Search results

Road network performance when a large disaster happens depends on how the road traffic is regulated. To evaluate the performance of the road network, one should consider the traffic regulation in an emergent condition. Authors have proposed the idea of area traffic regulation when a large disaster occurs (Iida, et al., 2000). In the former paper, a bi-level optimisation model to calculate the optimal regulation ratio is proposed. This paper proposes an efficient and fast method to calculate regulation ratios for two-stage road traffic regulation. The simplified model adopts linear programming method instead of bi-level optimisation method, which is quicker and simpler. The simpler algorithm contributes to conduct various kinds of case studies, and helps finding a reliability of the road network considering traffic regulations after a disaster.

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.

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.

This study was performed to examine the relationship between dynamic traffic information and driver's route choice behavior when non-recurrent events cause traffic jams. To enhance the effectiveness and applicability of the information system as a traffic control measure, it is important to investigate the influence of the software aspects of a dynamic traffic information system; these software aspects include information content and the timing of information delivery. This study was undertaken to investigate whether providing drivers with dynamic traffic information might relieve traffic jams and improve travel time reliability. A questionnaire survey was conducted to obtain data regarding the respondents' attitudes to detours and their stated preference (SP) of route choice behavior. These data are used to analyze the characteristics of drivers who show negative and positive attitudes to detours, including driver information usage and knowledge about the alternative routes. Also, this study analyzes the relation between the way to provide drivers with information and driver's decision-making on route using the SP data. Especially, the analytical attentions are paid to the influences of both timing and contents of information provided upon the respondent' route choices.

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.

Emergency vehicles should be planned to have smooth access to people's residences after a large scale disaster. This study proposes ANR, the Accessible Node Rate, which represents the ratio of the number of accessible nodes to total nodes in the network, as an indicator for evaluating the reliability of a local street network. Using the ANR, this study evaluates the urban districts of Nada Ward in Kobe City where the earthquake caused extensive damage, and proposes planning changes to provide the local street networks with higher reliability. Furthermore, in order to see if the ANR can be used for analyzing another city's reliability, a case study of Beppu City which is supposed to have the possibility of the same magnitude of earthquake, is examined. A system that supports traffic network editing and analysis for reducing the workload in a wider area is developed.

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.

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 paper describes and extends the game theoretic approach to network vulnerability assessment. The basic idea is to set up a game between the network users who are trying to minimise their expected travel time by choice of route and a network tester who is trying to penalise the users most by degrading a link through capacity reduction leading to congestion. The method therefore finds the worst possible location for a link degradation, taking re-routing options into account (an upper, lower bound of impact). The original game identifies the weakest link for routes between an OD pair in the network. Two variations are introduced in this paper in order to determine the weak links for a specific origin or a specific destination and for the whole network. All three game variations are tested on a small network in Leicester and the results are presented.