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Traffic control through video/image processing is a trending research topic within Intelligent Transportation Systems. The number of moving vehicles, the density of vehicles at the junctions, traffic anomalies, and traffic flow directly influence real-time traffic congestion. The primary goal of this work is to design an architecture that is simple and fast enough to use in real-time heterogeneous traffic scenes. The proposed methodology uses user-defined zones for determining vehicle occupancy and count based on traffic surveillance video. The angular integral projection function accompanies the background subtraction method for better localization. Traffic anomaly detection is implemented by incorporating intelligent sensor technology. Also, the skipping of frames at fixed intervals has increased the processing speed with minimal data loss. The compatibility with any Internet Protocol camera further distinguishes this approach from other state-of-the-art methods. The proposed algorithm has been tested on a publicly available traffic surveillance video dataset and real-time surveillance feeds. Experimental results from the real-time intersection scenes show an overall accuracy of 97.14% and an average processing speed of 92.91%. The accuracy of the detection module in the custom-made dataset is 98.73%. [ABSTRACT FROM AUTHOR]

The findings of this article expounds a multi-server priority queueing model by taking into account the preemptive resume priority scheduling and threshold based phase-type distribution ( P H D ) for retrial process. On the basis of priority, the incoming heterogeneous traffic is categorized as high priority traffic ( H P T ) and low priority traffic ( L P T ). When all the channels are busy, an arriving L P T will be denied for the service, and it will enter the orbit (virtual space) to retry after some time. The retrial process will follow P H D when the number of L P T is less than some threshold value otherwise the retrial process will follow exponential distribution. One of the following two instances may occur when all of the channels are occupied and a H P T enters the system. In the first instance, the arriving H P T will be discarded from the system if all the channels are packed with H P T solely. On the contrary, in the second instance, the approaching H P T will be provided service by employing preemptive priority when at least one L P T is receiving service, and that preempted L P T will enter a buffer of finite capacity. Whenever an idle channel is found, the preempted L P T will begin its service from the termination phase. The level dependent quasi-birth-death process is used for the modeling and analysis of the proposed framework. By establishing that the proposed Markov chain satisfies the asymptotically quasi-Toeplitz Markov chain classification, the ergodicity conditions for the chain are demonstrated. For the numerical illustration, the expressions of several performance measures have been developed. The non-dominated sorting genetic algorithm-II approach has been used to address an optimization problem for resource optimization and traffic control. [ABSTRACT FROM AUTHOR]

The construction and operation of linear infrastructure has major impacts on biodiversity through loss of habitat, increased mortality and loss of connectivity. In particular, minimising the impact of roads which pass through ecologically sensitive areas on surrounding species at the construction and operational phases is critical for conservation. However, potential impacts are rarely known perfectly at the construction phase and early in the operational phase. To address this problem, a company could build flexibility into road operation so that it can respond rapidly to future ecological impacts if necessary. In this paper we analyse the value of this flexibility using stochastic dynamic programming and use the results to guide a global search algorithm to find high value roads in the region. We consider flexibility in terms of the proportion of traffic volume routed along the road, with the remainder passing along an existing higher-cost, lower-impact road. We applied this to an example scenario where a road must be routed through a region with a vulnerable species present. By incorporating flexibility, the proposed model was able to find a road that met a desired ending population of animals and was more valuable than roads found under existing design alternatives. [ABSTRACT FROM AUTHOR]

In this paper we address unbalanced spatial distribution of hub-level flows in an optimal hub-and-spoke network structure of median-type models. Our study is based on a rather general variant of the multiple allocation hub location problems with fixed setup costs for hub nodes and hub edges in both capacitated and uncapacitated variants wherein the number of hub nodes traversed along origin-destination pairs is not constrained to one or two as in the classical models.. From the perspective of an infrastructure owner, we want to make sure that there exists a choice of design for the hub-level sub-network (hubs and hub edges) that considers both objectives of minimizing cost of transportation and balancing spatial distribution of flow across the hub-level network. We propose a bi-objective (transportation cost and hub-level flow variance) mixed integer non-linear programming formulation and handle the bi-objective model via a compromise programming framework. We exploit the structure of the problem and propose a second-order conic reformulation of the model along with a very efficient matheuristics algorithm for larger size instances. [ABSTRACT FROM AUTHOR]

Population growth and the massive production of automotive vehicles have lead to the increase of traffic congestion problems. Traffic congestion today is not limited to large metropolitan areas, but is observed even in medium-sized cities and highways. Traffic engineering can contribute to lessen these problems. One possibility, explored in this paper, is to assign tolls to streets and roads, with the objective of inducing drivers to take alternative routes, and thus better distribute traffic across the road network. This assignment problem is often referred to as the tollbooth problem and it is NP-hard. In this paper, we propose mathematical formulations for two versions of the tollbooth problem that use piecewise-linear functions to approximate congestion cost. We also apply a biased random-key genetic algorithm on a set of real-world instances, analyzing solutions when computing shortest paths according to two different weight functions. Experimental results show that the proposed piecewise-linear functions approximate the original convex function quite well and that the biased random-key genetic algorithm produces high-quality solutions. [ABSTRACT FROM AUTHOR]

This paper introduces a new centrality measure, nominated by the authors as mobility centrality ( C), which arose during the study of the interregional road network in Greece. The proposed measure is constructed by the use of the anagogic method considering the formula of the kinetic energy of a particle in Physics and adjusting its mathematical analogue to the case of the interregional road network. The new centrality measure is estimated to be useful for the operational analysis of a network (such as the analysis of network flows), since it characterizes as central these vertices that appear to have the greatest tendency to attract or expel network flows. The ability of the proposed centrality measure to illustrate flow tendencies was examined empirically by correlating and regressing mobility centrality to the commuting status of the Greek interregional network and to four of the most common existing centrality measures (betweenness, closeness, straightness and degree centrality) of the available data. The empirical analysis indicated that the proposed centrality measure ( C) presents sufficient ability to describe the status of the Greek interregional commuting system and it is believed that it is able to describe the inner potential that produces flows in a network. [ABSTRACT FROM AUTHOR]

This paper addresses the highway pavement rehabilitation scheduling and toll pricing issues over a planning horizon. In the highway system concerned, two types of agents are considered, namely highway operator and road users. Two models, which account for different highway regulatory regimes (i.e. public and private), are proposed. In the public regulatory model, the government aims to maximize total discounted social welfare of the transportation system over the planning horizon by determining the optimal pavement rehabilitation schedule and toll level. In the private regulatory regime, a profit-driven private operator seeks to optimize the pavement rehabilitation schedule and toll level to maximize its own discounted net profit over the planning horizon. The proposed models treat the interactions between the highway operator and the road users in the system as a bi-level hierarchical problem in which the upper level is a multi-period pavement rehabilitation scheduling and toll pricing problem, while the lower level is a multi-period route choice equilibrium problem. A heuristic solution algorithm that combines a greedy approach and a sensitivity analysis based approach is developed to solve the proposed bi-level multi-period optimization models. An illustrative example is used to show the applications of the proposed models. The findings show that the highway regulatory regime, pavement deterioration parameter and the roughness-induced vehicle operating cost can significantly affect the pavement rehabilitation schedules and the toll level as well as the performance of transportation system in terms of total life-cycle travel demand, net profit and social welfare. [ABSTRACT FROM AUTHOR]

Evacuations are massive operations that create heavy travel demand on road networks some of which are experiencing major congestions even with regular traffic demand. Congestion in traffic networks during evacuations, can be eased either by supply or demand management actions. This study focuses on modeling demand management strategies of optimal departure time, optimal destination choice and optimal zone evacuation scheduling (also known as staggered evacuation) under a given fixed evacuation time assumption. The analytical models are developed for a system optimal dynamic traffic assignment problem, so that their characteristics can be studied to produce insights to be used for large-scale solution algorithms. While the first two strategies were represented in a linear programming (LP) model, evacuation zone scheduling problem inevitable included integers and resulted in a mixed integer LP (MILP) one. The dual of the LP produced an optimal assignment principle, and the nature of the MILP formulations revealed clues about more efficient heuristics. The discussed properties of the models are also supported via numerical results from a hypothetical network example. [ABSTRACT FROM AUTHOR]

Throughout the last decade, extensive deployment of popular intra-domain routing protocols such as open shortest path first (OSPF) and intermediate system-intermediate system (IS-IS), has drawn an ever increasing attention to internet traffic engineering. This paper reviews optimization techniques that have been deployed for managing intra-domain routing in networks operated with shortest path routing protocols, and the state-of-the-art research that has been carried out in this direction. [ABSTRACT FROM AUTHOR]

In this paper we address the Sensor Location Problem, that is the location of the minimum number of counting sensors, on the nodes of a network, in order to determine the arc flow volume of all the network. Despite the relevance of the problem from a practical point of view, there are very few contributions in the literature and no combinatorial analysis is performed to take into account particular structure of the network. We prove the problem is $$\cal N \cal P$$ -complete in different cases. We analyze special classes of graphs that are particularly interesting from an application point of view, for which we give low order polynomial solution algorithms. [ABSTRACT FROM AUTHOR]

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 anactivesensor 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 arepassivesensors that mostlycountvehicles 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 thegeneralized edge-covering by nodesproblem on thepath intersection graphfor these special cases. An exact algorithm for the special cases and an approximate one for the general case are presented. [ABSTRACT FROM AUTHOR]

Radio traffic congestion occurs in a radio network when too many users simultaneously transmit on the same channel within close geographical proximity. Such congestion can be prevented by imposing channel loading constraints, which restrict the number of users that can operate using the same channel at one instance in time. Channel loading constraints are a variety of non-binary constraint that can be represented as subsets of transmitters which cannot operate on the same channel. This makes the computational cost in generating and storing them significant. In this paper we present an efficient technique for making an assignment when channel loading constraints are imposed. The method is suitable for implementation on large problem instances. We also propose a technique for finding a lower bound on the minimum span of channels required. The methods we introduce are well suited to the channel loading problem as they eliminate the need for explicit generation of the constraints involved. [ABSTRACT FROM AUTHOR]

The Ant System is a distributed metaheuristic that combines an adaptive memory with a local heuristic function to repeatedly construct solutions of hard combinatorial optimization problems. In this paper, we present an improved ant system algorithm for the Vehicle Routing Problem with one central depot and identical vehicles. Computational results on fourteen benchmark problems from the literature are reported and a comparison with five other metaheuristic approaches for solving Vehicle Routing Problems is given. [ABSTRACT FROM AUTHOR]

Network equilibrium models have recently been enhanced by explicitly incorporating link capacity constraints, resulting in queueing network equilibrium traffic patterns. Unfortunately, queueing delays at equilibrium are not unique, and thus models suffer deficiencies that limit their applications in network traffic control and management. This article proposes an entropymaximizing method to determine the most likely equilibrium traffic queueing pattern in a capacity constrained network. Queue-weighting factors or queueing probabilities are estimated based on the location of the saturated links in the network, and incorporated into an entropymaximizing model of the queueing distribution. The proposed method would significantly enhance the application of the current queueing network equilibrium models in the design and operation of congested traffic systems. [ABSTRACT FROM AUTHOR]

Research on how to model the dynamic behaviour of traffic flows efficiently and the development of algorithms to handle such models numerically has become a key activity in recent years as a consequence of the emerging applications of advanced technologies to transport. This paper offers a critical review of some of the most relevant formulations of the dynamic assignment problem and algorithms arising from both discrete and continuous models, emphasizing the underlying modelling hypothesis. Comments are made on the crucial underlying discussion on the basic implicit or explicit hypothesis and extensions to Wardrop's principle and the corresponding equilibrium concept. Properties and shortcomings are described and commented on and in some cases illustrated with simple examples. The paper ends with a description of a recent continuous modelling proposal that seems to overcome one of the reported major shortcomings: the FIFO discipline observance of traffic flows. A set of concluding remarks and a comprehensive bibliography close the paper. [ABSTRACT FROM AUTHOR]

An analytical model for the determination of the number and locations of time points as well as the amount of slack times in transit schedule design is developed. The model considers a bus route with a special passenger demand pattern in which all boarding passengers coordinate their arrivals at each stop in such a way that they never miss their intended bus, and therefore designing the schedule separately, a single run at a time, becomes possible. The model employs the dynamic programming method to deal with the trade-offs among various cost components associated with the schedule quantitatively, and yet is flexible enough to incorporate the existing rules of thumb as well as transit operators' policies. Numerical examples that illustrate the applications of the model are given. The model, although not quite applicable to bus routes with general passenger demand patterns, is useful in the analysis of the contributing factors to the design of an economical, reliable, and operational transit schedule, and is likely to be adaptable for more realistic cases. [ABSTRACT FROM AUTHOR]

This paper formulates two dynamic network traffic assignment models in which O-D desires for the planning horizon are assumed known a priori: the system optimal (SO) and the user equilibrium (UE) time-dependent traffic assignment formulations. Solution algorithms developed and implemented for these models incorporate a traffic simulation model within an overall iterative search framework. Experiments conducted on a test network provide the basis for a comparative analysis of system performance under the SO and UE models. [ABSTRACT FROM AUTHOR]

The problem of locating flow-intercepting facilities on a network with probabilistic customer flows and with facility set-up costs is studied in this paper. Two types of models are investigated, namely the double-counting model and the no-double-counting model (double-counting refers to multiple interceptions of the same customer). For each model, a nonlinear integer programming formulation is first obtained via the theory of Markov chains, and an equivalent linear integer program is then derived. A simple greedy heuristic is proposed for solving both models and a worst-case bound is established, which is shown to be tight under certain conditions. [ABSTRACT FROM AUTHOR]

We consider an example to show that the minimum instantaneous cost path principle, as suggested in Friesz et al. [1] for generalising Wardrop's first principle to the dynamic state, may cause some drivers' routes to ‘loop’. These looping routes traverse the same link more than once - indeed, in our example six times. [ABSTRACT FROM AUTHOR]

A basic issue in the planning of urban public transport is the determination of headways or inter-dispatch times. During each season, i.e. distinct time-period whose demand characteristics are constant, the following tradeoff must be considered. Dispatching too many vehicles on a route causes high operating costs, while too few vehicles may result in unsatisfactory levels of service. An appropriate policy on headways will help to balance resources between lines (routes) in peak-demand hours and will influence the total number of buses acquired by a transit company. Previous practice in industry usually bases the planning of headways upon satisfying service criteria on a ‘most-congested segment’. This approach reduces the problem from that of studying a route to that of a single segment (stop), but thereby fails to account for other important information about the line's characteristics. In this article, we develop two new service criteria which consider the line as a whole: (1) ‘crowding-overdistance’ takes into account discomfort resulting from a vehicle carrying too many passengers, and the corresponding distance travelled; and (2) ‘probability-of-failure’, the frequency with which a waiting passenger fails to board due to lack of space. COD will be analyzed using simulation. POF will be related to a time-dependent Markov chain that is ‘inhomogeneous’ in terms of distance along the route. Optimal headways are those which dispatch the smallest number of buses while meeting the particular service criterion. Models based on each of the two criteria are illustrated and applied to a number of routes of the Israeli transit company, DAN. [ABSTRACT FROM AUTHOR]

Suppose that a road network model is given, together with some given demand for travel by (say) car and that the demand for travel varies with time of day but not from day to day. Suppose that this demand is given in the form of specified total outflow rates from each origin headed towards each destination, for each origin-destination pair and for each time of day. and that some initial time-dependent route-inflow rates, meeting the given demand, are given. Finally, suppose that within-day time is represented by a continuous variable. This paper specifies a natural smooth day-to-day route-swapping procedure wherein drivers swap toward less expensive routes as day succeeds day, and shows that under reasonable conditions there is an equilibrium state of this dynamical system. If such a collection of route-inflows has arisen today, say, then there is no incentive for any route-inflow to change tomorrow, in the sense that at each moment of today each of today's route-inflows is already on a route which today yielded the smallest travel cost. Such a set of ‘no-incentive-to-change’ route-inflows is called a dynamic equilibrium, or a dynamic user-equilibrium, and may be regarded as a solution of the dynamic equilibrium traffic assignment problem. Thus, the paper introduces a smooth day-to-day dynamic assignment model and, using this model, shows that there is a dynamic user-equilibrium in a continuous time setting. The paper briefly considers the day-to-day stability of the route-swapping process, also in a continuous setting. Finally, the paper gives a simple dynamical example illustrating the stability of the route-swapping process in a simple two-route network when there is deterministic queueing at bottlenecks. [ABSTRACT FROM AUTHOR]