Evaluating the demand for supergauge trucks-on-trains services in Western Europe

We investigate the potential diversion of freight traffic from road to a new rail service in Western Europe. The research aims to predict broad estimates of the traffic diverting to the rail service using a network model and algorithms which optimise the use of time and hence cost for each journey. Traffic diversion is evaluated using a multinomial logit model which allocates volume across the set of shortest paths relevant to a given journey. Results from a case study are presented.     

Routing and capacity assignment in backbone communication networks under time varying traffic conditions

This paper studies the problem of assigning capacities to links in a backbone communication network and determining the routes used by messages for all communicating node pairs in the network under time varying traffic conditions. The best routes are to be chosen from among all possible routes in the network. Tradeoffs between link costs and response time to users are achieved by specifying an upper limit on the average link queueing delay in the network. The goal is to minimize total link fixed and variable costs. The topology of the network and the end-to-end traffic requirements during the different busy-hours are assumed to be known. The problem is formulated as a mathematical programming model. An efficient solution procedure based on a Lagrangian relaxation of the problem is developed. The results of extensive computational experiments across a variety of networks are reported. These results indicate that the solution procedure is effective for a wide range of traffic loads and cost structures.     

基于离散与连续选址相结合的平面选址问题研究——以华北石油局大牛地气田污水处理厂选址为例

选址问题的研究中,大多考虑的是理论距离(例如欧式距离等);但在实际问题中,真实的公路运输距离和理论距离有较大差异,并且修建公路的成本较高.在尽量利用当前的公路交通网络同时,又能得到最优选址,在现实中具有重要意义.以华北石油局大牛地气田第一采气厂污水处理厂选址为例,分别采用重心法选址、最大值最小化选址、多目标选址等选址的方法得到污水处理厂的备选点,并结合实际距离模拟出了各个备选点的运输费用,再综合考虑当地政策和交通状况等因素,最终得到了使得运输费用最低的新的污水处理厂的位置坐标P(9.33,11.79),在该位置建立污水处理厂比之前的运输方案每年大约可节约511万元的运输费用.方法最大的优点是减小了在选址过程中理论距离与实际距离的误差,在现实中具有一定的指导意义.     

Locating Active Sensors on Traffic Networks

Sensors are used to monitor traffic in networks. For example, in transportation networks, they may be used to measure traffic volumes on given arcs and paths of the network. This paper refers to an active sensor when it reads identifications of vehicles, including their routes in the network, that the vehicles actively provide when they use the network. On the other hand, the conventional inductance loop detectors are passive sensors that mostly count vehicles at points in a network to obtain traffic volumes (e.g., vehicles per hour) on a lane or road of the network.This paper introduces a new set of network location problems that determine where to locate active sensors in order to monitor or manage particular classes of identified traffic streams. In particular, it focuses on the development of two generic locational decision models for active sensors, which seek to answer these questions: (1) “How many and where should such sensors be located to obtain sufficient information on flow volumes on specified paths?”, and (2) “Given that the traffic management planners have already located count detectors on some network arcs, how many and where should active sensors be located to get the maximum information on flow volumes on specified paths?”The problem is formulated and analyzed for three different scenarios depending on whether there are already count detectors on arcs and if so, whether all the arcs or a fraction of them have them. Location of an active sensor results in a set of linear equations in path flow variables, whose solution provide the path flows. The general problem, which is related to the set-covering problem, is shown to be NP-Hard, but special cases are devised, where an arc may carry only two routes, that are shown to be polynomially solvable. New graph theoretic models and theorems are obtained for the latter cases, including the introduction of the generalized edge-covering by nodes problem on the path intersection graph for these special cases. An exact algorithm for the special cases and an approximate one for the general case are presented.     

主路多车道无信号交叉口混合交通流的通行能力

Highway capacity is defined as maximum volume of traffic flow through the particular highway section under given traffic conditions,road conditions and so on.Highway construction and management is judged by capacity standard.The reasonable scale and time of highway construction,rational network structure and optimal management mode of highway network can be determined by analyzing the fitness between capacity and traffic volume.All over the world,highway capacity is studied to different extent in different country. Based on the gap acceptance theory,the mixed traffic flow composed of two representative vehicle types heavy and light vehicles is analyzed with probability theory.Capacity model of the minor mixed traffic flows crossing m major lanes,on which the traffic flows fix in with M3 distributed headway,on the unsignalized intersection is set up,and it is an extension of minor lane capacity theory for one vehicle-type and one major-lane traffic flow.     

An N-path user equilibrium for transportation networks

The traditional trip-based approach to transportation modeling has been employed for the past decade. The last step of the trip-based modeling approach is traffic assignment, which has been typically formulated as a user equilibrium (UE) problem. In the conventional perspective, the definition of UE traffic assignment is the condition that no road user can unilaterally change routes to reduce their travel time. An equivalent definition is that the travel times of all the used paths between any given origin–destination pair are equal and less than those of the unused paths. The underlying assumption of the UE definition is that road users have full information on the available transportation paths and can potentially use any path if the currently used path is overly congested. However, a more practical scenario is that each road user has a limited path set within which she/he can choose routes from. In this new scenario, we call the resulting user equilibrium an N-path user equilibrium (NPUE), in which each road user has only N paths to select from when making route choices in the network. We introduce a new formulation of the NPUE and derive optimality conditions based on this formulation. Different from traditional modeling framework, the constraints of the proposed model are of linear form, which makes it possible to solve the problem with conventional convex programming techniques. We also show that the traditional UE is a special case of an NPUE and prove the uniqueness of the resulting flow pattern of the NPUE. To efficiently solve this problem, we devise path-based and link-based solution algorithms. The proposed solution algorithms are empirically applied to networks of various sizes to examine the impact of constrained user path sets. Numerical results demonstrate that NPUE results can differ significantly from UE results depending on the number of paths available to road users. In addition, we observed an interesting phenomenon, where increasing the number of paths available to road users can sometimes decrease the overall system performance due to their selfish routing behaviors. This paradox demonstrates that network information should be provided with caution, as such information can do more harm than good in certain transportation systems.     

Using fuzzy integral for evaluating subjectively perceived travel costs in a traffic assignment model

A good traffic assignment model can be a powerful tool to describe the characteristics of traffic behavior in a road network. The traffic assignment results often play an important role in transportation planning, e.g., an optimal and economical network design. Many traditional traffic assignment models rely heavily on the travel cost function established by Wardrop’s principles; however, the Wardrop’s travel cost function has been proven to be weak for explaining the uncertainty and interactivity of traffic among links. This study tries to construct a traffic assignment model that is different from Wardrop’s in many aspects. First, it considers the cross-effect among the links. Second, a fuzzy travel cost function is established based on the possibility concept instead of precise calculation of traffic volumes. Third, the techniques of fuzzy measure and fuzzy integral are applied to calculate the subjectively perceived travel costs during traffic assignment. Furthermore, in order to validate our model, a detailed network with 22 nodes and 36 links is used to illustrate it. Study results show that our model explains more interactivity and uncertainty of traffic among links when compared with the traditional model of Wardrop’s.     

A network traffic flow model for motorway and urban highways

The research reported in this paper develops a network-level traffic flow model (NTFM) that is applicable for both motorways and urban roads. It forecasts the traffic flow rates, queue propagation at the junctions and travel delays through the network. NTFM uses sub-models associated with all road and junction types that comprise the highway. The flow at any one part of the network is obviously very dependent on the flows at all other parts of the network. To predict the two-way traffic flow in NTFM, an iterative simulation method is executed to generate the evolution of dependent traffic flows and queues. To demonstrate the capability of the model, it is applied to a small case study network and a local Loughborough–Nottingham highway network. The results indicate that NTFM is capable of identifying the relationship between traffic flows and capturing traffic phenomena such as queue dynamics. By introducing a reduced flow rate on links of the network, the effects of strategies used to carry out roadworks can be mimicked.     

Dynamic routing in open queueing networks: Brownian models,cut constraints and resource pooling

We present an introductory review of recent work on the control of open queueing networks. We assume that customers of different types arrive at a network and pass through the system via one of several possible routes; the set of routes available to a customer depends on its type. A route through the network is an ordered set of service stations: a customer queues for service at each station on its route and then leaves the system. The two methods of control we consider are the routing of customers through the network, and the sequencing of service at the stations, and our aim is to minimize the number of customers in the system. We concentrate especially on the insights which can be obtained from heavy traffic analysis, and in particular from Harrison's Brownian network models. Our main conclusion is that in many respects dynamic routingsimplifies the behaviour of networks, and that under good control policies it may well be possible to model the aggregate behaviour of a network quite straightforwardly.Supported by SERC grant GR/F 94194.     

Car path tracking in traffic flow networks with bounded buffers at junctions

This article deals with the modeling for an individual car path through a road network, where the dynamics is driven by a coupled system of ordinary and partial differential equations. The network is characterized by bounded buffers at junctions that allow for the interpretation of roundabouts or on-ramps while the traffic dynamics is based on first-order macroscopic equations of Lighthill-Whitham-Richards (LWR) type. Trajectories for single drivers are then influenced by the surrounding traffic and can be tracked by appropriate numerical algorithms. The computational experiments show how the modeling framework can be used as navigation device.     

An Interactive Algorithm for Vehicle Routeing for Winter — Gritting

In winter, when roads may become dangerously slippery due to frost, ice or snow, a de-icing agent (usually salt) is spread on them by a local authority for safety reasons. A gritter only needs to travel once down all those roads requiring treatment, as it can spread the salt onto both sides of the carriageway. The problem studied is how to design routes for gritters which will minimise costs. This problem is a type of Capacitated Arc Routeing Problem including consideration of multiple depot locations, limited vehicle capacities, time constraints on when roads must be gritted, roads with different priorities for gritting, the existence of one-way roads and salt-refilling locations. The objective function to be optimised depends on both the total distance travelled and the number and capacity of the gritters. A heuristic algorithm is devised with a computer program which allows user-interaction, and provides a practical tool for planning gritter routes. The model is linked to a GIS containing information on the road network for the County of Lancashire. Test results from the interactive algorithm are found to outperform another existing approach which solves the same problem.     

Topological design of wide area communication networks

This paper develops a model for designing a backbone network. It assumes the location of the backbone nodes, the traffic between the backbone nodes and the link capacities are given. It determines the links to be included in the design and the routes used by the origin destination pairs. The objective is to obtain the least cost design where the system costs consist of connection costs and queueing costs. The connection costs depend on link capacity and queueing costs are incurred by users due to the limited capacity of links. The Lagrangian relaxation embedded in a subgradient optimization procedure is used to obtain lower bounds on the optimal solution of the problem. A heuristic based on the Lagrangian relaxation is developed to generate feasible solutions.     

Maximum likelihood estimation for a road traffic network model

The use of the maximum likelihood method for parameter estimation in a probabilistic path choice model used for road traffic networks is described. The method requires observation of mean travel costs in a given network rather than the traffic flows throughout the network, and thus data collection efforts may be reduced. A test network, for which many sets of artificial data were generated, is examined so that the usefulness of the parameter estimation procedure may be assessed. It is shown that the procedure is both convenient and quick, and that accurate estimates of model parameters may be obtained.     

Optimal control of road freight flows by route choice inducement: A case from Mexico

Contrasting with much of the research in freight transportation around the impacts to transport operators, this work focuses on the Road Planner providing the infrastructure. This viewpoint, seeking minimal repair costs and other payments generally conflicts with the carriers’ view, looking for the best hauling route.On a random utility frame, the user-planner interaction is modelled on a partially tolled road network, considering two types of costs: (a) lorries’ trip cost guiding the route choice, and affected by planners’ actions, and (b) planners’ road repair costs, depending on the traffic, the vehicles’ type and the control implementation. A Monte Carlo simulation bases the stochastic assignment on the network, determining optimal subsidies that divert traffic to tolled roads. On a portion of the Mexican Paved network optimal subsidies are found, increasing the toll roads’ use and reducing traffic on the non-charged roads, generally having weaker pavements and higher maintenance costs.     

Network flow assignment as a fixed point problem

This paper deals with the user equilibrium problem (flow assignment with equal journey time by alternative routes) and system optimum (flow assignment with minimal average journey time) in a network consisting of parallel routes with a single origin-destination pair. The travel time is simulated by arbitrary smooth nondecreasing functions. We prove that the equilibrium and optimal assignment problems for such a network can be reduced to the fixed point problem expressed explicitly. A simple iterative method of finding equilibriumand optimal flow assignment is developed. The method is proved to converge geometrically; under some fairly natural conditions the method is proved to converge quadratically.     

Location on a One-Way Rectilinear Grid

This paper considers two basic location problems — the Weber problem and the minimax problem-on a regular grid of alternating one-way routes or streets. Both the facility to be located and the demand points are restricted to any point on the network. The one-way restriction is often used for efficiency in traffic flow, but complicates the distances in the system.     

Location-allocation models for traffic police patrol vehicles on an interurban network

This research investigates the traffic police routine patrol vehicle (RPV) assignment problem on an interurban road network through a series of integer linear programs. The traffic police RPV’s main task, like other emergency services, is to handle calls-for-service. Emergency services allocation models are generally based on the shortest path algorithm however, the traffic police RPV also handles other roles, namely patrolling to create a presence that acts as a deterrence, and issuing tickets to offenders. The RPVs need to be located dynamically on both hazardous sections and on roads with heavy traffic in order to increase their presence and conspicuousness, in an attempt to prevent or reduce traffic offences, road accidents and traffic congestion. Due to the importance of the traffic patrol vehicle’s location with regard to their additional roles, allocation of the RPVs adheres to an exogenous, legal, time-to-arrival constraint. We develop location-allocation models and apply them to a case study of the road network in northern Israel. The results of the four models are compared to each other and in relation to the current chosen locations. The multiple formulations provide alternatives that jointly account for road safety and policing objectives which aid decision-makers in the selection of their preferred RPV assignments. The results of the models present a location-allocation configuration per RPV per shift with full call-for-service coverage whilst maximizing police presence and conspicuousness as a proxy for road safety.     

A Queueing Framework for Routing Problems with Time-dependent Travel Times

Assigning and scheduling vehicle routes in a dynamic environment is a crucial management problem. Despite numerous publications dealing with efficient scheduling methods for vehicle routing, very few addressed the inherent stochastic and dynamic nature of travel times. In this paper, a vehicle routing problem with time-dependent travel times due to potential traffic congestion is considered. The approach developed introduces the traffic congestion component based on queueing theory. This is an innovative modelling scheme to capture the stochastic behavior of travel times as it generates an analytical expression for the expected travel times as well as for the variance of the travel times. Routing solutions that perform well in the face of the extra complications due to congestion are developed. These more realistic solutions have the potential to reduce real operating costs for a broad range of industries which daily face routing problems. A number of datasets are used to illustrate the appropriateness of the novel approach. Moreover it is shown that static (or time-independent) solutions are often infeasible within a congested traffic environment which is generally the case on European road networks. Finally, the effect of travel time variability (obtained via the queueing approach) is quantified for the different datasets.      

Reformulating the traffic equilibrium problem via a smooth gap function

This paper proposes an alternate formulation of the traffic assignment problem using route flows and the shortest Origin-Destination (OD) travel times as the decision variables. This is accomplished through defining a gap function to convert the Nonlinear Complementarity Problem (NCP) formulation to an equivalent Mathematical Program (MP). This formulation has two advantages:

• 1.(i) it can model assignment problems with general route costs which cannot be accomplished with existing formulations that use link-flow variables
• 2.(ii) the objective function is smooth, convex, and bounded, which permits efficient MP algorithms for its solution.

Two solution approaches are developed to solve the proposed formulation. The first is based on a set of working routes, which are modeled as “known a priori” based on travelers' preferences or interviews. The second approach uses a column generation procedure to generate a new route in each iteration on a need basis. For each approach, we use a Successive Quadratic Programming (SQP) algorithm to solve for the solutions.To show that the formulation is correct, we solve a small example with a general route cost and compare it to the classic traffic equilibrium problem which assumes an additive route cost function. Finally, numerical results for a medium-sized network are provided to demonstrate the feasibility of the solution approach.     

An efficient algorithm for computing traffic equilibria using TRANSYT model

Computing traffic equilibria with signal settings using TRANSYT model for an area traffic control road system is considered in this paper. Following Wardrop’s first principle, this problem can be formulated as a variational inequality problem. In this paper, we propose a novel algorithm to efficiently solve this equilibrium traffic assignment with global convergence. Numerical calculations are conducted on a grid-size road network. As it shows, the proposed method achieved greater savings in computational overheads than did those conventional methods for solving traffic equilibria when signal settings are particularly taken into account.