Traveltime Computation Research Articles

Analyzing Access to Health Facilities by Road Using Unconventional Data Sources

The COVID-19 pandemic has led to an urgent need in emerging economies to quickly identify vulnerable populations that do not live within access of a health facility for testing and vaccination. This access information is critical to prioritize investments in mobile and temporary clinics. To meet this need, the World Bank team sought to develop an open-source methodology that could be quickly and easily implemented by government health departments, regardless of technical and data collection capacity. The team explored use of readily available open-source and licensable data, as well as non-intensive computational methodologies. By bringing together population data from Facebook’s Data for Good program, travel-time calculations from Mapbox, road network and point-of-interest data from the OpenStreetMap (OSM), and the World Bank’s open-source GOSTNets network routing tools, we created a computational framework that supports efficient and granular analysis of road-based access to health facilities in two pilot locations—Indonesia and the Philippines. Our findings align with observed health trends in these countries and support identification of high-density areas that lack sufficient road access to health facilities. Our framework is easy to replicate, allowing health officials and infrastructure planners to incorporate access analysis in pandemic response and future health access planning.

Finding Risk-Expenses Pareto-Optimal Routes in Ice-Covered Waters

Multi-objective optimization of a vessel route is considered of key importance when creating automatic navigation systems to ensure independent navigation in ice conditions. This is explained by the need to take into account not only the time or fuel expenditures on the route but also the risks. Previously, only a few models for navigation in ice used the multi-objective approach when finding the set of Pareto-optimal solutions. This paper suggests the multi-objective model of ship routing optimization with usage of the ice chart and ship parameters. Risks for a vessel are related to values of ice thickness and ice concentration in regions to travel through, which are specified by the ice chart. In the model, we use the extended version of the wave algorithm to find a set of routes, from which we select solutions of the Pareto-front for the multi-objective problem. The model uses objective functions of route length, maximum ice thickness, and maximum ice concentration. In addition, the travel time calculations are used in the model. Kaj Riska’s model of ship performance in ice is used for calculating travel time; the speed of a vessel is evaluated in each of the graph edges. The computational example provided in the paper is based on the particular ice chart of the Gulf of Finland. The developed method can be easily implemented for assisting a particular ship in independent ice navigation with the presence of a relevant ice chart.

Analysis of Extended Information Provided by Bluetooth Traffic Monitoring Systems to Enhance Short-Term Level of Service Prediction.

Bluetooth monitoring systems (BTMS) have opened a new era in traffic sensing, providing a reliable, economical, and easy-to-deploy solution to uniquely identify vehicles. Raw data from BTMS have traditionally been used to calculate travel time and origin–destination matrices. However, we could extend this to include other information like the number of vehicles or their residence times. This information, together with their temporal components, can be applied to the complex task of forecasting traffic. Level of service (LOS) prediction has opened a novel research line that fulfills the need to anticipate future traffic states, based on a standard link-based variable, accepted for both researchers and practitioners. In this paper, we incorporate BTMS’s extended variables and temporal information to an LOS classifier based on a Random Undersampling Boost algorithm, which is proven to efficiently respond to the data unbalance intrinsic to this problem. By using this approach, we achieve an overall recall of for up to 15-min prediction horizons, reaching predicting congestion, and improving the results for the intermediate traffic states, especially complex given their intrinsic instability. Additionally, we provide detailed analyses on the impact of temporal information on the LOS predictor’s performance, observing improvements up to a separation of 50 min between last features and prediction horizons. Furthermore, we study the predictor importance resulting from the classifiers to highlight those features contributing the most to the final achievements.

Increased Travel Time to the Tertiary Centre Is Associated With Decreased Long-term Survival Following Ascending Aortic Operations.

The association between travel time from tertiary care centre and outcomes after ascending thoracic aortic surgery is unknown. We determined the effect of travel time from the tertiary care centre on outcomes in ascending aortic repair in Nova Scotia. A retrospective analysis of patients undergoing elective and emergent ascending thoracic aortic operations from 2005 to 2015 was carried out. Patient's residential geographic coordinates were used to calculate travel time to the tertiary care centre, and patients who resided < 1 hour vs ≥ 1 hour were compared. Multivariable logistic regression was performed to determine the effect of travel time on in-hospital outcomes. Cox-proportional hazard modelling and Kaplan-Meier survival estimates were created to determine the effect on long-term survival. A total of 476 patients underwent ascending thoracic aortic surgery from 2005 to 2015. Patients who resided < 1 hour from the tertiary care centre vs patients who resided ≥ 1 hour had similar rates of in-hospital mortality (4.4% vs 6.1%, P= 0.42), in-hospital composite complications (66.7% vs 67.7%, P= 0.80), hospital length of stay (median 9 days; interquartile range [7-16] vs 10 [7-17], P= 0.41), and discharge disposition other than home (9.7% vs 11.7%, P= 0.55). Compared with patients who resided < 1 hour from the tertiary centre, patients who resided ≥ 1 hour were at higher risk for long-term mortality (hazard ratio, 2.19; 95% confidence interval, 1.13-4.28; P= 0.02). Patients who reside remotely from the tertiary centre experience equivalent in-hospital outcomes but decreased long-term survival following ascending aortic operations. These findings may guide resource expansion for postoperative follow-up.

AS/R system travel time in class-based storage with different input-output point levels: a proposed formula

PurposeThis paper aims to propose a simulation model integrated with an empirical regression analysis to provide a new mathematical formulation for automated storage and retrieval system (AS/RS) travel time estimation under class-based storage and different input/output (I/O) point vertical levels.Design/methodology/approachA simulation approach is adopted to compute the travel time under different warehouse scenarios. Simulation runs with several I/O point levels and multiple shape factor values.FindingsThe proposed model is extremely precise for both single command (SC) and dual command (DC) cycles and very well fitted for a reliable computation of travel times.Research limitations/implicationsThe proposed mathematical formulation for estimating the AS/RS travel time advances widely applied methodologies existing in literature. As well as, it provides a practical implication by supporting faster and more accurate travel time computations for both SC and DC cycles. However, the regression analysis is conducted based on simulated data and can be refined by numerical values coming from real warehouses.Originality/valueThis work provides a new simulation model and a refined mathematical equation to estimate AS/RS travel time.

Public transport accessibility to hospitals in the city of Córdoba: a comparative analysis in times of a pandemic (2019-2021)

Purpose: to evaluate the potential accessibility to public hospitals between 2019 and 2021. Methodology/Approach: comparative analysis of travel times by public transport, calculated using the r5r package in R with the GTFS provided by the municipality. Findings: for the three hospital categories evaluated, travel times increased around 20% in the study period, and the most vulnerable quintiles of population increased their travel times 8 points above the less vulnerable quintiles. Research Limitation/implication: travel times were calculated with programmed schedules and frequencies and fixed values of maximum travel time and maximum walking distance. Originality/Value of paper: comparative analysis pre-COVID and during COVID of geographical accessibility to healthcare centers. Use of the r5r package that allows changes in the parameters to calculate travel times such as maximum walking distance, maximum travel time, departure time or percentiles.

Calculating place-based transit accessibility: Methods, tools and algorithmic dependence

To capture the complex relationships between transportation and land use, researchers and practitioners are increasingly using place-based measures of transportation accessibility to support a broad range of planning goals. This research reviews the state-of-the-art in applied transportation accessibility measurement and performs a comparative evaluation of software tools for calculating accessibility by walking and public transit including ArcGIS Pro, Emme, R5R, and OpenTripPlanner using R and Python, among others. Using a case study of Toronto, we specify both origin-based and regional-scale analysis scenarios and find significant differences in computation time and calculated accessibilities. While the calculated travel time matrices are highly correlated across tools, each tool produces different results for the same origin-destination pair. Comparisons of the estimated accessibilities also reveal evidence of spatial clustering in the ways paths are calculated by some tools relative to others at different locations around the city. With the growing emphasis on accessibility-based planning, analysts should approach the calculation of accessibility with care and recognize the potential for algorithmic dependence in their calculated accessibility results.

Solving the eikonal equation for compressional and shear waves in anisotropic media using peridynamic differential operator

SUMMARY Traveltimes of compressional (P) and shear (S) waves have proven essential in many earthquake and exploration seismology applications. An accurate and efficient traveltime computation for P and S waves is crucial for the success of these applications. However, solving the eikonal equation with a complex phase velocity field in anisotropic media is challenging. The eikonal equation is a first-order nonlinear hyperbolic partial differential equation. It represents the high-frequency asymptotic approximation of the wave equation. The fast marching and sweeping methods are commonly used due to their efficiency in numerically solving the eikonal equation. However, these methods suffer from numerical inaccuracy in anisotropic media with sharp heterogeneity, irregular surface topography and complex phase velocity fields. This study presents a new method for the solution of the eikonal equation by employing the peridynamic differential operator (PDDO). The PDDO provides the non-local form of the eikonal equation by introducing an internal length parameter (horizon) and a weight function with directional non-locality. The operator is immune to discontinuities in the form of sharp changes in field or model variables and invokes the direction of traveltime in a consistent manner. The weight function controls the strength of association among points within the horizon. Solutions are constructed in a consistent manner without upwind assumptions through simple discretization. The robustness of this approach is established by considering different types of eikonal equations on complex velocity models in anisotropic media. The examples demonstrate its unconditional numerical stability and results compare well with the reference solutions.

Intelligent DoS Attack Detection with Congestion Control Technique for VANETs

Vehicular Ad hoc Network (VANET) has become an integral part of Intelligent Transportation Systems (ITS) in today's life. VANET is a network that can be heavily scaled up with a number of vehicles and road side units that keep fluctuating in real world. VANET is susceptible to security issues, particularly DoS attacks, owing to maximum unpredictability in location. So, effective identification and the classification of attacks have become the major requirements for secure data transmission in VANET. At the same time, congestion control is also one of the key research problems in VANET which aims at minimizing the time expended on roads and calculating travel time as well as waiting time at intersections, for a traveler. With this motivation, the current research paper presents an intelligent DoS attack detection with Congestion Control (IDoS-CC) technique for VANET. The presented IDoS-CC technique involves two-stage processes namely, Teaching and Learning Based Optimization (TLBO)-based Congestion Control (TLBO-CC) and Gated Recurrent Unit (GRU)-based DoS detection (GRU-DoSD). The goal of IDoS-CC technique is to reduce the level of congestion and detect the attacks that exist in the network. TLBO algorithm is also involved in IDoS-CC technique for optimization of the routes taken by vehicles via traffic signals and to minimize the congestion on a particular route instantaneously so as to assure minimal fuel utilization. TLBO is applied to avoid congestion on roadways. Besides, GRU-DoSD model is employed as a classification model to effectively discriminate the compromised and genuine vehicles in the network. The outcomes from a series of simulation analyses highlight the supremacy of the proposed IDoS-CC technique as it reduced the congestion and successfully identified the DoS attacks in network.

MFAST: A MATLAB toolbox for ocean bottom seismometer refraction first-arrival traveltime tomography

First-arrival seismic traveltime tomography (FAST) is a well-established technique to estimate subsurface velocity structures. Although several existing open-source packages are available for first-arrival traveltime tomography, most were written in compiled languages and lack sufficient extendibility for new algorithms and functionalities. In this work, we develop an open-source, self-contained FAST package based on MATLAB, one of the most popular interpreted scientific programming languages, with a focus on ocean bottom seismometer refraction traveltime tomography. Our package contains a complete traveltime tomography workflow, including ray-tracing-based first-arrival traveltime computation, linearized inversion, quality control, and high-quality visualization. We design the package as a modular toolbox, making it convenient to integrate new algorithms and functionalities as needed. At the current stage, our package is most efficient for performing FAST for two-dimensional ocean bottom seismometer surveys. We demonstrate the efficacy and accuracy of our package by using a synthetic data example based on a modified Marmousi model.

The modeling of effective parameters on public bus passengers’ boarding time prediction

Passengers’ boarding times at bus stops have a great importance to calculate dwell and travel time for scheduling process in public transport operations. However, there are not so much observed boarding times data in the actual bus transport systems and it may cause some prediction problems in scheduling process of public transport operations. For this reason, accurate estimation of the boarding times will ensure correct calculation of dwell and total travel time for bus transport systems. Based on this idea, this study aims to model boarding times of each passengers by evaluating different parameters using two different (statistical and optimization analysis) methods. For this purpose, a comprehensive data collection process was conducted in total seven different cities of Turkey based upon their population. Two new models were developed for boarding time estimation by evaluating various parameters using a multiple Ordinary Least Square (OLS) regression and Artificial Bee Colony (ABC) algorithm as statistical and optimization methods, respectively. Study results showed that modeling of boarding times by considering various parameters is an effective strategy to improve the performance of bus transport systems by using developed two models

Fast and accurate calculation of seismic wave travel time in 3D TTI media

Fast and accurate calculation of seismic wave travel time in 3D TTI media

Application Of Finite Difference Eikonal Solver For Traveltime Computation In Forward Modeling And Migration

Traveltime is one of the propagating wave’s components. As the wave propagates further, the traveltime increases. It can be computed by solving wave equation of the ray path or the eikonal wave equation. Accurate method of computing traveltimes will give a significant impact on enhancing the output of seismic forward modeling and migration. In seismic forward modeling, computation of the wave’s traveltime locally by ray tracing method leads to low resolution of the resulting seismic image, especially when the subsurface is having a complex geology. However, computing the wave’s traveltime with a gridding scheme by finite difference methods able to overcomes the problem. This paper aims to discuss the ability of ray tracing and fast marching method of finite difference in obtaining a seismic image that have more similarity with its subsurface model. We illustrated the results of the traveltime computation by both methods in form of ray path projection and wavefront. We employed these methods in forward modeling and compared both resulting seismic images. Seismic migration is executed as a part of quality control (QC). We used a synthetic velocity model which based on a part of Malay Basin geology structure. Our findings shows that the seismic images produced by the application of fast marching finite difference method has better resolution than ray tracing method especially on deeper part of subsurface model.

State Estimates and Forecasts of the Northern Philippine Sea Circulation including Ocean Acoustic Travel Times

AbstractThe 2010–11 North Pacific Acoustic Laboratory (NPAL) Philippine Sea experiment measured travel times between six acoustic transceiver moorings in a 660-km diameter ocean acoustic tomography array in the northern Philippine Sea (NPS). The travel-time series compare favorably with travel times computed for a yearlong series of state estimates produced for this region using the Massachusetts Institute of Technology General Circulation Model–Estimating the Circulation and Climate of the Ocean four-dimensional variational (MITgcm-ECCO 4DVAR) assimilation system constrained by satellite sea surface height and sea surface temperature observations and by Argo temperature and salinity profiles. Fluctuations in the computed travel times largely match the fluctuations in the measurements caused by the intense mesoscale eddy field in the NPS, providing a powerful test of the observations and state estimates. The computed travel times tend to be shorter than the measured travel times, however, reflecting a warm bias in the state estimates. After processing the travel times to remove tidal signals and extract the low-frequency variability, the differences between the measured and computed travel times were used in addition to SSH, SST, and Argo temperature and salinity observations to further constrain the model and generate improved state estimates. The assimilation of the travel times reduced the misfit between the measured and computed travel times, while not increasing the misfits with the other assimilated observations. The state estimates that used the travel times are more consistent with temperature measurements from an independent oceanographic mooring than the state estimates that did not incorporate the travel times.

Analysis of Hypocenter Relocation by Using Double Difference Method in a Deep Underground Mining

Hypocenter relocation is one of the keys to success in the analysis of seismicity induction in underground mines. Overburden thickness, topography, geological complexity, and mining activities can result in newly induced seismicity that can endanger the safety of underground mine workers. The relatively narrow underground mine area requires the most accurate hypocenter location information possible. The double-difference algorithm approach is one of the keys to overcoming this problem. The double-difference method is a relative location method that tries to minimize the residuals between the observed and calculated travel time differences for pairs of microseismic events at each station, by adjusting the differences between all pairs of events at each station repeatedly. In this study, we utilized microseismic measurement data in the deepest underground mine in Indonesia. A total of 1783 seismic events were successfully relocated. The relocation results show the rock mass stress which is illustrated by the distribution of events around the cave, especially the abutment area and underground mining tunnels.

Homotopy solutions of the acoustic eikonal equation for strongly attenuating transversely isotropic media with a vertical symmetry axis

Many applications in seismology involve the modeling of seismic-wave traveltimes in anisotropic media. We have developed homotopy solutions of the acoustic eikonal equation for P-wave traveltimes in attenuating transversely isotropic media with a vertical symmetry axis. Instead of the commonly used perturbation theory, we use the homotopy analysis method to express the traveltimes by a Taylor series expansion over powers of an embedding parameter. For the derivation, we first perform homotopy analysis of the eikonal equation and derive the linearized ordinary differential equations for the coefficients of the Taylor series expansion. Then, we obtain the homotopy solutions for the traveltimes by solving the linearized ordinary differential equations. Results of our investigation with approximate formulas demonstrate that the analytical expressions are efficient methods for the computation of traveltimes from the eikonal equation. In addition, these formulas are also effective methods for benchmarking approximate numerical solutions in strongly attenuating anisotropic media.

Single Pass Computation of First Seismic Wave Travel Time in Three Dimensional Heterogeneous Media With General Anisotropy

We present a numerical method for computing the first arrival travel-times of seismic waves in media defined by a general Hooke tensor, in contrast with previous methods which are limited to a specific subclass of anisotropic media, such as “tilted transversally isotropic” (TTI) media or “tilted orthorhombic” (TOR) media in Waheed et al. (G 80: 49-58, 2015), Bouteiller et al. (GJlI 212: 1498-1522, 2017). Our method proceeds in a single pass over the discretized domain, similar to the fast marching method, whereas existing methods for these types of anisotropy require multiple iterations, similar to the fast sweeping method. We introduce a new source factorization model, making it possible to achieve third-order accuracy in smooth media. We also validate our solver by comparing it with the solution of the elastic wave equation in a 3D medium with general anisotropy.

1206Will access to Covid-19 vaccine in Aotearoa be equitable for priority populations?

Abstract Background This research examines the equity implications of the geographic distribution of COVID-19 vaccine delivery locations in Aotearoa New Zealand under five potential scenarios: (1) stadium mega-clinics; (2) Community Based Assessment Centres; (3) GP clinics; (4) community pharmacies; and (5) schools. Methods We mapped the distribution of Aotearoa New Zealand’s population and the location of potential vaccine delivery facilities under each scenario. Geostatistical techniques identified population clusters for Māori, Pacific and people aged 65 years and over. We calculated travel times between all potential facilities and each Statistical Area 1 in the country. Descriptive statistics indicate the size and proportion of populations that could face significant travel barriers when accessing COVID-19 vaccinations. Results Several areas with significant travel times to potential vaccine delivery sites were also communities identified as having an elevated risk of COVID-19 disease and severity. All potential scenarios for vaccine delivery, with the exception of schools, resulted in travel barriers for a substantial proportion of the population. Overall, these travel time barriers disproportionately burden Māori, older communities and people living in areas of high socioeconomic deprivation. Conclusions The equitable delivery of COVID-19 vaccines is key to an elimination strategy. However, if current health services and facilities are used without well-designed and supported outreach services, then access to vaccination is likely to be inequitable. Key messages Organisations need to proactively plan for equity, including the delivery of COVID-19 vaccines. A social justice approach should be prioritised, and in Aotearoa Te Tiriti o Waitangi obligations must be met.

An iterative factored topography-dependent eikonal solver for anisotropic media

Accurate and efficient eikonal solvers for heterogeneous media play an important role in many areas of seismology, such as seismic tomography, migration, and earthquake localization. Incorporating seismic anisotropy and complex topography remain a computational challenge for finite-difference eikonal solvers. In recent years, the topography-dependent eikonal equation (TDEE) has been proposed as an effective way to calculate seismic traveltimes for isotropic and anisotropic media with irregular topography. However, the Lax-Friedrichs sweeping method used in previous studies to approximate the viscosity solution of TDEE for anisotropic media is more dissipative and needs a much higher number of iterations to converge. In addition, the TDEE solution for the initial point source has an upwind source singularity, which makes all TDEE solvers, even the high-order ones, exhibit polluted convergence and relatively large errors that propagate from the point source to the entire computational domain. To solve these problems, we have formulated the factored topography-dependent anisotropic eikonal (FTDAE) equation in tilted transversely isotropic (TTI) media using the factorization principle. Then, the resulting quartic equation can be numerically solved by using a fixed-point iteration technique based on the simpler elliptical anisotropic eikonal (EAE) equation with a high-order source term due to anelliptical anisotropy introduced by TTI media. At each iteration, the unknown traveltime in the EAE equation is factored into two functions: One of the functions is specified analytically to capture the source singularity, such that the unknown factor is differentiable in the source neighborhood and could be solved by the fast sweeping method. Numerical examples indicate that our FTDAE solver can treat source singularity successfully and achieve high accuracy after just a few iterations, independently of the mesh size, which could provide a more efficient and robust tool for traveltime calculation in the presence of seismic anisotropy and complex surfaces.

Microseismic P-Wave Travel Time Computation and 3D Localization Based on a 3D High-Order Fast Marching Method.

The travel time computation of microseismic waves in different directions (particularly, the diagonal direction) in three-dimensional space has been found to be inaccurate, which seriously affects the localization accuracy of three-dimensional microseismic sources. In order to solve this problem, this research study developed a method of calculating the P-wave travel time based on a 3D high-order fast marching method (3D_H_FMM). This study focused on designing a high-order finite-difference operator in order to realize the accurate calculation of the P-wave travel time in three-dimensional space. The method was validated using homogeneous velocity models and inhomogeneous layered media velocity models of different scales. The results showed that the overall mean absolute error (MAE) of the two homogenous models using 3D_H_FMM had been reduced by 88.335%, and 90.593% compared with the traditional 3D_FMM. On that basis, the three-dimensional localization of microseismic sources was carried out using a particle swarm optimization algorithm. The developed 3D_H_FMM was used to calculate the travel time, then to conduct the localization of the microseismic source in inhomogeneous models. The mean error of the localization results of the different positions in the three-dimensional space was determined to be 1.901 m, and the localization accuracy was found to be superior to that of the traditional 3D_FMM method (mean absolute localization error: 3.447 m) with the small-scaled inhomogeneous model.