Traffic dynamics in a bi-modal transportation network with information provision and adaptive transit services

This paper has two major components. The first one is the day-to-day evolution of travelers’ mode and route choices in a bi-modal transportation system where traffic information (predicted travel cost) is available to travelers. The second one is a public transit operator adjusting or adapting its service over time (from period to period) based on observed system conditions. Particularly, we consider that on each day both travelers’ past travel experiences and the predicted travel cost (based on information provision) can affect travelers’ perceptions of different modes and routes, and thus affect their mode choice and/or route choice accordingly. This evolution process from day to day is formulated by a discrete dynamical model. The properties of such a dynamical model are then analyzed, including the existence, uniqueness and stability of the fixed point. Most importantly, we show that the predicted travel cost based on information provision may help stabilize the dynamical system even if it is not fully accurate. Given the day-to-day traffic evolution, we then model an adaptive transit operator who can adjust frequency and fare for public transit from period to period (each period contains a certain number of days). The adaptive frequency and fare in one period are determined from the realized transit demands and transit profits of the previous periods, which is to achieve a (locally) maximum transit profit. The day-to-day and period-to-period models and their properties are also illustrated by numerical experiments.     

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.     

A reliability‐based traffic assignment model for multi‐modal transport network under demand uncertainty

In densely populated and congested urban areas, the travel times in congested multi‐modal transport networks are generally varied and stochastic in practice. These stochastic travel times may be raised from day‐to‐day demand fluctuations and would affect travelers' route and mode choice behaviors according to their different expectations of on‐time arrival. In view of these, this paper presents a reliability‐based user equilibrium traffic assignment model for congested multi‐modal transport networks under demand uncertainty. The stochastic bus frequency due to the unstable travel time of bus route is explicitly considered. By the proposed model, travelers' route and mode choice behaviors are intensively explored. In addition, a stochastic state‐augmented multi‐modal transport network is adopted in this paper to effectively model probable transfers and non‐linear fare structures. A numerical example is given to illustrate the merits of the proposed model. Copyright © 2012 John Wiley & Sons, Ltd.     

A stochastic multimodal reliable network design problem under adverse weather conditions

This paper formulates a network design problem (NDP) for finding the optimal public transport service frequencies and link capacity expansions in a multimodal network with consideration of impacts from adverse weather conditions. The proposed NDP aims to minimize the sum of expected total travel time, operational cost of transit services, and construction cost of link capacity expansions under an acceptable level of variance of total travel time. Auto, transit, bus, and walking modes are considered in the multimodal network model for finding the equilibrium flows and travel times. In the proposed network model, demands are assumed to follow Poisson distribution, and weather‐dependent link travel time functions are adopted. A probit‐based stochastic user equilibrium, which is based on the perceived expected travel disutility, is used to determine the multimodal route of the travelers. This model also considers the strategic behavior of the public transport travelers in choosing their routes, that is, common‐line network. Based on the stochastic multimodal model, the mean and variance of total travel time are analytical estimated for setting up the NDP. A sensitivity‐based solution algorithm is proposed for solving the NDP, and two numerical examples are adopted to demonstrate the characteristics of the proposed model. Copyright © 2014 John Wiley & Sons, Ltd.     

Modeling competitive multi-modal transit services: a nested logit approach

In metropolitan areas where multi-modal trips are common, modeling the combined-mode choices of travelers, and the strategic interactions between the private service operators are important issues. This study developed a novel network approach, designated as state-augmented multi-modal (SAM) network, to explicitly consider transfer behaviors and non-linear fare structures. To overcome the independence of irrelevant alternatives (IIA) assumption associated with the standard logit approach, we integrated the SAM network with the nested logit (NL) approach. Specifically, we developed a three-level NL choice model to deal with the complex and inter-related decisions in a multi-modal network: the first level focuses on combined-mode choice, the second on transfer location choice, and the third on route choice. Using this NL SAM network as a platform, we examined the effect of fare competition on company profitability as well as on overall network congestion. A case study of the ground transportation system connecting the Hong Kong International Airport to the downtown area is provided to illustrate the approach.     

Impact of ITS measures on public transport: A Case study

Intelligent Transport Systems (ITS) have a wide range of applications. They range from the more traditional signal coordination system to concepts such as smart cars and smart roads. This paper describes transit‐based ITS measures in Singapore. The island‐state has plans to double the current 90 km rail network over the next ten years and has also implemented or committed to implement many ITS initiatives that impact upon the public transport systems. The aim of these investments is to achieve a high transit modal share using a comprehensive transit network. ITS measures that can promote this aim include: automatic vehicle location systems for buses and taxis, integrated transit fare systems using contactless smart cards, rail information systems, multi‐modal travel guides on Internet and electronic road pricing. The potential impacts of these measures are delay reduction, more comfort, productivity gain and better network accessibility. ITS measures do not necessarily add physical capacity to a public transport system but are excellent supporting measures to encourage the modal shift to transit, particularly if a quality transit system is already in place.     

Perceived accessibility,mobility, and connectivity of public transportation systems

Although public transportation is considered effective at reducing the external cost of driving private vehicles, many urbanites do not use public transportation. This study develops measures employing accessibility, mobility, and seamless connectivity for an entire public transportation service chain as indicators for evaluating public transport services, prioritizes underperforming scenarios from the perspective of urban travelers, and derives various market segmentation strategies that consider different socio-demographic characteristics. A conceptual model is set up herein to assess these latent constructs that describe unobservable and immeasurable characteristics. As a Likert ordinal scale can generate misleading statistical inferences, the Rasch model is used to eliminate bias generated by an ordinal scale when measuring these three latent constructs separately. The Rasch model compares person parameters with item parameters, which are then subjected to logarithmic transformation along a logit scale so as to recognize specific difficulties of service scenarios that cannot be easily eliminated by certain urban travelers. The multidimensional Rasch model also measures the perceptions of urban travelers in terms of the interactions between accessibility, mobility, and seamless connectivity of this public transportation system. While comparing urban travelers of two large cities in Taiwan, Taipei and Kaohsiung, the empirical results demonstrate that perceived accessibility, mobility, and seamless connectivity differ based on travelers’ age, frequency of weekly sports activities, and environmental awareness. This paper also advances appropriate improvement strategies and provides policy suggestions for urban planners, public transportation service operation agencies, and policy makers when they seek to create user-friendly public transportation services. The proposed approach can be generalized in other cities by considering their local context uniqueness and further evaluating their public transport services.     

Urban transport in Germany: providing feasible alternatives to the car

With the second highest level of car ownership in the world, and the third highest population density in Europe, Germany has adopted a range of policies to balance the many private benefits of car use with its serious social and environmental problems. In order to ‘tame’ the car, most German cities have implemented a twofold strategy of expanding and improving pedestrian, bicycling and public transport alternatives simultaneously with restricting car use and making it more expensive. That has increased political acceptability since the car‐restrictive measures are not perceived as mere punishment of car drivers. The results of this coordinated urban transport strategy have been impressive. Germany, as a whole, has managed to increase public transport use and to stabilize the car share of modal split. Some cities, of course, have been more successful than others, and this paper examines three of the most successful cities: Münster, Freiburg and Munich. In each of the cities, the percentage of travel by bicycling, walking and public transport has been raised over the past 20 years, while the car's share of modal split has fallen. This article documents the range of policies used to restrict car use, both in Germany as a whole, and in the three case‐study cities in particular. The key to success is found to be mutually reinforcing transport and land‐use policies. It is the combination of a whole set of coordinated policies that explains the dramatic success in changing travel behavior.     

Matatu: A Case Study of the Core Segment of the Public Transport Market of Kampala,Uganda

Abstract

In Uganda, public transport is provided by a four‐tiered public transport system, with the Matatu (usually Toyota cabin‐transporters of 1990s make) as its backbone, providing the widest, densest and cheapest connectivity. The article shares findings of a survey on perceptions, profiles and aspirations of drivers/conductors/stage personnel and of passengers. They show that entering a career within the Matatu business opens choices and promises inclusion into a relatively strong social network. For passengers, the Matatu offers a cost‐effective opportunity to commute to places of work, transport goods and connect with business partners. The findings also point to limitations of the current public transport system, with emphasis on lacking client care, e.g. fare cheating by conductors. There is a need to better understand the dynamics of urban transport systems against the background of expanding urbanization in low‐income countries. This article has attempted to contribute to that need.     

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.     

Policy analysis of third party electronic coupons for public transit fares

Mobile technologies are generating new business models for urban transport systems, as is evident from recent startups cropping up from the private sector. Public transport systems can make more use of mobile technologies than just for measuring system performance, improving boarding times, or for analyzing travel patterns. A new transaction model is proposed for public transport systems where travelers are allowed to pre-book their fares and trade that demand information to private firms. In this public-private partnership model, fare revenue management is outsourced to third party private firms such as big box retail or large planned events (such as sports stadiums and theme parks), who can issue electronic coupons to travelers to subsidize their fares. This e-coupon pricing model is analyzed using marginal cost theory for the transit service and shown to be quite effective for monopolistic coupon rights, particularly for demand responsive transit systems that feature high cost fares, non-commute travel purposes, and a closed access system with existing pre-booking requirements. However, oligopolistic scenarios analyzed using game theory and network economics suggest that public transport agencies need to take extreme care in planning and implementing such a policy. Otherwise, they risk pushing an equivalent tax on private firms or disrupting the urban economy and real estate values while increasing ridership.     

The Downs–Thomson Paradox with responsive transit service

Downs (1962) and Thomson (1977) suggested that highway capacity expansion may produce counterproductive effects on the two-mode (auto and transit) transport system (Downs–Thomson Paradox). This paper investigates the occurrence of this paradox when transit authority can have different economic objectives (profit-maximizing or breakeven) and operating schemes (frequency, fare, or both frequency and fare). For various combinations of economic objectives and operating schemes, the interaction between highway expansion and transit service is explored, as well as its impact on travelers’ mode choices and travel utilities. Further, for each combination, the conditions for occurrence of the Downs–Thomson Paradox are established. We show that the paradox never occurs when transit authority is profit-maximizing, but it is inevitable when the transit authority is running to maximize travelers’ utility while maintaining breakeven. This is because the former transit authority tends to enhance transit service (e.g., raise frequency or reduce fare) when facing an expanded highway; and on the contrary, the latter tends to compromise transit service (e.g., reduce frequency or raise fare). Both analytical and numerical examples are provided to verify the theoretical results.     

Physics of day-to-day network flow dynamics

This paper offers a new look at the network flow dynamics from the viewpoint of physics by demonstrating that the traffic system, in terms of the aggregate effects of human behaviors, may exhibit like a physical system. Specifically, we look into the day-to-day evolution of network flows that arises from travelers’ route choices and their learning behavior on perceived travel costs. We show that the flow dynamics is analogous to a damped oscillatory system. The concepts of energies are introduced, including the potential energy and the kinetic energy. The potential energy, stored in each link, increases with the traffic flow on that link; the kinetic energy, generated by travelers’ day-to-day route swapping, is proportional to the square of the path flow changing speed. The potential and kinetic energies are converted to each other throughout the whole flow evolution, and the total system energy keeps decreasing owing to travelers’ tendency to stay on their current routes, which is analogous to the damping of a physical system. Finally, the system will approach the equilibrium state with minimum total potential energy and zero kinetic energy. We prove the stability of the day-to-day dynamics and provide numerical experiments to elucidate the interesting findings.     

Deregulation of inter‐city coach services in Britain

Public transport in Britain has traditionally operated under conditions of regulation. The 1930 Road Traffic Act imposed controls upon the quantity and quality of transport regulations, with an abolition of the quantity controls associated with inter‐city coach services. The principal objectives of the Act were to eliminate restriction upon entry to the market and to promote competition between coach operators.

This paper is based on research which was undertaken to establish the impact of the 1980 Transport Act upon express (inter‐city) coach services in Britain. The effects of the legislation are examined in relation to the experience of various coach operators, British Rail, and the inter‐city traveller. This provides evidence of the way in which the supply of, and demand for, public transport behaves in a competitive, deregulated environment. It is shown that at least in net terms, the consumer has enjoyed short‐term benefits. Greater uncertainty surrounds the long‐term situation. The main competition has been confined to the principal trunk routes and has taken place between the state‐owned undertaking of National Express and British Rail. The outcome of deregulation for the private sector has been disappointing.

The paper identified similarities which exist between inter‐city and local public transport services. In this context, the lessons derived from express deregulation are employed to suggest likely developments in the deregulation of stage carriage (local) services in Britain.     

Estimation of a route choice model for urban public transport using smart card data

This paper describes a logit model of route choice for urban public transport and explains how the archived data from a smart card-based fare payment system can be used for the choice set generation and model estimation. It demonstrates the feasibility and simplicity of applying a trip-chaining method to infer passenger journeys from smart card transactions data. Not only origins and destinations of passenger journeys can be inferred but also the interchanges between the segments of a linked journey can be recognised. The attributes of the corresponding routes, such as in-vehicle travel time, transfer walking time and to get from alighting stop to trip destination, the need to change, and the time headway of the first transportation line, can be determined by the combination of smart card data with other data sources, such as a street map and timetable. The smart card data represent a large volume of revealed preference data that allows travellers' behaviour to be modelled with higher accuracy than by using traditional survey data. A multinomial route choice model is proposed and estimated by the maximum likelihood method, using urban public transport in ?ilina, the Slovak Republic, as a case study     

Public transit service operation strategy under indifference thresholds‐based bi‐modal equilibrium

This paper investigates public transit service (fare and frequency) operation strategies in a bi‐modal network with assumption of indifference thresholds‐based travelers' mode choice behavior. Under such behavior, users would switch to a new mode only if its utility is larger than the utility of current mode plus a threshold. The concept of indifference thresholds‐based bi‐modal equilibrium (ITBE) and the properties of the ITBE solution are explicitly proposed. Considering transit operator's different economic objectives (profit‐maximizing, no‐deficit and total system cost‐minimizing), the effect of indifference thresholds on transit fare and frequency schemes is studied. Some numerical experiments are accompanied to verify the theoretical results. Copyright © 2016 John Wiley & Sons, Ltd.     

A path-based flow formulation for the traffic assignment problem

In order to improve cooperation between traffic management and travelers, traffic assignment is the key component to achieve the objectives of both traffic management and route choice decisions for travelers. Traffic assignment can be classified into two models based on the behavioral assumptions governing route choices: User Equilibrium (UE) and System Optimum (SO) traffic assignment. According to UE and SO traffic assignment, travelers usually compete to choose the least cost routes to minimize their own travel costs, while SO traffic assignment requires travelers to work cooperatively to minimize overall cost in the road network. Thus, the paradox of benefits between UE and SO indicates that both are not practical. Thus, a solution technique needs to be proposed to balance UE and SO models, which can compromise both sides and give more feasible traffic assignments. In this paper, Stackelberg game theory is introduced to the traffic assignment problem, which can achieve the trade-off process between traffic management and travelers. Since traditional traffic assignments have low convergence rates, the gradient projection algorithm is proposed to improve efficiency.     

Commuting trip satisfaction in Beijing: Exploring the influence of multimodal behavior and modal flexibility

In the past decade, many studies have explored the relationship between travelers’ travel mode and their trip satisfaction. Various characteristics of the chosen travel modes have been found to influence trip experiences; however, apart from the chosen modes, travelers’ variability in mode use and their ability to vary have not been investigated in the trip satisfaction literature. This current paper presents an analysis of commuting trip satisfaction in Beijing with a particular focus on the influence of commuters’ multimodal behavior on multiple workdays and their modal flexibility for each commuting trip. Consistent with previous studies, we find that commuting trips by active modes are the most satisfying, followed by trips by car and public transport. In Beijing, public transport dominates. Urban residents increasingly acquire automobiles, but a strict vehicle policy has been implemented to restrict the use of private cars on workdays. In this comparatively constrained context for transport mode choice, we find a significant portion of commuters showing multimodal behavior. We also find that multimodal commuters tend to feel less satisfied with trips by alternative modes compared with monomodal commuters, which is probably related to their undesirable deviation from habitual transport modes. Furthermore, the relationship between modal flexibility and trip satisfaction is not linear, but U-shaped. Commuters with high flexibility are generally most satisfied because there is a higher possibility for them to choose their mode of transport out of preference. Very inflexible commuters can also reach a relatively high satisfaction level, however, which is probably caused by their lower expectations beforehand and the fact that they did not have an alternative to regret in trip satisfaction assessments.     

Bottleneck congestion pricing and modal split: Redistribution of toll revenue

The paper examines the question of the redistribution of toll revenue as seen in a bottleneck congestion model. Our objective is to analyse the impact of this redistribution on total cost and on modal split between railroad and road. Following Tabuchi’s two-mode model (Tabuchi, T., 1993. Bottleneck congestion and modal split. Journal of Urban Economics 34, 414-431.), we integrate a redistribution of toll revenue towards public transport into our study. In this context, we investigate two kinds of road toll regimes: a fine toll and a uniform toll. We will consider two types of railroad fare: when it is set equal to the marginal cost and when it is set equal to average cost. These models allow us to show that toll policy to be more efficient as long as toll revenue is directed towards public transport when the railroad fare is equal to average cost.     

Modeling intermodal equilibrium for bimodal transportation system design problems in a linear monocentric city

This paper investigates the intermodal equilibrium, road toll pricing, and bus system design issues in a congested highway corridor with two alternative modes - auto and bus - which share the same roadway along this corridor. On the basis of an in-depth analysis of the demand and supply sides of the bimodal transportation system, the mode choice equilibrium of travelers along the continuum corridor is first presented and formulated as an equivalent variational inequality problem. The solution properties of the bimodal continuum equilibrium formulation are analytically explored. Two models, which account for different infrastructure/system regulatory regimes (public and private), are then proposed. In the public regulatory model, the road toll location and charge level are simultaneously optimized together with the bus service fare and frequency. In the private regulatory model, the fare and frequency of bus services, which are operated by a profit-driven private operator, are optimized for exogenously given toll pricing schemes. Finally, an illustrative example is given to demonstrate the application of the proposed models. Sensitivity analysis of residential/household distribution along the corridor is carried out together with a comparison of four different toll pricing schemes (no toll, first best, distance based, and location based). Insightful findings are reported on the interrelationships among modal competition, market regulatory regimes, toll pricing schemes, and urban configurations as well as their implications in practice.