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A major performance index for analyzing a stochastic transport network is the two-terminal capacity reliability Rd, defined as the probability that d units of goods can be successfully transported via stochastic arc capacities from the source to the destination. This paper presents an efficient d-minimal path method to calculate Rd based on some newly obtained results. The proposed method uses a simple method to check d-minimal path candidates and a more efficient approach to remove duplicate d-minimal paths that are the biggest obstacle in solving d-minimal paths, along with an indication of the advantage over the existing methods. Besides, sensitivity analysis is adopted to explore the most important arc whose reliability change affects the network reliability most significantly, which helps supervisor identify and enhance the critical arcs for improving the network reliability more effectively. Computational and application examples demonstrate the efficiency and utility of the method, respectively.

To evaluate the travel reliability of an urban rail transit (URT) in normal operation, three travel reliability indicators are proposed from passengers' travel. The connectivity reliability, travel time reliability, and capacity reliability indicators are computed from the weighted average of the number of tolerable travel paths, the ratios of 95-50 quantiles of travel times, and effective residual capacity coefficients between pairs of stations, respectively. The weight of an origin-destination (OD) station pair in a certain time period is the ratio of the passenger trips of this station pair to the passenger trips entering the origin station during that period. The tolerable coefficient, which is the ratio of passengers' tolerable travel time to shortest possible travel time, is proposed to determine the tolerable travel paths. The effective residual capacity coefficient between an OD station pair is calculated with residual capacities and capacities of all tolerable paths between them. The travel reliability indicators are used to evaluate the travel reliability of Chengdu's URT stations and network during different time periods and for different tolerable coefficients. The correlations among the travel reliability indicators of stations are analyzed. The results show the travel reliability of a URT in different time periods and indicate how that reliability is related to the tolerable coefficient. A station with better connectivity reliability often has higher capacity reliability also. Because passengers may choose different tolerable travel paths when multiple tolerable travel paths exist between station pairs, a station with high connectivity reliability may correspond to low travel time reliability. [ABSTRACT FROM AUTHOR]

SUMMARY Capacity reliability is defined as the probability that the network capacity can accommodate a certain volume of traffic demand at a required service level. It is a supply-side reliability measure for assessing the adequacy of a degradable transportation network. The network capacity model used to calculate the capacity reliability measure is based on the concept of reserve capacity, which requires preserving a pre-determined origin-destination (O-D) demand pattern. In this paper, we relax this assumption by allowing a non-uniform growth in the spatial distribution of the O-D demand pattern. By using this non-uniform O-D growth approach, two network capacity models related to the concepts of ultimate capacity and practical capacity are developed to estimate alternate capacity reliability measures. Numerical results are provided to analyze the features of three capacity reliability measures for transportation networks. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

To describe the characteristics of travelers' route choice and estimate capacity reliability of road network with ice and snowfall, the function of generalized travel cost was defined by using the weighted sum of travel time, travel time reliability and safety, and the safety coefficient of driving on ramp was introduced to quantify the safety cost index of driving under ice and snowfall conditions, so that a stochastic user equilibrium (SUE) assignment model was formulated on the assumption of minimization of generalized travel cost in choosing path. The capacity reliability was defined based on the viewpoint of links and its model of road network was set up. Moreover, an assessment method integrated Monte Carlo simulation and solution of traffic plan models was developed. The simulation results show that the weighted coefficients have conspicuous impacts on reliabilities of links and road network, and the adventure travelers' attitude decreases the road network reliability. [ABSTRACT FROM AUTHOR]

To develop an approach to evaluate the capacity reliability of road network based on ice and snowfall conditions, the capacity reliability was studied on the basis of travel time reliability and capacity of links. The concept of network capacity reliability was proposed. Through the introduction of free travel time and capacity correction functions for Bureau of Public Roads (BPR) model, an Ice and Snowfall Based-Bureau of Public Roads (ISB-BPR) function was proposed. Then the bi - level programming model of road network capacity reliability was developed. The travel time reliability and link capacity as restrictions were proposed in the upper programming model. To follow the characteristics of route choice under ice and snowfall conditions, the elastic demand user equilibrium (EDUE) was set up in the lower programming model. An assessment methodology integrating sensitivity analysis of EDUE and Monte Carlo simulation was proposed to evaluate the capacity reliability. A numerical case was also given to demonstrate the practicality of the given model. The results show that the ice and snowfall intensity, traffic supply and demand all have great influence on the capacity reliability. The methodology is useful and applicable. It may provide a basis for network planning, design and maintenance. [ABSTRACT FROM AUTHOR]

Given stochastic features of the demands on both the major road and the minor road at an at-grade un-signalized intersection, the capacity of the minor road is viewed as the vulnerable and critical part impacting on the overall capacity of the intersection. To facilitate the analysis of intersection performance reliability, the capacity reliability of the minor road is defined as the probability that the capacity of the minor road can accommodate a certain traffic demand at a certain degree of saturation. The headway distribution of traffic stream on major road is reflected by three types of distributions, namely, exponential distribution, shifted exponential distribution, and Cowan's M3 distribution. Based on field observations, the volumes on both major roads and minor roads are treated as correlated normal random variables. This paper presents the methods for modeling capacity reliability of the minor road at an at-grade un-signalized priority intersection. A method based on first-order reliability method is used to model the capacity reliability index. As important associated factors of capacity reliability analysis, the methods for modeling and analyzing capacity sensitivity of the minor road and reserve capacity of the priority intersection are also presented. A procedure for evaluating the intersection potential performance using capacity reliability, sensitivity and reserve capacity is developed and demonstrated with a numerical example. Finally, some new findings from the case studies are summarized. [ABSTRACT FROM AUTHOR]

Due to the presence of transportation infrastructure in metropolitan areas, authorities often seek to modify the capacity of existing urban transportation links. Therefore, to meet travel demands, it is necessary to consider public transport (PT) modes and carry out systematic planning. In this research, assuming the existence of urban transportation infrastructure, we develop a mathematical model to determine the amount of link capacity increase for the dual-mode PT network. Such an increase in capacity can improve the network capacity and travel time reliabilities under both normal and peak traffic conditions. To investigate this issue, travel demand is assumed to follow a lognormal distribution under normal conditions. Then, the total travel time and flow through the links are calculated and applied to the model using the Monte Carlo method. In this study, we assume that the links of both transport modes forming a path are interdependent. Moreover, due to NP-hardness, we propose the PSO algorithm with dynamic parameters to solve the multi-objective bi-level model. Considering two public transport modes, we develop the algorithm for a part of the urban transportation network in Tehran, Iran. • Expansion of link capacity in the urban transportation network investigated. • The upper level of the bi-level optimization is a multi-objective problem. • The reliability of travel time and capacity are considered in the bimodal network. • Proposed solution method which can update the parameters of PSO adaptively. [ABSTRACT FROM AUTHOR]