Adding a new station and a road link to a road–rail network in the presence of modal competition

In this paper we study the problem of locating a new station on an existing rail corridor and a new junction on an existing road network, and connecting them with a new road segment under a budget constraint. We consider three objective functions and the corresponding optimization problems, which are modeled by means of mixed integer non-linear programs. For small instances, the models can be solved directly by a standard solver. For large instances, an enumerative algorithm based on a discretization of the problem is proposed. Computational experiments show that the latter approach yields high quality solutions within short computing times.     

Highway pricing and capacity choice in a road network under a build–operate–transfer scheme

It is often argued lately that the private sector should be allowed to build and operate roads in a transportation network at its own expense, in return it should receive the revenue from road toll charge within some years, and then these roads will be transferred to the government. This type of build–operate–transfer (B–O–T) projects is currently fashionable worldwide, especially for developing countries short of funds for road construction. One of the important issues concerning a highway B–O–T project is the selection of the capacity and toll charge of the new road and the evaluation of the relevant benefits to the private investor, the road users and the whole society under various market conditions. This paper deals with the selection and evaluation of a highway project under such a B–O–T scheme. For a given road network with elastic demand, mathematical models are proposed to investigate the feasibility of a candidate project and ascertain the optimal capacity and level of toll charge of the new highway. The response of road users to the new B–O–T project is explicitly considered. The characteristic of the problem is illustrated graphically with a numerical example.     

An intersection control strategy for a short‐headway P.R.T. network

Much PRT development and research is currently being undertaken assuming quasi‐synchronous longitudinal control of guideway vehicles. This method of control has the characteristic that intersection performance has a substantial influence on the efficiency of trip demand processing. An algorithm for the control of a PRT intersection is discussed here, which would appear to have significant advantages over all other known existing stratagems. The stratagem is not only efficient but its flexibility facilitates tailoring to diverse local conditions; furthermore, the algorithm does not require intractable computations or excessive computer memory requirements. The algorithm is described and simulation results are presented. A comparative study is also made between this algorithm and its fore‐runner.     

A generalized sensor location model for the estimation of network origin–destination matrices

This study examined the network sensor location problem by using heterogeneous sensor information to estimate link-based network origin–destination (O–D) demands. The proposed generalized sensor location model enables different sensors’ traffic monitoring capabilities to be used efficiently and the optimal number and deployment locations of both passive- and active-type sensors to be determined simultaneously without path enumeration. The proposed sensor location model was applied to solve the network O–D demand estimation problem. One unique aspect of the proposed model and solution algorithms is that they provide satisfactory network O–D demand estimates without requiring unreasonable assumptions of known prior information on O–D demands, turning proportions, or route choice probabilities. Therefore, the proposed model and solution algorithms can be practically used in numerous offline transportation planning and online traffic operation applications.     

Competitiveness of container terminal operating companies in South Korea and the industry–university–government network

Burgeoning container port facilities have fostered intensified competition among container terminal operating companies (CTOCs). However, despite research into their survival strategies which identified antecedents of competitiveness including hard factors such as facilities, available cargo and cargo processing ability, softer factors spanning human resource management, networks and strategic alliances with universities and government agencies in industry–university–government (I–U–G) networks have been overlooked. This study aims to examine both hard and softer antecedents of competitiveness as perceived by 152 professionals in South Korean CTOCs; empirical relationships among these antecedents, I–U–G networks, and competitiveness itself; and the significance of the I–U–G network in establishing and improving competitiveness. Posited antecedents of competitiveness included human resources, facilities, service quality, customer orientation, reputation, and government support policy as independent variables; the I–U–G network as a moderating variable; and competitiveness as a dependent variable. Empirical structural relationships revealed that excepting government support policy, each variable significantly affected CTOC competitiveness. Further, the I–U–G network moderated the relationships between the antecedents of competitiveness and competitiveness. Because an effective I–U–G network was pivotal in controlling CTOC competitiveness, improved competitiveness requires not only differentiation of human resources, facilities, service quality, customer orientation, and reputation factors but also I–U–G network developments.     

Implementing first-in–first-out in the cell transmission model for networks

In traffic assignment models with time-varying flows (dynamic network loading or dynamic traffic assignment), overtaking behaviour is normally not included in the model and, in that case, it is important that the model at least approximates first-in–first-out (FIFO), to prevent deviations from FIFO that are arbitrary or unrealistic or not physically possible. For the cell transmission model (CTM) it has recently been shown that the usual recommended method for preserving FIFO will ensure FIFO for each cell taken separately but does not fully ensure FIFO in the transition between cells and hence does not fully ensure FIFO for sequences of cells or for links or for routes. As a result, deviations from FIFO can easily occur and cumulate along the links or routes. In view of that, we define and analyse three different levels of satisfaction or approximation of FIFO, together with corresponding methods for achieving them. Two of these are existing methods and one is new. We develop, analyse and compare the three methods and the extent to which each of them adheres to FIFO for sequences of cells and links or routes. Also, for two of the methods we present a more detailed algorithm for applying them within the CTM. The paper is concerned with how to implement FIFO in the CTM and not with testing for FIFO or measuring deviations from FIFO.     

A network‐based model for estimating the market share of a new high‐speed rail system

This paper presents a novel application of static traffic assignment methods, but with a variable time value, for estimating the market share of high‐speed rail (HSR) in the northwest–southeast (NW–SE) corridor of Korea currently served by air, conventional rail and highway modes. The proposed model employs a time–space network structure to capture the interrelations among competing transportation modes, and to reflect their supply‐ and demand‐side constraints as well as interactions through properly formulated link‐node structures. The embedded cost function for each network link offers the flexibility for incorporating all associated factors, such as travel time and fare, in the model computation, and enables the use of a distribution rather than a constant to represent the time–value variation among all transportation mode users. To capture the value‐of‐time (VOT) of tripmakers along the target corridor realistically, this study has developed a calibration method with aggregate demand information and key system performance data from the NW–SE corridor.     

What drives the gap? Applying the Blinder–Oaxaca decomposition method to examine generational differences in transportation-related attitudes

Transportation - Considerable recent work suggests that Millennials’ behaviors may be converging with those of Generation X as they enter later life stages, but few have investigated whether...     

Determining the number and location of winter road maintenance depots – a case study of the district road network in Serbia

Determining the number and location of depots for winter road maintenance (WRM) represents one of the important strategic decisions while planning WRM activities. However, most organizations dealing with WRM make empirically based decisions. Optimizing the number and location of WRM depots has the potential to achieve considerable cost savings, improve mobility and efficiency, as well as reduce environmental impacts. This paper presents two optimization models. The first model determines the location of WRM depots by minimizing the total distance travelled by maintenance vehicles. The second model determines the optimum number and location of WRM depots by minimizing total transportation costs and capital expenditure and operational expenditure of the depots. The models are then applied to the district road network in Serbia. Results show that their application could lead to significant reductions in WRM costs.     

Repetitions in individual daily activity–travel–location patterns: a study using the Herfindahl–Hirschman Index

Using Herfindahl–Hirschman Index and the Mobidrive and Thurgau six-week travel diary datasets this paper examines the degree of repetition of individuals’ choices of their daily activity–travel–location combinations. The results show that the repetitiveness of individual activity–travel–mode–location combinations is highly influenced by the individuals’ out-of-home commitments, the intra-household conditions and the availability and the accessibility of the activity locations. Different types of activity have different pattern of repetition. The level of repetition of individual’s daily activity–travel pattern is less correlated to travel mode choice, but more to the individuals’ commitments and obligations. The repetitiveness of mode choices is more related to the conditions or the accessibilities of the activity location, but not directly to the activity itself.     

Changes concerning commute traffic distribution on a road network following the occurrence of a natural disaster – The example of a flood in the Mazovian Voivodeship (Eastern Poland)

The purpose of this article is to determine the size and spatial structure of changes in traffic density within the regional road network following an occurrence of a flood in the Mazovian Voivodeship, Poland. The use of the application developed for the purpose of this article – offers a possibility to react accordingly when there are non-typical obstructions (here: a flood). On the basis of the conducted study, it has been stated that the greatest changes in vehicle traffic density (the analysis of commute traffic) regard the capital of Mazovian Voivodeship, which – first of all – stems from the fact that it is Warsaw that the largest number of employees commute to. Secondly, it is influenced by the location of the capital city in relation to the river system. In the case of the analysed voivodeship and in ‘normal’ circumstances (no flood), commuting to work remains approximately within the 160-min isochrone. In the second variant, this time would extend nearly eightfold, and in the remaining scenarios fivefold. As far as ‘normal’ circumstances (no flood) and commuting in the Mazovian Voivodeship are concerned, the greatest load refers in particular to the following road classes: main road of accelerated traffic, main road and cumulative road. In this case, express and motorways play a marginal role. On the other hand, in the remaining scenarios, the importance of the class of main road of accelerated traffic decreases at the expense of the classes of main road and cumulative road.     

A ‘Less-flexibility-first’ Heuristic for the Placement of Inland Vessels in a Lock

Abstract

Inland vessels move goods along waterways (canals and rivers) and they visit ports. Because of their tidal nature, vessels make use of locks to enter ports or waterways. From a port management point of view, fast access to and from the port and high utilization of locks are important objectives. Where the former relates to low inbound and outbound waiting times, the latter relates to the placement of as many vessels as possible in the lock before its operation. This article includes a case study that relates to the operation of the Van Cauwelaert lock in the port of Antwerp, Belgium. Lock operation policy is as follows: vessels wait in front of the lock for a port administrator to assign places in the lock based on knowledge of the vessels’ dimensions. As such, there is no FIFO-discipline, but a ‘group-FIFO’-discipline, i.e. if n vessels are allowed into the lock, they are the first n vessels in the arrival queue. A heuristic algorithm is formulated for the placement of vessels in the lock. This algorithm supports the decision where to place the vessel in the lock, aiming to place as many vessels as possible from the arrival queue. At the same time, it supports the decision to start a locking operation or not, based on information about vessels that are announced but which have not yet arrived at the lock's entrance. The heuristic is called a ‘less-flexibility-first’-heuristic as it looks for pseudo-placements, showing which flexibility is left for the remaining vessels after placing a vessel. This article describes the implementation of the heuristic and provides numerical examples. A comparison is made between the heuristic results and daily practice, based on real-life vessel movements through the Van Cauwelaert lock in 2002.     

On allowing a general form for unobserved heterogeneity in the multiple discrete–continuous probit model: Formulation and application to tourism travel

This paper proposes a new econometric formulation and an associated estimation method for a finite discrete mixture of normals (FDMN) version of the multiple discrete–continuous probit (MDCP) model. To our knowledge, this is the first such formulation and application of an MDCP model in the econometric literature. Using the New Zealand Domestic Travel Survey data set, the model is applied to analyze individual-level decisions regarding recreational destination locations and the number of trips to each destination. The results provide insights into the demographic and other factors that influence individuals’ preferences for different destinations, and show that the FDMN MDCP model is able to identify different segments of the sample, each one of them with different effects of the exogenous variables on destination choice.     

Towards a microeconomic framework for modelling the joint choice of activity–travel behaviour and ICT use

The rapid development of information and communication technologies (ICT) has been argued to affect time use patterns in a variety of ways, with consequent impacts on travel behaviour. While there exists a significant body of empirical studies documenting these effects, theoretical developments have lagged this empirical work and in particular, microeconomic time allocation models have not to date been fully extended to accommodate the implications of an increasingly digitised society. To address this gap, we present a modelling framework, grounded in time allocation theories and the goods–leisure framework, for joint modelling of the choice of mode of activity (physical versus tele-activity), travel mode and route, and ICT bundle. By providing the expression for a conditional indirect utility function, we use hypothetical scenarios to demonstrate how our framework can conceptualise various activity–travel decision situations. In our scenarios we assume a variety of situations such as the implications of severe weather, the introduction of autonomous vehicles, and the interaction between multiple decision makers. Moreover, our approach lays the microeconomic foundations for deriving subjective values of ICT qualities such as broadband speed or connection reliability. Finally, we also demonstrate the means by which our framework could be linked to various data collection protocols (stated preference exercises, diaries of social interactions, laboratory experiments) and modelling approaches (discrete choice modelling, hazard-based duration models).     

A data-driven approach for origin–destination matrix construction from cellular network signalling data: a case study of Lyon region (France)

Transportation - Spatiotemporal data, and more specifically origin–destination matrices, are critical inputs to mobility studies for transportation planning and urban management purposes....     

Construction Technology for the Dazhushan Tunnel in a High-Pressure Fault with Abundant Water北大核心CSCD

The Dazhushan tunnel of Dali-Ruili railway is located in an area with complex geological structures,dense faults, various lithologies, fractured soft rock, developed karst and an underground water pressure of up to 3 MPa. Serious mud bursts and water inflow occured during the construction of the parallel adit passing through the Yanziwo fault. The water-stopping technique of grouting reinforcement is studied in light of this high-pressure fault with abundant water; sectional water drainage for moving water and polymerized grouting with super high pressure are presented; and the key points of the grouting reinforcement scheme, construction equipment configuration, criti-cal technology parameters and construction organization are described in detail. © 2018, Editorial Office of "Modern Tunnelling Technology". All right reserved.     

The treatment of uncertainty in the dynamic origin–destination estimation problem using a fuzzy approach

Regardless of existing types of transportation and traffic model and their applications, the essential input to these models is travel demand, which is usually described using origin–destination (OD) matrices. Due to the high cost and time required for the direct development of such matrices, they are sometimes estimated indirectly from traffic measurements recorded from the transportation network. Based on an assumed demand profile, OD estimation problems can be categorized into static or dynamic groups. Dynamic OD demand provides valuable information on the within-day fluctuation of traffic, which can be employed to analyse congestion dissipation. In addition, OD estimates are essential inputs to dynamic traffic assignment (DTA) models. This study presents a fuzzy approach to dynamic OD estimation problems. The problems are approached using a two-level model in which demand is estimated in the upper level and the lower level performs DTA via traffic simulation. Using fuzzy rules and the fuzzy C-Mean clustering approach, the proposed method treats uncertainty in historical OD demand and observed link counts. The approach employs expert knowledge to model fitted link counts and to set boundaries for the optimization problem by defining functions in the fuzzification process. The same operation is performed on the simulation outputs, and the entire process enables different types of optimization algorithm to be employed. The Box-complex method is utilized as an optimization algorithm in the implementation of the approach. Empirical case studies are performed on two networks to evaluate the validity and accuracy of the approach. The study results for a synthetic network and a real network demonstrate the robust performance of the proposed method even when using low-quality historical demand data.     

Attitudes towards the role of Cost–Benefit Analysis in the decision-making process for spatial-infrastructure projects: A Dutch case study

This paper provides a systematic overview of the attitudes of key actors in the Dutch Cost–Benefit Analysis (CBA) practice towards the role of CBA in the decision-making process for spatial-infrastructure projects. The main aim of this paper is to scrutinize the extent to which there is agreement among these Dutch actors in regard to the role of the CBA in the decision-making process. A secondary goal is to provide possible explanations for agreements and controversies among key actors in the Dutch CBA practice. In this study two research methods are combined to study the key actors’ attitudes. Firstly, 86 key actors (e.g. consultants, scientists, policy makers) were interviewed in-depth. Secondly, 74 of them completed a written questionnaire. The most important conclusion of this paper is that in the Dutch CBA practice there is agreement that CBA must have a role in the appraisal process of spatial-infrastructure projects. However, there is a lot of controversy among economists and spatial planners in the Dutch CBA practice concerning the value that is and should be assigned to CBA in the decision-making process. Economists predominantly believe that not enough value is assigned to the CBA in the decision-making process, whereas spatial planners predominantly think that too much value is assigned to the CBA. Both economists and spatial planners believe that this controversy is problematic as it results in debates about the pros and cons of CBA instead of the pros and cons of the spatial-infrastructure projects. This paper analyzes some solutions for this controversy.     

Exact and grid-free solutions to the Lighthill–Whitham–Richards traffic flow model with bounded acceleration for a class of fundamental diagrams

In this article, we propose a new exact and grid-free numerical scheme for computing solutions associated with an hybrid traffic flow model based on the Lighthill–Whitham–Richards (LWR) partial differential equation, for a class of fundamental diagrams. In this hybrid flow model, the vehicles satisfy the LWR equation whenever possible, and have a constant acceleration otherwise. We first propose a mathematical definition of the solution as a minimization problem. We use this formulation to build a grid-free solution method for this model based on the minimization of component function. We then derive these component functions analytically for triangular fundamental diagrams, which are commonly used to model traffic flow. We also show that the proposed computational method can handle fixed or moving bottlenecks. A toolbox implementation of the resulting algorithm is briefly discussed, and posted at https://dl.dropbox.com/u/1318701/Toolbox.zip.     

Analysis of long-distance vacation travel demand in the United States: a multiple discrete–continuous choice framework

This study analyzes the annual vacation destination choices and related time allocation patterns of American households. More specifically, an annual vacation destination choice and time allocation model is formulated to simultaneously predict the different vacation destinations that a household visits in a year, and the time (no. of days) it allocates to each of the visited destinations. The model takes the form of a multiple discrete–continuous extreme value (MDCEV) structure. Further, a variant of the MDCEV model is proposed to reduce the prediction of unrealistically small amounts of vacation time allocation to the chosen destinations. To do so, the continuously non-linear utility functional form in the MDCEV framework is replaced with a combination of a linear and non-linear form. The empirical analysis was performed using the 1995 American Travel Survey data, with the United States divided into 210 alternative destinations. The model estimation results provide several insights into the determinants of households’ vacation destination choice and time allocation patterns. Results suggest that travel times and travel costs to the destinations, and lodging costs, leisure activity opportunities (measured by employment in the leisure industry), length of coastline, and weather conditions at the destinations influence households’ destination choices for vacations. The annual vacation destination choice model developed in this study can be incorporated into a larger national travel modeling framework for predicting the national-level, origin–destination flows for vacation travel.