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In this paper, a model to estimate travel time reliability is proposed assuming a stochastic user equilibrium. Travel time reliability is defined as the probability that travel time between the origin and destination does not exceed a standard travel time corresponding to each service level. Also it is shown how to calculate travel time reliability in a large-scale network. This model is applied to the road network in the Hanshin area to evaluate new lines in the national road plan from the viewpoint of travel time reliability. Some important links and lines in the future road network are evaluated from the viewpoint of travel time reliability.

The importance of the adverse impacts of network degradation has stimulated substantial international research interest in transport network reliability, that is, the ability of degraded transport networks to cope with travel demand. Most of the recent research effort has focused on the reliability of urban passenger transport networks, in terms of the probability that the network will deliver a required standard of performance. This situation is characterised by high levels of congestion, a dense road network, and quantifiable probability of degradation of the network. Outside major urban centres, the situation is very different. The main dominant consideration in transport network infrastructure provision is accessibility - linking urban centres, providing regional coverage, and basic levels of accessibility for the non-urban community and economy. The network is sparse, congestion is not a significant issue, and access to essential community services and to markets is the major driving force underlying network development. In this context, the vulnerability of the network is perhaps more important than ‘reliability’. This paper develops the concept of network vulnerability. It begins by reviewing the current state of research into network reliability, then proposes extensions and adaptations to the reliability concepts that are more appropriate for strategic-level multi-modal transport systems. Several alternative definitions for vulnerability are proposed. The paper also discusses the development of algorithmic and visualisation tools that may be used to identify specific ‘weak spots’ in a network, where failure of some part of the transport infrastructure would have the most serious effects on access to specific locations and on overall system performance. Finally, the paper describes potential applications of network vulnerability concepts, and proposes directions for further research.

This paper attempts to assess the parking reliability with taking into account drivers' travel choice behaviors under various traffic conditions. Apart from the well-known travel-time reliability, a parking reliability is newly defined as the probability that the drivers' average searching time for parking is less than a given threshold. This is particularly important under conditions of shortage of parking spaces in urban areas. A Monte Carlo simulation approach, which incorporates a combined trip distribution and assignment model with explicit elastic demand function, is proposed to estimate the two reliability measures of road network (i.e. travel-time and parking reliabilities). A numerical example is used to illustrate the applications of the reliability measures and the proposed approach.

Travel time variability has generally been recognized as one of the most important attributes in travelers' route choice decisions. In fact, many empirical studies have indicated that both passengers and freight carriers are strongly averse to travel time variability, because it introduces uncertainty to their route choice decisions. In this chapter, we examine the effect of incorporating travel time variability and risk-taking behavior into the route choice models and its impact on the estimation of travel time reliability under demand and supply variations.

In this study, a mode choice model explicitly considering travel time reliability is developed. This model quantifies travelers' attitudes towards travel time variability as well as average travel time. Data were collected from the morning commuters who have two or three alternative modes including some public transportation and private vehicles. The survey period includes both a normal period where all the transportation modes were available and an abnormal period where the main major public transportation service was closed. The model is applied to practical commuters' decision making, and one of the findings in the mode choice model is that they pay relatively large attention to the travel time variability. In this model, travel time variability is dealt with as the possibilities that the commuters arrive before or after their job starting time separately. The best-fit model indicates that the commuters pay more attention to early arrival and less to late arrival in the normal period. In the abnormal period, however, their attention shifts drastically to late arrival. This suggests that the commuters behave optimistically in the normal period and pessimistically in the abnormal period.

The objective of this paper is to give an overview of various reliability concepts that have been developed in the last decades. The paper first summarises various indicators that have been developed in order to measure the reliability of a network and then looks at techniques to calculate these indicators. The usefulness and limitations of the different indicators is discussed. The paper suggests that there is no single perfect indicator but that the choice of indicator and technique depends on several factors, including the viewpoint of the analyst and the type and range of interventions being considered. In order to assess the impact of incidents the authors propose to distinguish between three types of intervention, namely “benevolent”, “neutral” or random, and “malevolent”. Also discussed is why the provision of up-to-date information to the traveller has a central role to play when trying to minimise the impact of an incident.

This paper attempts to assess the transit service reliability with taking into account the interaction between network performance and passengers' travel choice behaviors. Besides the well-known schedule reliability, a waiting-time reliability is newly defined as the probability that the passengers' average waiting time is less than a given threshold. A Monte Carlo simulation approach, which incorporates a stochastic user equilibrium transit assignment model with explicit capacity constraints and elastic frequencies, is proposed to estimate the above two reliability measures of transit service. A numerical example is used to illustrate the applicability of the reliability measures and the proposed approach.

This paper provides a day-to-day analysis of the reliability of commuting time and trip scheduling under the Advanced Traveler Information System (ATIS). A simple network with parallel routes and bottleneck congestion is used to simulate the departure time and route choice decisions of commuters to minimize total travel time and scheduling delay cost. There are two major factors influencing the decisions of drivers in their departure time and route choices: their accumulated travel experience and information provided by ATIS. A simple experiment is carried for investigating trip-scheduling reliability of this network system.

This chapter discusses the reliability of the NBPTS assessments. In order to meet the challenge of ensuring reliability of a complex performance assessment, particular attention was given to the design of the assessment and scoring processes. Several models for considering and determining the reliability of the assessment are also introduced. Results from two assessment cohorts are presented. These results demonstrate that the design features of the NBPTS system support a relatively reliable set of assessments without compromising the complexity of the teaching performance it was designed to assess.