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.     

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.     

A survey of Hungarian transport policy

Abstract

In its introductory part this article discusses the principles of the transport policy approved in 1968, followed by the reasons behind the advances on this policy approved in 1978.

It then goes on to review the Hungarian transport pattern and organization, including the roles played by the railways, the road transport companies, the state‐owned enterprises as well as cooperatives, urban transport, shipping, air transport, pipelines, and private transport.

In discussing the division of labour (or market sharing) in transport it concludes that passenger transport is increasing slowly, while the proportion of private transport is continuing to rise. A moderate increase is expected in goods transport with a decline in the share of the railways and a rise in that of the other transport branches. This division of labour is being influenced by economic, not administrative, means.

The main target of the advanced transport policy is to shape a transport system which corresponds to socioeconomic requirements. This means that goods transport capacities must be put to more efficient use, which involves improving development, organizational and planning operations. In passenger transport priority must go to public transport while the proportion of private transport must be defined in keeping with demand and economic possibilities.

In the development of the infrastructure and investments, the need to improve energy use and protect the environment must be stressed.

The rest of the article presents the detailed reasoning behind the measures already taken and scheduled to be taken to achieve these main targets.     

Impacts of highly automated vehicles on travel demand: macroscopic modeling methods and some results

Automated vehicles (AV) will change transport supply and influence travel demand. To evaluate those changes, existing travel demand models need to be extended. This paper presents ways of integrating characteristics of AV into traditional macroscopic travel demand models based on the four-step algorithm. It discusses two model extensions. The first extension allows incorporating impacts of AV on traffic flow performance by assigning specific passenger car unit factors that depend on roadway type and the capabilities of the vehicles. The second extension enables travel demand models to calculate demand changes caused by a different perception of travel time as the active driving time is reduced. The presented methods are applied to a use case of a regional macroscopic travel demand model. The basic assumption is that AV are considered highly but not fully automated and still require a driver for parts of the trip. Model results indicate that first-generation AV, probably being rather cautious, may decrease traffic performance. Further developed AV will improve performance on some parts of the network. Together with a reduction in active driving time, cars will become even more attractive, resulting in a modal shift towards car. Both circumstances lead to an increase in time spent and distance traveled.

     

Structural equation modeling for national travel demand: an examination of the relationships between communication modes

This paper examines the relationships among different transportation modes, and between transportation and telecommunications, by applying the structural equation modeling (SEM) technique. For this purpose, we collected and compiled time series data on national travel demand, and socioeconomic and telecommunications conditions in Taiwan, and built national travel demand models using SEM. The estimation results show that the relationship between telecommunications and transportation demand (either car ownership or public transportation) is more complementary than substitutional. Moreover, car ownership is a type of inelastic necessity good, and its relationship with public transportation is more substitutional than complementary. Finally, among the three public transportation modes – rail, bus and domestic air – it is found that air is weakest in terms of competitive power. From the viewpoint of long-term forecasting trends, the bus holds its competitive power in comparison with other public transportation modes and would not be replaced in the future.     

Planning the driverless city

ABSTRACT

AV technologies have the potential to transform urban landscapes and existing transport systems and networks. Yet, the utopian imaginary of reduced automobile ownership and a new shared economic future sits in tension with suggestions that car dependency, urban sprawl and transport inaccessibility will be exacerbated. The issues are situated in a complex governance landscape involving an influential private sector who are increasingly setting the agenda. The public sector may be forced into reacting to the new innovations by information technology and automobile companies as they are introduced into existing built environments. Drawing on an extensive literature base and interviews with public sector planners, this paper reveals the conceptual gaps in the framing of AV technology – the prospects and limits – and how these are conceived. The paper raises questions about the role urban planning can play in the rollout of AVs in order to anticipate and mediate unwanted built environment and socio-spatial impacts, as well as reconciling the ambition of transport innovation with the public purpose of planning.     

The introduction of innovation in Urban transport

More than 200 new systems of transport have been proposed as solutions to problems of urban congestion. However, very few of these have reached even the prototype stage and practically none at all have ever actually been installed.

The author asks himself why this is so. If an invention is to be introduced into a field which is poorly receptive to innovation, it must not only bring something really new and attractive for the users on the functional level as opposed merely to the technological level, but must also consider the political, industrial, social and human context.

The author gives two examples of innovation conceived and developed at the Battelle Geneva Research Centre: one for private transport, a new system for an electric car which will include the interests of the petrol industry, and the other for public transport, the “Speedaway” sponsored by Dunlop Limited. These two systems will be put on the market shortly and will attempt to fulfill the criteria mentioned above.     

The utilisation and user characteristics of Uber services in London

ABSTRACT

Ridesourcing services such as Uber are nowadays a common feature within available transport options of many cities around the world (E.g. London & San Francisco). There has been much publicity about the potential impacts of ridesourcing services and how (or if) they should be managed or regulated without an objective understanding of who uses these services and why, as well as its current and future implications for public transport (PT).

Ridesourcing is part of a broader tech-driven, mobile app-based sharing phenomenon – the ‘sharing economy’ – which has disrupted traditional market models and industries, for example, the transport industry, where new players such as Uber have emerged and have quickly become part of the urban transport landscape. Uber has been at the forefront in disrupting the transport sector since its first launch in 2010 (San Francisco, USA). Since its launch, Uber has generated extensive media coverage and debate among policymakers, transport planners and transport authorities on how these services are affecting traditional transport modes such as buses and taxis. However, without objective empirical data – in terms of impacts on trip making characteristics, PT ridership and congestion – policymakers and transport regulators are yet to fully understand the real impacts ridesourcing services are having on the transport network.

This paper is part of broader research that aims to provide insights and empirical-based evidence on how Uber services are used (UberX and Uberpool) in London. A comprehensive survey was undertaken using a detailed questionnaire, issued to UberX and Uberpool users in London to gather detailed data on who uses the Uber services, why they use it and what are the trip purposes, in order to understand Uber user demographics and what effects (if any) Uber services are having on PT usage and trip making characteristics in London. The final findings provide important insights on Uber user demographics, trip purposes, types of trips replaced, impact on car ownership and why travellers use Uber services.     

Short-term impact analysis of fuel price policy change on travel demand in Malaysian cities

Abstract

Malaysia is one of the few countries in the world that provides a fuel subsidy to consumers. Due to the recent economic crisis, the Malaysian Government decided to revise its fuel subsidization policy from a fixed price subsidy to a floating price subsidy dependent on global oil demand. Recognizing that the change in fuel subsidization policy can have an impact on travel behavior, this article investigates the short-term impact of the policy change on private and public transportation in the Klang Valley region of Malaysia. Spectral analyses are performed to investigate if the policy change has an impact on private vehicle travel demand, measured in terms of road traffic, and short-term travel demand elasticity with respect to fuel price is estimated. To measure the impact on the public transportation system, the demand cross-elasticity values of rail transit and buses are also estimated. It was found that traffic flow reduces with an increase in fuel price, although elasticity and cross-elasticity values obtained are low. The article finds that there is a potential mode shift from private vehicles to rail transit with increasing fuel price. It is demonstrated that reducing fuel price subsidy can be an effective travel demand management strategy to alleviate congestion.     

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.     

Evaluating Flexible Transport Solutions

Abstract

Flexible transport services (FTS) have been of increasing interest in developing countries as a bridge between the use of personal car travel and fixed route transit services. This paper reports on findings from a recent study in Queensland Australia, which identified lessons from an international review and implications for Australia. Potential strategic directions, including a vision, mission, key result areas, strategies, and identified means of measuring performance are described. Evaluation criteria for assessing flexible transport proposals were developed, and approaches to identifying and assessing needs and demands outlined. The use of emerging technologies is also a key element of successful flexible transport services.     

Forecasting petrol demand and assessing the impact of selective strategies to reduce fuel consumption

Abstract

The use of fossil fuels in transportation is an important topic as a result of growing concerns over global warming. Automobile petrol demand has been of particular interest to researchers and policy-makers, given that the automobile is a major contributor to the enhanced greenhouse effect. This paper forecasts Australia's automobile petrol demand up to the year 2020 based on the best performing forecasting model selected out of eight models. In order to establish ways to reduce the demand for petrol, and the consequent by-product of reducing the amount of greenhouse gas emissions, we have estimated the impact on CO₂ for several potential policy instruments, using Transportation and Environment Strategy Impact Simulator (an integrated transport, land use and environmental strategy impact simulation programme). We find that a carbon tax of AU$0.50/kg can reduce automobile kilometres by 5.9%, resulting in reduced demand for petrol and a reduction in CO₂ of 1.5%.     

Relationships Between US Consumer Expenditures on Communications and Transportation Using Almost Ideal Demand System Modeling: 1984–2002

Abstract

This study analyzes aggregate consumer expenditure data from the US between 1984 and 2002, to determine relationships between expenditures on transportation and communications. We first identified 15 categories of goods – nine for transportation, five for communications, and one for all others – and obtained prices for each category across time. Then, we applied the linear approximate almost ideal demand system (AIDS) method for estimating consumer demand functions, aggregating the categories to six (non-personal vehicle (PV), PV capital, PV operation, electronic communications media, print communications media, and all others) due to the small sample size. The results indicate that transportation and communications categories have both substitution and complementarity relationships. The existence of effects in both directions (substitution and complementarity) is testimony to the complexity of the relationships involved, with both generation and replacement possible and happening simultaneously. In addition, expenditures in the transportation categories are generally more income-elastic and price-elastic than those in communications, indicating that communications expenditures are more essential than those for travel. The transportation categories have both substitution and complementarity relationships with each other, while the two communications categories have a substitution relationship.     

A Review of Ex-Post Evidence for Mode Substitution and Induced Demand Following the Introduction of High-Speed Rail

ABSTRACT

To date, relatively little is known about the nature of the demand for high-speed rail (HSR) soon after inauguration of the services, despite close to 50-year experience of HSR operation and 17 166?km of HSR network around the world. This is a real lacuna given the scale of HSR construction around the world, the amount of resources committed to it, the desired accessibility, economic and environmental effects associated with HSR development and the relatively poor track record of forecasting demand for HSR services. Focusing on mode substitution and induced demand effects, this review aims to fill the gap in knowledge about the ex-post demand for HSR services in order to facilitate a learning process for the planning of the future HSR network. Although there is not much evidence on the demand for HSR services and existing evidence is largely influenced by route-specific characteristics, a methodological limitation that must be acknowledged, the evidence presented allows a better characterisation of HSR as a mode of transport. The review shows that the demand for HSR a few years after inauguration is about 10–20% induced demand and the rest is attributed to mode substitution. In terms of mode substitution, in most cases the majority of HSR passengers have used the conventional rail before. Substitution from aircraft, car and coach is generally more modest.     

Solving the station-based one-way carsharing network planning problem with relocations and non-linear demand

One-way station-based carsharing systems allow users to return a rented car to any designated station, which could be different from the origin station. Existing research has been mainly focused on the vehicle relocation problem to deal with the travel demand fluctuation over time and demand imbalance in space. However, the strategic planning of the stations’ location and their capacity for one-way carsharing systems has not been well studied yet, especially when considering vehicle relocations simultaneously. This paper presents a Mixed-integer Non-linear Programming (MINLP) model to solve the carsharing station location and capacity problem with vehicle relocations. This entails considering several important components which are for the first time integrated in the same model. Firstly, relocation operations and corresponding relocation costs are taken into consideration to address the imbalance between trip requests and vehicle availability. Secondly, the flexible travel demand at various time steps is taken as the input to the model avoiding deterministic requests. Thirdly, a logit model is constructed to represent the non-linear demand rate by using the ratio of carsharing utility and private car utility. To solve the MINLP model, a customized gradient algorithm is proposed. The application to the SIP network in Suzhou, China, demonstrates that the algorithm can solve a real world large scale problem in reasonable time. The results identify the pricing and parking space rental costs as the key factors influencing the profitability of carsharing operators. Also, the carsharing station location and fleet size impact the vehicle relocation and carsharing patronage.     

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.     

Optimal transit fare in a bimodal network under demand uncertainty and bounded rationality

This paper investigates the optimal transit fare in a simple bimodal transportation system that comprises public transport and private car. We consider two new factors: demand uncertainty and bounded rationality. With demand uncertainty, travelers are assumed to consider both the mean travel cost and travel cost variability in their mode choice decision. Under bounded rationality, travelers do not necessarily choose the travel mode of which perceived travel cost is absolutely lower than the one of the other mode. To determine the optimal transit fare, a bi‐level programming is proposed. The upper‐level objective function is to minimize the mean of total travel cost, whereas the lower‐level programming adopts the logit‐based model to describe users' mode choice behaviors. Then a heuristic algorithm based on a sensitivity analysis approach is designed to solve the bi‐level programming. Numerical examples are presented to illustrate the effect of demand uncertainty and bounded rationality on the modal share, optimal transit fare and system performance. Copyright © 2013 John Wiley & Sons, Ltd.     

Towards a general microeconomic model for the operation of public transport

After Vickrey's view, Mohring constructed a microeconomic model to determine the optimal frequency of buses serving a corridor with fixed demand. The main result was that frequency should be proportional to the square root of demand. The role of users' costs was shown to be crucial. This approach has evolved over the past decades, improving our understanding of public transport operations. This paper describes and analyses the evolution of microeconomic models for the analysis of public transport services with parametric demand, leading towards a more comprehensive one. An in-depth review of all the contributions in the academic literature is presented, emphasizing both the treatment of variables and the form of the results mostly in terms of frequency and fleet size. A series of partial new elements is also identified. An extension of Jansson's model for a single period is developed analytically, including the effect of vehicle size on operating costs and the influence of crowding on the value of time. Numerical simulations are used for comparison and analysis. A general model is then proposed where bus operations are optimized accounting for a number of simultaneous relations. Finally, the different models are discussed and compared.     

Urban transport policy development: two case studies in the Middle East

Abstract

The recent completion of two major transport studies of predominantly urban areas in the Middle East (Amman‐Jordan and Bahrain) has provided the opportunity to compare and contrast the transport characteristics of, and medium term transport policies for, the two areas.

While in structure the two transport systems have many similarities, their base year usage differs significantly. In view of the much lower income levels in Amman, and the resulting lower levels of car ownership, greater reliance is placed on public transport in Amman than in the more car‐oriented society in Bahrain. Against this background, and in the context of broadly similar overall levels of growth in travel demand, their development in the medium term future should follow different paths. Amman will need to depend on public transport very heavily, with only limited road building. Bahrain should be able to develop a satisfactory road system, with public transport playing its current role except for the provision of services for some relatively modest number of restrained private vehicle users. In both cases, however, substantial investment in off‐street parking spaces is needed.

The paper briefly describes the social and economic backgrounds of the two areas, and reviews the transport systems and the organisations responsible for them. Travel demand forecasts are summarized, leading to the transport plan and policy development. The prospects for implementation are discussed, and the paper lastly focuses on some aspects which are key to the development of the transport systems in the two countries.