Modeling Day-to-day Flow Dynamics on Degradable Transport Network

Variation in Patients' Travel Times among Imaging Examination Types at a Large Academic Health System

Uncertainties often exist in traffic systems because of interday route flow swapping and intraday road capacity degradation. These uncertainties obviously affect the traveler’s individual route adjustment behavior and the corresponding network traffic dynamic evolution at an aggregate level. Seeking to give a more realistic description of traffic dynamics, this study extends the existing day-to-day (DTD) model by considering both travelers’ study of uncertain travel time and travelers’ choice of risky routes. In the proposed model, an exponential-smoothing filter is introduced to describe travelers’ study of uncertain travel time. Meanwhile, on-time arrival probability is used to model travelers’ dynamic adjustment to their reference travel time (RTT). Under the framework of cumulative prospect theory, the perceived stochastic route travel time and the RTT are both integrated into a unified prospect value function to reflect travelers’ perception of route attractiveness. On this basis, a logit model is applied to describe travelers’ stochastic route choice behaviors. The proposed model’s several mathematical properties, including fixed-point existence, uniqueness, and stability, are also investigated through theoretical analyses. Numerical examples are used to illustrate the applications of the DTD model and verify some important dynamic system properties.

Evaluating the impact of public transport travel time inaccuracy and variability on socio-spatial inequalities in accessibility

The use of autonomous buses increases, and their operations increasingly intertwine with other public transport lines. At the same time, the use of autonomous buses in a mixed traffic environment induces new challenges with respect to their service synchronization with other lines. In fact, due to their cautious driving behavior in a mixed environment, the operations of autonomous buses show a high degree of variation in inter-station travel times, which leads to many unsuccessful transfers. Many tactical planning problems, however, naively assume that this uncertainty can be reduced to a single deterministic value (e.g., a travel time expectation). In this study, we propose a technique to find a robust schedule of dispatching and holding times that incorporates the inherent uncertainty in the operations. We discuss the complexity and applicability of such robust problems in public transit operations in general, and solve the optimization problem for an autonomous bus system that serves as a feeder line to a collector line. The numerical experiments show that the robust rescheduling and holding solution is resilient to variations in travel times: the operations maintain a high level of service regularity and avoid missed passenger transfers even under extreme scenarios.

: The anisotropic ocean environment will lead to variability of ocean acoustic travel time. The variability of travel times comes from several ocean dynamical processes, including eddies, internal tides, and stochastic internal waves. This study analyzes time series of travel time from the Philippine Sea 20102011 experiment conducted by the Scripps Institution of Oceanography. In this experiment, a pentagonal array of acoustic transceivers of radius 600-km transmitted 250 Hz pulses for the purpose of observing acoustic variability at multiple time and space scales. Using filtering methods, this study separates variability in travel time in bands associated with eddies, internal tides, and stochastic internal waves. The observed fluctuations in the internal wave band are compared to a simple theoretical model. The result of the research shows that over the year, eddies induce the largest amount of variability. Internal tides and internal waves show comparable fluctuations. There is some seasonal variability. Eddies and internal waves show fluctuations that are fairly isotropic across the array, while internal tides give highly anisotropic fluctuations. This anisotropy is related to the strong directionality of the internal tides that emanate from the Luzon Strait.

Effect of complex traffic situations on route choice behaviour and driver stress in residential areas

This study applies high-resolution archived transit data to study the effect of roadway changes using data collected before and after the completion of a project affecting transit. Methodologies are presented to compare percentile and time-of-day performance measures before and after the project. In addition, differences in travel time and travel-time variability are examined over the altered route. The case study examines one heavily used route in Portland that was recently diverted onto a newly built transit-only bridge to examine the claims that travel times would decrease and reliability would increase. The results of this study indicate that travel times increased for the majority of trips but travel-time variability during the peak period was sharply reduced.

Exploring travel time distribution and variability patterns is essential for reliable route choices and sophisticated traffic management and control. State-of-the-art studies tend to treat different types of roads equally, which fails to provide more detailed analysis of travel time characteristics for each specific road type. In this study, based on a vast amount of probe vehicle data, 200 links inside the Third Ring Road of Beijing, China, were investigated. Four types of roads were covered including urban expressways, auxiliary roads of urban expressways, major roads, and secondary roads. The day-of-week distributions of unit distance travel time were first analyzed. Kolmogorov-Smirnov test, Anderson-Darling test, and chi-squared test were employed to test the goodness-of-fit of different distributions and the results showed lognormal distribution was best-fitted for different time periods and road types compared with normal, gamma, and Weibull distribution. In addition, four reliability measures, that is, unit distance travel time, coefficient of variation, buffer time index, and punctuality rate, were used to explore the day-of-week travel time variability patterns. The results indicated that urban expressways, auxiliary roads of urban expressways, and major roads have regular and distinct morning and afternoon peaks on weekdays. It is noteworthy that in daytime the travel times on auxiliary roads of urban expressways and major roads share similar variability patterns and appear relatively stable and reliable, while urban expressways have most reliable travel times at night. The results of analysis help enable a better understanding of the volatile travel time characteristics of each road type in urban network.

Despite the importance of reliability, few countries monitor it or explicitly incorporate it into transport policy making. Nevertheless, a number of policy options are available to improve this aspect of transport management. Active management of the network through ramp metering is recognized as an efficient way to control motorway traffic and improve average travel time. Far less is said about the reliability benefits of ramp metering. This paper assesses reliability benefits of ramp metering on the basis of a before-and-after study on the A6W, a French motorway near Paris. Several indicators for travel time variability are applied before and after the introduction of ramp metering. For purposes of taking reliability into account in policy impact evaluation, cost–benefit assessment provides a consistent framework within which to assess the monetized benefits. The monetary value of the reliability benefits of ramp metering is therefore calculated, and the policy implications of the results are discussed. The results suggest that in addition to providing gains in average travel time, ramp metering significantly improves reliability of travel times. It is also proposed that indices such as buffer time or planning time are useful for communicating the results, both for network operators and for users. Failing to unbundle the time-savings benefits of a project between average travel time and the variability in travel time is likely to lead to suboptimal policy solutions. Managing existing capacity better can be a cost-effective way to improve both average travel time and the variability in travel time.

Sensitivity analysis based approximation models for day-to-day link flow evolution process

To study the relationship of different reliability indices for road network under stochastic demand, an evaluation method based on travel time reliability (TTR) was set up for level of service (Los) reliability. Assuming that travelers acquire the variation of the route travel time based on past experiences and factor such variability into their route choice considerations in the form of travel time budget, which was defined as the minimal travel time that can accommodate a specified travel time reliability and can be derived according to the probability characteristics of log-normal distribution. Accordingly, Los reliability evaluation models of link and road network were proposed based on the link flow distribution, which can be determined by a travel time budget-based variational inequality (VI) network equilibrium model and a route-based solution algorithm. Some numerical studies on a small road network were presented to validate the proposed method and algorithm.

Scheduling preferences and the value of travel time information

Fosgerau's travel time reliability ratio and the Burr distribution

Unreliable transport systems cause stress and anxiety for travelers and create difficulties for authorities managing network operations. This study conducted a comprehensive investigation of travel time distributions in terms of various time windows based on extensive automatic vehicle identification data collected from the CityLink Tollway in Melbourne, Australia. The study also examines the components of travel time variability and explores their relationships. Given the number of factors affecting travel time variability and their interaction effects, multiple regression analysis is used to quantify the contribution of the various sources to the variability in travel time. Application of the methodology to two groups of data—namely, travel times in morning peak and afternoon peak—demonstrates that they have distinctive sources of variability. Morning peak travel times vary mostly because of driver-related factors, specifically lane choice decisions, whereas 25% of the variability of travel times in the afternoon peak corresponds to capacity-related factors.

This paper describes the application of the perception-preference- selection model which has been utilized in the field of marketing science to the study of the route choice behaviour based on a variety of factors including the mental aspects. The analysis of the data from the questionnaires revealed the major route choice criteria i. e., road conditions, variability in travel time and driver's familiarity with the route. The probability of a specific route being chosen estimated by the utility function which was derived from the preference model agreed well with the observed value. In conclusion the usefulness of the model was proved.