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.     

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.     

Relationship between service quality and demand for inter-urban buses

This article proposes a model for analysing the modal choice of travellers making inter-urban journeys. Discrete choice models with systematic and random tastes variation were applied to find the most relevant variables for encouraging the use of public transport by bus rather than private car. This research follows on from the results of previous user satisfaction studies on inter-urban bus services in the province of Burgos (Spain). Willingness to pay is also estimated for time savings or other improvements in the bus service.The results indicate that, in general, improvements in the journey time or the number of daily journeys are valued less by inter-urban bus users than they are by car or railway users. The type of bus and its characteristics are evaluated as a function of the distance travelled and result in very small values for this variable. Contrary to what is often reported in satisfaction surveys, the journey cost is found to be relevant when choosing which mode of transport to use, but the most important variable is journey time. Little value is placed on the features of the bus, except on long distance journeys.Finally, a methodology differentiating four hierarchical groups is presented for comparing the results of the relevant variables in demand and satisfaction models. Some only improve perception rather than encourage new users, while others increase take-up but do not improve the image of the service.     

Estimating heterogeneity of car travelers on mode shifting behavior based on discrete choice models

In order to understand the mode shift behavior of car travelers and relieve traffic congestion, a Stated Preference survey has been conducted in the city of Ji'nan in China to analyze bus choice behavior and the heterogeneity of car travelers. Several discrete choice models, including multinomial logit, mixed logit and latent class model (LCM) are developed based on these survey data. A comparative analysis indicates that the LCM has the highest precision and is more suitable to analyze the heterogeneity of car travelers. The LCM divides car travelers into three classes. Different classes have different sets of influencing factors in the model. Policy recommendations are also proposed for those classes to promote bus shift from car travelers based on the model results. Finally, sensitivity analysis on parking fees and fuel cost is carried out on the LCMs under different bus service levels. Car travelers have different sensitivities to the influencing factors. The conclusions indicate that the LCM can reflect the heterogeneity and preferences of car travelers and can be used to understand how to shift the behavior of car travelers and make more effective traffic policy.     

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.     

Accommodating preference heterogeneity in commuting mode choice: an empirical investigation in Shaoxing,China

A latent class model is developed to accommodate preference heterogeneity across commuters with respect to their mode choice between electric bike, private car, and public bus within the context of China. A three-segment solution – ‘electric bike individuals’, ‘private car addicts’, and ‘public bus enthusiasts’ – is identified, each characterized by heterogeneous preferences regarding specific mode attributes and unique socio-demographic profile. The choice model confirms the determinative effects of perceived alternative attributes on commuting mode choice, while the traditionally used objective attributes – travel time and cost – are found to have relatively small influences. The membership model provides solid explanations for these segment-specific preferences. This study provides a better understanding of the nature of mode choice behavior, which can be useful for strategies tailored to a specific segment in order to promote the use of sustainable transport modes.     

The asymmetric effects of service quality on passengers' choice of carriers for international air travel

The asymmetric effects of service quality on international travelers' airline choice behavior were investigated in this paper. The linear structural equation modeling system was first applied to quantify passengers' perceptions of service quality provided by airlines, which were then used as the input variables of the asymmetric response model developed to capture international travelers' airline decision. Their asymmetric responses to various service quality of airlines were assumed to be either gains or losses with respect to their reference points. The results showed that the asymmetric response model performs better than the traditional logit models that capture only symmetrical effects.     

Patterns of car usage and restraint modelling

Transport demand forecasting procedures have traditionally employed household based modal split models implicitly assuming a selection of mode for each trip based on relative generalised cost. A detailed examination of the trip patterns of a sample of household in West Yorkshire shows that in fact there is little discretionary choice of public transport; public transport trips in car owning households generally being explained in terms of the specific unavailability of the car for such trips. Two versions of a category analysis model for modal split are based on this observation and applied to household data for Glamorgan and Monmouthshire to show that such a procedure is workable and produces results comparing favourably with traditional approaches. The likely implications of three types of restraint policy are examined and it is concluded that the existing interdependence in trip patterns and modal choice within the household is of great significance in determining their effects. In particular it appears that positive attempts to increase vehicle occupancy at the peak are likely to be more favourable to public transport finances than the more negative policies to restrain use of the car for journey to work, or second car ownership.     

Continuous price and flow dynamics of tradable mobility credits

This study examines the price and flow dynamics under a tradable credit scheme, when the credits can be traded in a free market. A continuous dynamic model in a finite time horizon is proposed to describe the travelers’ learning behavior and the evolution of network flows and credit price, and then the existence and uniqueness of the equilibria are established. The conditions for stability and convergence of the dynamic system as the time horizon extends to infinity and the impact of limited implementation time horizon on the system behavior are investigated.     

Determinants of ground transport modal choice in long-distance trips in Spain

In transport economics, modeling modal choice is a fundamental key for policy makers trying to improve the sustainability of transportation systems. However, existing empirical literature has focused on short-distance travel within urban systems. This paper contributes to the limited number of investigations on mode choice in medium- and long-distance travel. The main objective of this research is to study the impacts of socio-demographic and economic variables, land-use features and trip attributes on long-distance travel mode choice. Using data from 2007 Spanish National Mobility Survey we apply a multilevel multinomial logit model that accounts for the potential problem of spatial heterogeneity in order to explain long-distance travel mode choice. This approach permits us to compute how the probability of choosing among private car, bus and train varies depending on the traveler spatial location at regional level. Results indicate that travelers characteristics, trip features, cost of usage of transport modes and geographical variables have significant impacts on long-distance mode choice.     

The Role of Tradable Credit Schemes in Road Traffic Congestion Management

Abstract

Road traffic congestion is not yet reflected in current market prices within the sector and has given rise to a number of instruments to mitigate the resulting negative impacts. The focus of this paper is the tradable credit scheme — an incentive-based economic measure — in order to address traffic congestion. The research questions are (1) whether the state-of-the-art in the literature suggests that tradable credit schemes could be feasibly introduced to mitigate congestion, and (2) whether a tradable credit scheme could have advantages over other instruments. A brief outline of congestion mitigation approaches is provided first to position this type of economic instrument with respect to other measures. The broad issues in the design of a tradable credit scheme are then presented. Most research to date has focused on the use of tradable credits to manage related pollution, but it is clear there is potential to design a scheme for traffic congestion management. To date this is a novel review of tradable credit schemes that has focused specifically on their role in road traffic congestion management.     

Trial and error method for optimal tradable credit schemes: The network case

Recent studies on the new congestion reduction method―tradable credit scheme rely on the full information of speed‐flow relationship, demand function, and generalized cost. As analytical travel demand, functions are difficult to establish in practice. This paper develops a trial and error method for selecting optimal credit schemes for general networks in the absence of demand functions. After each trial of tradable credit scheme, the credit charging scheme and total amount of credits to be distributed are updated by both observed link flows at traffic equilibrium and revealed credit price at market equilibrium. The updating strategy is based on the method of successive averages and its convergence is established theoretically. Our numerical experiments demonstrate that the method of successive averages based trial and error method for tradable credit schemes has a lower convergence speed in comparison with its counterpart for congestion pricing and could be enhanced by exploring more efficient methods that make full use of credit price information. Copyright © 2013 John Wiley & Sons, Ltd.     

Line haul interstation spacing for low cost feeder modes

The choice behaviour of low cost travel (LCT) modes is very sensitive to travel distance. A line haul system designed on the basis of current planning practice of locating widely spaced stations to cater auto and bus feeder modes with the primary objective of gaining travel speed is hostile to non‐motorized and low cost feeder modes. With the revival of interest in promoting the use of walk'n ride and bike'n ride modes, there is a need to develop an appropriate tool to examine the effect of their specific characteristics in establishing the number and location of stations.

A generic normative behavioural hybrid model for locating the cost minimizing number and location of stations is developed for an LCT‐fed line haul system. The model considers the system with many to many two dimensional line haul demand density function in which the density varies in both x‐ and y‐directions. The feeder mode choice behaviour is incorporated in the model by integrating probability‐access/egress distance function with the objective function. Explicit functional relationships among the parameters of these feeder modes such as modal share as a function of access/egress distance with the parameters of line haul systems are developed. Dynamic programming is used to minimize the system cost. The generic model is shown to collapse into several simplified models capable of yielding approximate solutions for several well known special cases. It has been shown that location of stations is sensitive to the through load on board as well as users’ cost that defines the choice behaviour at large. Numerical examples are presented to demonstrate the applicability of the model.     

Hierarchical network-based equilibrium model and algorithm for a mixed-traffic urban transport system

Abstract

Many equilibrium models and algorithms based on homogeneous motorized traffic have been devised to model urban transport systems in developed countries, but they are inadequate when it comes to represent mixed-traffic urban transport systems, including automobiles, transit, bicycles, and pedestrians, in developing countries such as China or India. In these cases, traffic flow on a road segment is an aggregated result of travellers' combined mode/route choices and corresponding interactions. Therefore, a special assignment model and algorithm are needed for modeling these distinct behaviors. In this article, the structure of a mixed-traffic urban transport system is analyzed and then expanded and represented using a hierarchical network model based on graph theory. Based on the analysis of travelers' combined mode/route choices, generalized travel cost functions and link impedance functions for different modes are formulated, where the interferences between different modes on the same road segments are taken into account. Due to the ‘asymmetric’ nature of these functions, a variational inequality model is proposed to represent the equilibrium assignment problem in a mixed-traffic urban transport system. The corresponding solution algorithm is also presented. Finally, a numerical example is provided to illustrate the practicality of the proposed model and algorithm.     

Influences on commuter trip departure time decisions in Singapore

This paper provides empirical evidence to support the widely held view that institutional factors such as official work start times and staggered working hours are powerful policy tools in traffic management and in influencing travel behaviour. This approach is to be preferred over continued investment in infrastructure given the scarcity of land in Singapore. A more efficient use of existing infrastructure could be achieved by spreading peak travel. Full utilisation of the Mass Rapid Transit will depend on changing the commuter's perception on multi mode travel in addition to using public transport. While many studies have been carried out on modal choice, research on commuter trip departure decisions have been few and remain largely least understood. This paper employs multinomial logit and simultaneous nested logit analysis to model the choice of departure time (using household data collected in Singapore in 1983). Preliminary findings show that schedule delay, travel cost, and journey time to be important influences on commuter's choice of trip departure time to work. Some difficulties are highlighted and suggestions for further research are made.     

Attitudinal models of modal choice: The multinomial case for selected nonwork trips

Attitudinal multinomial logit models of modal choice are presented for four nonwork activities: major grocery shopping, shopping for odds and ends, shopping for personal goods and visiting friends and acquaintances. Explanatory variables are individuals' beliefs about attributes of four modal alternatives: bus, car, taxi and walking. Factor analysis is employed to identify latent dimensions of perception of the modal alternatives and to eliminate problems of multicollinearities in model estimation. Models are estimated using data obtained for a sample of residents of Buffalo, New York. Planning implications of the methodology are assessed.This author is presently Systems Planner with Applied Resource Integration, Ltd., Boston, Massachusetts.     

Integrating congestion pricing,transit subsidies and mode choice

We model and analyze optimal (welfare maximizing) prices and design of transport services in a bimodal context. Car congestion and transit design are simultaneously introduced and consumers choose based on the full price they perceive. The optimization variables are the congestion toll, the transit fare (and hence the level of subsidies) and transit frequency. We obtain six main results: (i) the optimal car-transit split is generally different from the total cost minimizing one; (ii) optimal congestion and transit price are interdependent and have an optimal frequency attached; (iii) the optimal money price difference together with the optimal frequency yield the optimal modal split; (iv) if this modal split is used in traditional stand-alone formulations – where each mode is priced independently–resulting congestion tolls and transit subsidies and fares are consistent with the optimal money price difference; (v) self-financing of the transport sector is feasible; and (vi) investment in car infrastructure induces an increase in generalized cost for all public transport users.     

Modeling and optimization of multimodal urban networks with limited parking and dynamic pricing

Cruising-for-parking constraints mobility in urban networks. Car-users may have to cruise for on-street parking before reaching their destinations. The accessibility and the cost of parking significantly influence people's travel behavior (such as mode choice, or parking facility choice between on-street and garage). The cruising flow causes delays eventually to everyone, even users with destinations outside limited parking areas. It is therefore important to understand the impact of parking limitation on mobility, and to identify efficient parking policies for travel cost reduction. Most existing studies on parking fall short in reproducing the dynamic spatiotemporal features of traffic congestion in general, lack the treatment of dynamics of the cruising-for-parking phenomenon, or require detailed input data that are typically costly and difficult to collect. In this paper, we propose an aggregated and dynamic approach for modeling multimodal traffic with the treatment on parking, and utilize the approach to design dynamic parking pricing strategies. The proposed approach is based on the Macroscopic Fundamental Diagram (MFD), which can capture congestion dynamics at network-level for single-mode and bi-modal (car and bus) systems. A parsimonious parking model is integrated into the MFD-based multimodal modeling framework, where the dynamics of vehicular and passenger flows are considered with a change in the aggregated behavior (e.g. mode choice and parking facility choice) caused by cruising and congestion. Pricing strategies are developed with the objective of reducing congestion, as well as lowering the total travel cost of all users. A case study is carried out for a bi-modal city network with a congested downtown region. An elegant feedback dynamic parking pricing strategy can effectively reduce travel delay of cruising and the generic congestion. Remarkably, such strategy, which is applicable in real-time management with limited available data, is fairly as efficient as a dynamic pricing scheme obtained from system optimum conditions and a global optimization with full information about the future states of the system. Stackelberg equilibrium is also investigated in a competitive behavior between different parking facility operators. Policy indications on on-street storage capacity management and pricing are provided.     

Special issue: Importance of public transport

The transport demand in most major cities around the world can only be met with a high‐quality public transport system. The requirements on bus, rail, underground and tram systems are manifold with reliability and efficiency as the key factors. The service operating hours and the size of the network are often extended in order to serve the needs better. Further, most metropolitan areas are trying to provide more incentives for citizens to leave the car at home and use the local transit systems instead. The reasons are well known. Not only does a public transport system only make economical sense if it is well used, but most urban areas with a high car‐dependency face at least three major problems; safety, congestion, and pollution (noise and air pollution, land separation, etc.). It is generally recognised that to decrease car usage and to increase public transport usage a stick & carrot approach is needed. The London congestion‐charging scheme is an example since all revenues collected by the scheme are put into the improvement of bus and underground services.