycle is as a way to soften the rigid nature of public transport and thus accommodate diverse individual travel needs and situations. Public transport can be seen as a means to dramatically extend cycling’s speed and spatial reach. We combine a system perspective with conceptual analysis to explore how, why and when this reconsideration is important. We use the Netherlands as illustrative case because of the relative maturity of its bicycle–train connections. The case shows that the synergy between rather opposite yet highly complementary aspects, high speed of the train, high accessibility of the bicycle and flexibility in combining both sub-modes, are the fundamental characteristics to understand the functioning of this system in a wider spatial context. In our conclusion we propose a research agenda, to further explore the relevance of this system for land-use and transport planning and distil wider implications for the international debate.     

Development of railway station choice models to improve the representation of station catchments in rail demand models

ABSTRACT

This paper describes the development of railway station choice models suitable for defining probabilistic station catchments. These catchments can then be incorporated into the aggregate demand models typically used to forecast demand for new rail stations. Revealed preference passenger survey data obtained from the Welsh and Scottish Governments was used for model calibration. Techniques were developed to identify trip origins and destinations from incomplete address information and to automatically validate reported trips. A bespoke trip planner was used to derive mode-specific station access variables and train leg measures. The results from a number of multinomial logit and random parameter (mixed) logit models are presented and their predictive performance assessed. The models were found to have substantially superior predictive accuracy compared to the base model (which assumes the nearest station has a probability of one), indicating that their incorporation into passenger demand forecasting methods has the potential to significantly improve model predictive performance.     

Imperfect reversibility of air transport demand: Effects of air fare,fuel prices and price transmission

There are recent evidence that air transport demand may not have a perfectly reversible relationship with income and jet fuel prices, as is assumed in most demand models. However, it is not known if the imperfectly reversible effects of jet fuel price are a result of asymmetries in the supply side, i.e., asymmetries in cost pass through from fuel prices to air fare, or of demand side behavioral asymmetries whereby people value gains and losses differently. This paper uses US time series data and decomposes air fare and fuel price into three component series to develop an econometric model of air transport demand that is capable of capturing the potential imperfectly reversible relationships and test for the presence or absence of reversibility. We find that air transport demand shows asymmetry with respect to air fare, indicating potential imperfect reversibility in consumer behavior. We also find evidence of asymmetry and hysteresis in cost pass-through from jet fuel prices to air fare, showing rapid increases in airfare when fuel prices increases but a slower response in the opposite direction.     

Improving the forecasting accuracy of air passenger and air cargo demand: the application of back-propagation neural networks

This study employs back-propagation neural networks (BPN) to improve the forecasting accuracy of air passenger and air cargo demand from Japan to Taiwan. The factors which influence air passenger and air cargo demand are identified, evaluated and analysed in detail. The results reveal that some factors influence both passenger and cargo demand, and the others only one of them. The forecasting accuracy of air passenger and air cargo demand has been improved efficiently by the proposed procedure to evaluate input variables. The established model improves dramatically the forecasting accuracy of air passenger demand with an extremely low mean absolute percentage error (MAPE) of 0.34% and 7.74% for air cargo demand.     

The transit network design problem with elastic demand and internalisation of external costs: An application to rail frequency optimisation

In this paper we examine the transit network design problem under the assumption of elastic demand, focusing on the problem of designing the frequencies of a regional metro. In this problem, investments in transit services have appreciable effects on modal split. Neglecting demand elasticity can lead to solutions that may not represent the actual objectives of the design. We propose four different objective functions that can be adopted to assume demand as elastic, considering the costs of all transportation systems (car, bus and rail) as well as the external costs, and we define the constraints of the problem. Heuristic and meta-heuristic solution algorithms are also proposed. The models and algorithms are tested on a small network and on a real-scale network.     

Technical and environmental effects of biodiesel use in local public transport

Biodiesel use in local public transport could be especially significant in improving air quality in cities. The purpose of the experiments described in this paper was to evaluate the various (10, 20 and 50%) blends of biodiesel with diesel in the context of the engine and pollution aspects. As regards the experimental use of these findings on municipal buses, these experiments were the first reference in Hungary. The ages (15–20 years) and types of buses (Ikarus-280, Ikarus-260) used in the experiments are still common vehicles in Hungarian public transport. During our measurements, there was a significant difference between the change in fuel consumption of articulated and solo buses in traffic when compared to test bench measurements. The proportion of the engine performance reduction is nearly the same as that for biodiesel share in the blends. Most pollutants were decreasing (both at idle and full rpm), but this reduction is not directly proportional to the increase of the blending percentage. However, as for CO₂, emission increase was observed in the case of idle rpm in comparison to normal diesel operation, even though this phenomenon was not due to biodiesel use, but the catalytic converter and the fact that biodiesel was used for the first time in the engine concerned.     

Integrating parking behaviour in activity-based travel demand modelling: Investigation of the relationship between parking type choice and activity scheduling process

Traditionally, the parking choice/option is considered to be an important factor in only in the mode choice component of a four-stage travel demand modelling system. However, travel demand modelling has been undergoing a paradigm shift from the traditional trip-based approach to an activity-based approach. The activity-based approach is intended to capture the influences of different policy variables at various stages of activity-travel decision making processes. Parking is a key policy variable that captures land use and transportation interactions in urban areas. It is important that the influences of parking choice on activity scheduling behaviour be identified fully. This paper investigates this issue using a sample data set collected in Montreal, Canada. Parking type choice and activity scheduling decision (start time choice) are modelled jointly in order to identify the effects of parking type choice on activity scheduling behaviour. Empirical investigation gives strong evidence that parking type choice influences activity scheduling process. The empirical findings of this investigation challenge the validity of the traditional conception which considers parking choice as exogenous variable only in the mode choice component of travel demand models.     

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.