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.     

Hybrid model of taxonomy and genetic algorithms for finding shortest path in transportation systems

This is research is aimed at elaborating a new methodology of shortest path finding by utilizing the methods of taxonomy and genetic algorithms. Combination of the two is developed and called Genetic Taxonomy Evaluator (GTE) which is expected to be an alternative tool to solve shortest path finding problems within the transportation networks While keeping the properties of transportation networks Taxonomy Reconstructor (TR) transforms the network representation into taxonomic structure, which is hierarchically shaped, based on problem to be solved. In the process TR also creates classification of nodes in the network. This classification provides facilities to isolate the problem to the core, and the criteria that can be inserted in the Genetic Algorithm (GA). A package program for GTE is then developed in C-Language and performance of model is analyzed upon a medium scale of Sioux-Falls City Network. In conclusion, it is found that to achieve fairly quick convergence of GTE computation several optimal parameters of GA should be determined prior to searching for the shortest paths. And since GTE has only been applied to limited case, it is suggested that the findings could be a threshold for further researches.     

Path-constrained traffic assignment: A trip chain analysis under range anxiety

This paper proposes and analyzes a distance-constrained traffic assignment problem with trip chains embedded in equilibrium network flows. The purpose of studying this problem is to develop an appropriate modeling tool for characterizing traffic flow patterns in emerging transportation networks that serve a massive adoption of plug-in electric vehicles. This need arises from the facts that electric vehicles suffer from the “range anxiety” issue caused by the unavailability or insufficiency of public electricity-charging infrastructures and the far-below-expectation battery capacity. It is suggested that if range anxiety makes any impact on travel behaviors, it more likely occurs on the trip chain level rather than the trip level, where a trip chain here is defined as a series of trips between two possible charging opportunities (Tamor et al., 2013). The focus of this paper is thus given to the development of the modeling and solution methods for the proposed traffic assignment problem. In this modeling paradigm, given that trip chains are the basic modeling unit for individual decision making, any traveler’s combined travel route and activity location choices under the distance limit results in a distance-constrained, node-sequenced shortest path problem. A cascading labeling algorithm is developed for this shortest path problem and embedded into a linear approximation framework for equilibrium network solutions. The numerical result derived from an illustrative example clearly shows the mechanism and magnitude of the distance limit and trip chain settings in reshaping network flows from the simple case characterized merely by user equilibrium.     

A dynamic route choice model for public transport networks with boarding queues

Abstract

The concepts of optimal strategy and hyperpath were born within the framework of static frequency-based public transport assignment, where it is assumed that travel times and frequencies do not change over time and no overcrowding occurs. However, the formation of queues at public transport stops can prevent passengers from boarding the first vehicle approaching and can thus lead to additional delays in their trip. Assuming that passengers know from previous experience that for certain stops/lines they will have to wait for the arrival of the 2nd, 3rd, …, k-th vehicle, they may alter their route choices, thus resulting in a different assignment of flows across the network. The aim of this paper is to investigate route choice behaviour changes as a result of the formation and dispersion of queues at stops within the framework of optimal travel strategies. A new model is developed, based on modifications of existing algorithms.     

Computing 4D near-optimal trajectories for dynamic air traffic flow management with column generation and branch-and-price

Abstract

The current air traffic system faces recurrent saturation problems. Numerous studies are dedicated to this issue, including the present research on a new dynamic regulation filter holding frequent trajectory optimisations in a real-time sliding horizon loop process. We consider a trajectory optimisation problem arising in this context, where a feasible four-dimensional (4D) trajectory is to be built and assigned to each regulated flight to suppress sector overloads while minimising the cost of the chosen policy. We model this problem with a mixed integer linear programme and solve it with a branch-and-price approach. The pricing sub-problem looks for feasible trajectories in a dynamic three-dimensional (3D) network and is solved with a specific algorithm based on shortest path labelling algorithms and on dynamic programming. Each algorithm is tested on real-world data corresponding to a complete traffic day in the European air traffic system; experimental results, including computing times measurement, validate the solution process.     

Exploring public bicycle network structure based on complex network theory and shortest path analysis: the public bicycle system in Yixing,China

A well-functioning public bicycle system relates not only to its mode of operation, vehicle allocation, rental station layout and vehicle leasing configuration, but also the bicycle network structure and its formation. However, the latter aspects have been widely overlooked in China. Here, we help to further attract more researchers to conduct relevant studies and make suggestions for the development of public bicycle transport in many small and medium-sized cities across the world. We demonstrate how to explore the public bicycle network structure of a county-level Chinese city – Yixing – known for its clay ware and tourism. We show that complex network theory and shortest path analysis technology are useful in characterizing the public bicycle network structure, in aspects such as network topology, the spatial distribution of sub-networks and traffic flows. Finally, the paper proposes relevant urban planning strategies.     

The European freight railway system as a hub-and-spoke network

This paper addresses a hub-and-spoke network problem for railroad freight, where a central planner is to find transport routes, frequency of service, length of trains to be used, and transportation volume. Hub-and-spoke networks, often found in air freight, have not been favoured by railways in the past. Such a structure could be profitable, however, if there exist concentrated freight flows on some service links. We formulate a linear integer programming model whose objective function includes not only the typical operational cost, but also cost due to the transit time spent by freight in the network. We then develop heuristic algorithms to solve large scale instances occurring in rail freight systems in France plus Italy; Germany; and a 10-country European network. By assuming that every node is equipped with consolidation capability, we let the final solution naturally reveal potential hub locations, the impact of several of which is studied by sensitivity analysis.     

Finding the most reliable path with and without link travel time correlation: A Lagrangian substitution based approach

Path travel time reliability is an essential measure of the quality of service for transportation systems and an important attribute in travelers’ route and departure time scheduling. This paper investigates a fundamental problem of finding the most reliable path under different spatial correlation assumptions, where the path travel time variability is represented by its standard deviation. To handle the non-linear and non-additive cost functions introduced by the quadratic forms of the standard deviation term, a Lagrangian substitution approach is adopted to estimate the lower bound of the most reliable path solution through solving a sequence of standard shortest path problems. A subgradient algorithm is used to iteratively improve the solution quality by reducing the optimality gap. To characterize the link travel time correlation structure associated with the end-to-end trip time reliability measure, this research develops a sampling-based method to dynamically construct a proxy objective function in terms of travel time observations from multiple days. The proposed algorithms are evaluated under a large-scale Bay Area, California network with real-world measurements.     

Distributed computing approaches for large‐scale probit‐based stochastic user equilibrium problems

Applications of probit‐based stochastic user equilibrium (SUE) principle on large‐scale networks have been largely limited because of the overwhelming computational burden in solving its stochastic network loading problem. A two‐stage Monte Carlo simulation method is recognized to have satisfactory accuracy level when solving this stochastic network loading. This paper thus works on the acceleration of the Monte Carlo simulation method via using distributed computing system. Three distributed computing approaches are then adopted on the workload partition of the Monte Carlo simulation method. Wherein, the first approach allocates each processor in the distributed computing system to solve each trial of the simulation in parallel and in turns, and the second approach assigns all the processors to solve the shortest‐path problems in one trial of the Monte Carlo simulation concurrently. The third approach is a combination of the first two, wherein both different trials of the Monte Carlo simulation as well as the shortest path problems in one trial are solved simultaneously. Performances of the three approaches are comprehensively tested by the Sioux‐Falls network and then a randomly generated network example. It shows that computational time for the probit‐based SUE problem can be largely reduced by any of these three approaches, and the first approach is found out to be superior to the other two. The first approach is then selected to calculate the probit‐based SUE problem on a large‐scale network example. Copyright © 2011 John Wiley & Sons, Ltd.     

Park-and-ride lot choice model using random utility maximization and random regret minimization

This research aims to understand the park-and-ride (PNR) lot choice behaviour of users i.e., why PNR user choose one PNR lot versus another. Multinomial logit models are developed, the first based on the random utility maximization (RUM) concept where users are assumed to choose alternatives that have maximum utility, and the second based on the random regret minimization (RRM) concept where users are assumed to make decisions such that they minimize the regret in comparison to other foregone alternatives. A PNR trip is completed in two networks, the auto network and the transit network. The travel time of users for both the auto network and the transit network are used to create variables in the model. For the auto network, travel time is obtained using information from the strategic transport network using EMME/4 software, whereas travel time for the transit network is calculated using Google’s general transit feed specification data using a backward time-dependent shortest path algorithm. The involvement of two different networks in a PNR trip causes a trade-off relation within the PNR lot choice mechanism, and it is anticipated that an RRM model that captures this compromise effect may outperform typical RUM models. We use two forms of RRM models; the classical RRM and µRRM. Our results not only confirm a decade-old understanding that the RRM model may be an alternative concept to model transport choices, but also strengthen this understanding by exploring differences between two models in terms of model fit and out-of-sample predictive abilities. Further, our work is one of the few that estimates an RRM model on revealed preference data.

     

Impact evaluation of a mass transit fare change on demand and revenue utilizing smart card data

Transit fares are an effective tool for demand management. Transit agencies can raise revenue or relieve overcrowding via fare increases, but they are always confronted with the possibility of heavy ridership losses. Therefore, the outcome of fare changes should be evaluated before implementation. In this work, a methodology was formulated based on elasticity and exhaustive transit card data, and a network approach was proposed to assess the influence of distance-based fare increases on ridership and revenue. The approach was applied to a fare change plan for Beijing Metro. The price elasticities of demand for Beijing Metro at various fare levels and trip distances were tabulated from a stated preference survey. Trip data recorded by an automatic fare collection system was used alongside the topology of the Beijing Metro system to calculate the shortest path lengths between all station pairs, the origin–destination matrix, and trip lengths. Finally, three fare increase alternatives (high, medium, and low) were evaluated in terms of their impact on ridership and revenue. The results demonstrated that smart card data have great potential with regard to fare change evaluation. According to smart card data for a large transit network, the statistical frequency of trip lengths is more highly concentrated than that of the shortest path length. Moreover, the majority of the total trips have a length of around 15 km, and these are the most sensitive to fare increases. Specific attention should be paid to this characteristic when developing fare change plans to manage demand or raise revenue.     

Development of commuter and non-commuter mode choice models for the assessment of new public transport infrastructure projects: A case study

This paper uses state of the art stated choice designs to parameterise modal choice models for commuting and non-commuting travel futures in the presence of new public transport infrastructure (variations of new heavy rail, light rail and dedicated busway systems). D-optimal choice experiments are developed for a set of labelled modal alternatives in which respondents establish a reference benchmark based on the existing service levels (for access, linehaul and egress trip legs) which is used in a computer aided personal interview instrument to generate future scenarios of service levels for current and prospective new modals options. We show that a fully integrated stated choice experiment provides all the information required to obtain behaviourally relevant parameter estimates (within a nested logit framework) for all but the mode-specific constants (MSCs). The MSCs can be calibrated for the current modes within a network model setting, giving the transport planner an appropriate model for predicting the patronage potential for proposed new public transport infrastructure services. A useful by-product is a new set of behavioural values of travel time savings for access, egress, linehaul and wait times.     

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.     

Livelihoods,daily mobility and poverty in sub-saharan Africa

Based on research funded by the UK Department for International Development, this paper investigates the utility of a livelihoods approach in identifying the mobility and accessibility needs of the poor. Mobility patterns and livelihoods of stratified samples of households in urban-to-rural corridors originating in the national capital cities of Zimbabwe and Uganda are compared, with emphasis on the poor's position relative to higher income groups. It is found that livelihood work was the most frequent purpose of short-distance travel for all income groups and localities, amounting to 38% of trip purposes in Uganda and 46% in Zimbabwe. On average, Zimbabweans were more mobile making more daily trips over longer distances reflective of greater reliance on motorized transport in the country. Nonetheless, walking dominates modal journeys in both countries. Ugandans display heavier dependence on bicycle and motorcycle transport primarily through taxi hire compared with Zimbabweans' private care and public kombi bus transport. Survey evidence suggests that Uganda's poor and middle-incomed urban and rural residents benefit from more widely available multimodal public transport.     

A mixed-integer linear program for optimizing sensor locations along freeway corridors

How to optimally allocate limited freeway sensor resources is of great interest to transportation engineers. In this paper, we focus on the optimal allocation of point sensors, such as loop detectors, to minimize performance measurement errors. Although it has been shown that the minimization problem can be intuitively formulated as a nonlinear program, the formulation is so complex that only heuristic approaches can be used to solve the problem. In this paper, we transform the nonlinear program into an equivalent mixed-integer linear model. The linearized model is shown to have a graphical interpretation and can be solved using resource constrained shortest path algorithms. A customized Branch-and-Bound technique is then proposed to solve the resource constrained shortest path problem. Numerical experiments along an urban freeway corridor demonstrate that this sensor location model is successful in allocating loop detectors to improve the accuracy of travel time estimation.     

Parametric search for the bi-attribute concave shortest path problem

A bi-attribute concave shortest path (BC-SP) problem seeks to find an optimal path in a bi-attribute network that minimizes a linear combination of two path costs, one of which is evaluated by a nondecreasing concave function. Due to the nonadditivity of its objective function, Bellman’s principle of optimality does not hold. This paper proposes a parametric search method to solve the BC-SP problem, which only needs to solve a series of shortest path problems, i.e., the parameterized subproblems (PSPs). Several techniques are developed to reduce both the number of PSPs and the computation time for these PSPs. Specifically, we first identify two properties of the BC-SP problem to guide the parametric search using the gradient and concavity of its objective function. Based on the properties, a monotonic descent search (MDS) and an intersection point search (IPS) are proposed. Second, we design a speedup label correcting (LC) algorithm, which uses optimal solutions of previously solved PSPs to reduce the number of labeling operations for subsequent PSPs. The MDS, IPS and speedup LC techniques are embedded into a branch-and-bound based interval search to guarantee optimality. The performance of the proposed method is tested on the mean-standard deviation shortest path problem and the route choice problem with a quadratic disutility function. Experiments on both real transportation networks and grid networks show that the proposed method reduces the computation time of existing algorithms by one to two orders of magnitude.     

Modelling car trip generations for UK residential developments using data from TRICS

Abstract

This paper models trip generation for a cross-section of residential developments around the UK. Consistent with recent literature, the empirical model tests whether trip making patterns for residential developments are independent of car ownership and finds that trip generation is dependent upon car ownership socio-economic factors and site-specific characteristics, in particular land-zone type (e.g. town centre, out of town, etc.). However, public transport services are not found to have a significant relationship with trip generation; consequently, a policy implication of the results is that increasing bus services to residential developments is not associated with a reduction in generated trips.     

Promoting Development through Multimodal Freight Transport in Bangladesh

Abstract

Development emanating from international trade and investment in many least‐developed economies is impeded by inland freight transport systems that restrict multimodal transport. Increasing international trade may raise gross domestic product, generating increased demand for internal containerized cargo movements, but the requisite transport infrastructure is lacking. The paper explores impediments to developing effective multimodal transport and possible solutions in Bangladesh, which is an extreme case in point. It reports applications of Delphi techniques that explored local expert opinions regarding policies required to tackle such impediments. A panel of corporate executives perceived a changing inland transport system poorly suited to efficient origin‐to‐destination cargo movements in international supply chains. To promote further development, customs procedures must be streamlined and Bangladeshi shippers must adopt a door‐to‐door transport system.     

Transport reviews prize

The transport problems that urban centres now face (as regard congestion, the environment and public deficits) have led to an examination of competition in the sector. Some countries have moved towards the deregulation or privatization of urban public transport, influenced by developments in the theory of contestable markets. These analyses could potentially provide a means of increasing the efficiency of public services and, hence, public transport. However, the authors do not feel that they can deal with the full extent of the problem. Particularly in urban areas, there is a need nowadays to examine the issue of competition between the passenger car and public transport, especially from the pricing angle. In France, decades of policy strongly influenced by a preference for the car have prevented this problem from being a central concern for researchers and decision-makers. The approach to the problem has mainly been centred on increasing urban supply to meet demand better. However, a failure to consider pricing, and the subsidization phenomena that can occur as a result, affects the shape of supply systems. Pricing, through its action on demand, acts on supply by increasing or reducing its potential profitability. 'Snowball' effects can, therefore, mean that slight underpricing results in the domination of one transport mode. These effects have been revealed in particular by work in the new field of network economics. The example of the Lyon conurbation shall be used to illustrate the case, which is that car travel is underpriced. The basis of the exposé will be a detailed analysis of the externalities associated with the car, i.e. the costs of car use and the revenue it raises for the community. The second part of the paper is a study of several urban travel policies in Europe (France, UK, Switzerland, Italy) to show the 'effects' of this underpricing. Where supply has followed the pressure of demand, the dominance of the car has been reinforced. However, in cities, particularly in Switzerland, where supply has been restricted, this dominance has been considerably moderated. On the other hand, it can be seen from the French example that taking strong action to improve public transport is not in itself sufficient to increase usage. Several lessons can be learnt from this work. First, it is shown, if it was still necessary to do so, that the problems of urban travel require a comprehensive and coherent approach. Modal policy must, therefore, be assessed with reference to the entire transport system. Next, in connection with the issue of regulation, it is important to consider the issue of competition in urban areas, and not only competition between public transport operators, but also (and even above all) competition within the entire system of personal and public transport. Finally, with regard to pricing, the ratchet effects that benefit the car as a result of its underpricing in urban areas need to be studied.     

Could you also have made this trip by another mode? An investigation of perceived travel possibilities of car and train travellers on the main travel corridors to the city of Amsterdam,The Netherlands

We investigated perceived travel possibilities (or subjective choice-sets, consideration-sets) of car and train travellers on the main corridors to the city of Amsterdam, The Netherlands, and associations with traveller and trip characteristics. We conducted secondary analysis on a survey sample consisting of 7950 train and 19,232 car travellers. Forty-five percent of train travellers had a car in their objective choice-set, 27% of them would however never use it for this trip. Trip destination city centre, trip purpose, paying for the trip, public transport commitment, traffic congestion and parking problems were associated with consideration of car as alternative. Forty-two percent of car travellers had public transport in their subjective choice-set. The ratio between perceived public transport and objective car travel time stood out as determinant of consideration-sets, next to destination city centre, trip purpose, travel time and private versus company car ownership. On average, car travellers’ perceptions of public transport travel time exceeded objective values by 46%. We estimated that if perceptions would be more accurate, two out of three car travellers that currently do not see public transport as an alternative would include it in their choice-set, and use it from time to time. This effect has strong theoretical and policy implications.