Traveltime Computation Research Articles

Just do it! Combining agent-based travel demand models with queue based-traffic flow models

Proper travel demand models aim to create an equilibrium between expected travel times in the planning phase and simulated travel times after mapping the road traffic on the road network. While agent-based travel demand models (ABM) focus on the trip generation mainly based on pre-calculated travel times, traffic flow models simulate these trips and compute travel times taking into account speed restrictions and road capacities. This leads to deviations between the simulated travel times and the initially expected ones especially during rush hour so that both models are not in equilibrium state. Due to the complexity and limited computational resources, combinations of these two models are often simplified in either one or both parts. In this work we present an iteratively combined simulation model with feedback of travel times. We couple an ABM with a queue-based traffic flow model which simulates the set of trips for each agent. The ABM used adjusts its activity generation, destination choice and mode choice according to the re-calculated travel times resulting in more realistic day plans. The traffic flow model takes the sequential character of the trips into account and propagates the delay to the subsequent trips of each modelled agent, resulting in feasible trips. We show that equilibrium of travel time between these two models can be achieved with a low number of iterations. Our approach is sensitive to new travel times in destination and mode choice and results in trips which are consistent for a whole day for each modelled agent.

Estimated travel time between the city (Case study: Waru Street-Mojokerto)

The area in Surabaya and Mojokerto is an industrial area that is increasing quite rapidly. Based on City Mojokerto in Figures Year 2016. From an industrial estate is a change of land use from agriculture or ponds into settlements and / or industries. The occurrence of congestion along this road because of the capacity that is not sufficient to accommodate the number of vehicles passing. The purpose of this research is to know the model of land use interaction, knowing the network performance and know the travel time to be passed. And analyze what components affect the calculation of travel time. Necessary data. The existing land layout along the road and the average traffic calculation data on the road in the study area. To know the travel time must be known in advance the capacity of the road that can be accommodated along the road. After the capacity is known the service performance becomes the main factor in determining road network performance. This research uses regression analysis for land use modeling.

Algorithms for Motion Optimization on a Given Trajectory Taking into Account Weather Forecast and Constraints

Abstract The paper is devoted to the problem of motion optimization of a ship on a given long trajectory with respect to weather forecast and additional constraints. This problem has practical meaning for long distances, where saving of fuel consumption and reducing travel time is of significant importance. A finite-dimensional formulation of the optimization problem is considered taking into account the mathematical model of ship motion, weather forecast, constraints and given cost functionals. The computational algorithms for calculation of travel time and fuel consumption are proposed. The main result is presented by the algorithm for optimizing the velocity distribution on a given trajectory. This algorithm is based on the representation of the route of motion on a fixed trajectory in two-dimensional space. The obtained results are demonstrated by illustrative examples.

Finite difference calculation of traveltime on non-orthogonal grid

Finite difference calculation of traveltime on non-orthogonal grid

A Simple Method to Show the Economic and Educational Value of Wildlife and Wildlands

A Simple Method to Show the Economic and Educational Value of Wildlife and Wildlands

An experimental result of distance and travel time calculations between two locations using freely available spatial data, GIS software, and web services

An experimental result of distance and travel time calculations between two locations using freely available spatial data, GIS software, and web services

A more realistic approach towards concrete delivery dispatching problem: using real distance instead spatial distance

The Ready Mixed Concrete Dispatching Problem (RMCDP) is a generalised version of the Vehicle Routing Problem (VRP). In RMCDP however, given the particular properties of concrete, a set of additional constraints must be considered. The perishability of fresh material, for example, has to be contemplated, together with other technical issues, such as a truck can only serve a single customer and two or more customers cannot be supplied using a truck in a single trip. RMCDP can be modelled as a mixed integer problem (with soft time window) and it can be optimally solved for small and medium sized variants of the problem. However, the objective cost and similar constraints are usually calculated using spatial distances (Euclidian distance) and similar approximate travel times are used. In this paper, we propose a more realistic method for calculating travel times based on real travel distances obtained from Google Maps API. The accurate travel time information is used as input for the RMCDP, to provide results that are more convincing. This paper compares RMCDP with two different objective functions; (i) spatial distance and (ii) real distance. This research will clarify the influence that the quality of this information has on the decision-making process and whether it is relevant to regard the accurate travel time to achieve a more realistic result.

A Novel Acoustic Liquid Level Determination Method for Coal Seam Gas Wells Based on Autocorrelation Analysis

In coal seam gas (CSG) wells, water is periodically removed from the wellbore in order to keep the bottom-hole flowing pressure at low levels, facilitating the desorption of methane gas from the coal bed. In order to calculate gas flow rate and further optimize well performance, it is necessary to accurately monitor the liquid level in real-time. This paper presents a novel method based on autocorrelation function (ACF) analysis for determining the liquid level in CSG wells under intense noise conditions. The method involves the calculation of the acoustic travel time in the annulus and processing the autocorrelation signal in order to extract the weak echo under high background noise. In contrast to previous works, the non-linear dependence of the acoustic velocity on temperature and pressure is taken into account. To locate the liquid level of a coal seam gas well the travel time is computed iteratively with the non-linear velocity model. Afterwards, the proposed method is validated using experimental laboratory investigations that have been developed for liquid level detection under two scenarios, representing the combination of low pressure, weak signal, and intense noise generated by gas flowing and leakage. By adopting an evaluation indicator called Crest Factor, the results have shown the superiority of the ACF-based method compared to Fourier filtering (FFT). In the two scenarios, the maximal measurement error from the proposed method was 0.34% and 0.50%, respectively. The latent periodic characteristic of the reflected signal can be extracted by the ACF-based method even when the noise is larger than 1.42 Pa, which is impossible for FFT-based de-noising. A case study focused on a specific CSG well is presented to illustrate the feasibility of the proposed approach, and also to demonstrate that signal processing with autocorrelation analysis can improve the sensitivity of the detection system.

3D traveltime computation for quasi-P-wave in orthorhombic media using dynamic programming

A fractured area, such as a fault area, usually induces orthorhombic anisotropy. Ignoring orthorhombic anisotropy may degrade the subsurface image by creating a well mistie and blurring the image. Traveltime computation is essential for many processing techniques, such as depth imaging and tomography. Solving the ray-tracing system and eikonal equation are two popular methods for traveltime computation in isotropic media. However, because the ray-tracing system becomes complex and the eikonal equation becomes highly nonlinear, their applications in orthorhombic media become complex. We have developed an alternative 3D traveltime computation method in orthorhombic media based on dynamic programming. To avoid solving the complex ray-tracing system and nonlinear eikonal equation, it adopts an explicitly expressed group velocity from the moveout approximation to describe the propagation of the wavepath and computes the traveltime by Fermat’s principle. Similar to depth extrapolation, it computes the traveltime from one depth to the next depth and does not suffer from a shadow zone. Besides, three strategies of traveltime computation are proposed to deal with different geologic scenarios. Because classic dynamic programming (i.e., the first strategy) computes all possible wavepaths (i.e., 24 wavepaths) across one spatial location, it may be computationally intensive. Based on the idea of wavefield decomposition (e.g., upgoing and downgoing), the second and third strategies simplify the traveltime computation and reduce the computational cost. Numerical examples on the vertical and tilted orthorhombic models indicate that the traveltime contour obtained by our method matches well with the wavefront extrapolated from the wave equation. Our method can be applied in depth imaging and tomography.

An accurate discontinuous Galerkin method for solving point-source Eikonal equation in 2-D heterogeneous anisotropic media

Accurate numerical computation of wave traveltimes in heterogeneous media is of major interest for a large range of applications in seismics, such as phase identification, data windowing, traveltime tomography and seismic imaging. A high level of precision is needed for traveltimes and their derivatives in applications which require quantities such as amplitude or take-off angle. Even more challenging is the anisotropic case, where the general Eikonal equation is a quartic in the derivatives of traveltimes. Despite their efficiency on Cartesian meshes, finite-difference solvers are inappropriate when dealing with unstructured meshes and irregular topographies. Moreover, reaching high orders of accuracy generally requires wide stencils and high additional computational load. To go beyond these limitations, we propose a discontinuous-finite-element-based strategy which has the following advantages: (1) the Hamiltonian formalism is general enough for handling the full anisotropic Eikonal equations; (2) the scheme is suitable for any desired high-order formulation or mixing of orders (p-adaptivity); (3) the solver is explicit whatever Hamiltonian is used (no need to find the roots of the quartic); (4) the use of unstructured meshes provides the flexibility for handling complex boundary geometries such as topographies (h-adaptivity) and radiation boundary conditions for mimicking an infinite medium. The point-source factorization principles are extended to this discontinuous Galerkin formulation. Extensive tests in smooth analytical media demonstrate the high accuracy of the method. Simulations in strongly heterogeneous media illustrate the solver robustness to realistic Earth-sciences-oriented applications.

Travel Time Cost for Private Car in Bumi Serpong Damai (BSD) City: Income and Mode Choice Approach

Abstract : Travel time cost is one of the primary aspects that considered, especially with respect to its economic impact. To account for the increment of road users, often travel time cost has to be highlighted and further investigated. One technique to compute travel time costs is by using travel time evaluation as a loss opportunity that used to produce traveling needs. The aim of the study is to compute travel time cost for the private transportation users in BSD City by employing two methodologies. Income approach is the first method, which requires only two factors to be computed (capital income and amount of annual working hour assuming that time used to produce one product as function of personal income). For mode choice approach, the method uses the travel time cost from the model to estimate the choices comparison from the specified mode traffic. In this model, comparisons of choices are assumed as a function of two independent variables; operational cost and time cost. Travel time cost is defined as the comparison between parameter of travel time cost against the operational cost. Additionally, the study adopted stated preference techniques surveys, which have been undertaken in BSD town area to derive the travel time cost. The survey focused on the private car passengers where background information collected were traveling distance, time of travel, journey characteristics, education level, employment and income of the respondents respectively. Subjects were asked to choose between different scenarios of mode choices. For income approach method, the results showed that the travel time cost for the private transport commuters was Rp 6,272 / hour/ person and Rp. 11,828 / hour / person by using mode choice approach. It was found that the value of time has increased as the income increases. Thus, value of time is significant in accounting for personal income.Keywords : Income, Mode Choice, Stated Preference

An efficient General Transit Feed Specification (GTFS) enabled algorithm for dynamic transit accessibility analysis.

The social functions of urbanized areas are highly dependent on and supported by the convenient access to public transportation systems, particularly for the less privileged populations who have restrained auto ownership. To accurately evaluate the public transit accessibility, it is critical to capture the spatiotemporal variation of transit services. This can be achieved by measuring the shortest paths or minimum travel time between origin-destination (OD) pairs at each time-of-day (e.g. every minute). In recent years, General Transit Feed Specification (GTFS) data has been gaining popularity for between-station travel time estimation due to its interoperability in spatiotemporal analytics. Many software packages, such as ArcGIS, have developed toolbox to enable the travel time estimation with GTFS. They perform reasonably well in calculating travel time between OD pairs for a specific time-of-day (e.g. 8:00 AM), yet can become computational inefficient and unpractical with the increase of data dimensions (e.g. all times-of-day and large network). In this paper, we introduce a new algorithm that is computationally elegant and mathematically efficient to address this issue. An open-source toolbox written in C++ is developed to implement the algorithm. We implemented the algorithm on City of St. George’s transit network to showcase the accessibility analysis enabled by the toolbox. The experimental evidence shows significant reduction on computational time. The proposed algorithm and toolbox presented is easily transferable to other transit networks to allow transit agencies and researchers perform high resolution transit performance analysis.

A theory of hydrodynamic tomography

A problem of the forecast of spatial distribution of effective filtration resistance of permeable layer based on tomography principles is under consideration. Theoretical grounds of hydrodynamic tomography have been elaborated based on the data of hydrodynamic interception and analysis of dynamics of the fixed point on the curve of pressure renewal. Calculating schemes have been designed implementing the algorithm of solving a direct problem for calculation of interval travel time of the fixed point between the boreholes system for the specified distribution of piezoconductivity coefficient, as a problem of travel time minimization along the rays. Algorithm for solving the inverse problem based on the principle of algebraic tomography has been designed. Initial data for realization of hydrodynamic tomography algorithm can be synthesized in addition to direct experiment from the operation model of a deposit trained on its development history.

A High-Resolution, Yet Scalable Framework for Transport Infrastructure Accessibility Based on Open Big Data

Throughout the last years, open big data has brought many challenges and revealed much potential for transportation research. In this study, we show how large open datasets can be used to accurately estimate the accessibility of transportation infrastructure for whole China, a scale unprecedented in the literature. Hundreds of airports and almost one thousand high-speed railway (HSR) stations serve the tremendously growing transportation demand. These access points to the transportation networks are not equivalently distributed throughout the country. Existing large-scale studies on transportation infrastructure accessibility focus on highly-aggregated forms of land-use area, with travel times from centroids of administrative regions. Other studies analyze spatially-constrained regions with very detailed data. In this study, we design and implement a fine-grained accessibility framework based on large open data sets, which allows us to estimate the accessibility based on grid cells with a resolution of less than one square kilometer. We automatize the computation of free-flow road travel times, as well as, the public transit times, from grid cells to infrastructure elements, by using a scalable routing framework. Based on our experiments, we find that the HSR network for China is much better accessible for the population than airports. Moreover, grid cells with a high population density are much better connected to the Chinese transportation networks than other grid cells. Our methodology is generic in that it can be applied on an even larger scale (whole planet) and with different points of interest.

Racial Differences in Geographic Access to Medical Care as Measured by Patient Report and Geographic Information Systems.

Geographic access-the travel burden required to reach medical care-is an important aspect of care. Studies, which typically rely on geographic information system (GIS) calculated travel times, have found some evidence of racial disparities in spatial access to care. However, the validity of these studies depends on the accuracy of travel times by patient race. To determine if there are racial differences when comparing patient-reported and GIS-calculated travel times. Data came from the Philadelphia Area Prostate Cancer Access Study (P Access), a cohort study of men diagnosed with localized prostate cancer. We conducted cross-sectional analysis of 2136 men using multivariable linear mixed-effects models to examine the effect of race on differences in patient-reported and GIS-calculated travel times to urology and radiation oncology cancer providers. Patient-reported travel times were, on an average, longer than GIS-calculated times. For urology practices, median patient-reported travel times were 12.7 minutes longer than GIS-calculated travel times for blacks versus 7.2 minutes longer for whites. After adjusting for potential confounders, including socioeconomic status and car access, the difference was significantly greater for black patients than white patients (2.0 min; 95% confidence interval, 0.58-3.44). GIS-calculated travel time may underestimate access to care, especially for black patients. Future studies that use GIS-calculated travel times to examine racial disparities in spatial access to care might consider including patient-reported travel times and controlling for factors that might affect the accuracy of GIS-calculated travel times.

A fast sweeping algorithm for accurate solution of the tilted transversely isotropic eikonal equation using factorization

Traveltime computation is essential for many seismic data processing applications and velocity analysis tools. High-resolution seismic imaging requires eikonal solvers to account for anisotropy whenever it significantly affects the seismic wave kinematics. Moreover, computation of auxiliary quantities, such as amplitude and take-off angle, relies on highly accurate traveltime solutions. However, the finite-difference-based eikonal solution for a point-source initial condition has upwind source singularity at the source position because the wavefront curvature is large near the source point. Therefore, all finite-difference solvers, even the high-order ones, show inaccuracies because the errors due to source-singularity spread from the source point to the whole computational domain. We address the source-singularity problem for tilted transversely isotropic (TTI) eikonal solvers using factorization. We solve a sequence of factored tilted elliptically anisotropic (TEA) eikonal equations iteratively, each time by updating the right-hand-side function. At each iteration, we factor the unknown TEA traveltime into two factors. One of the factors is specified analytically, such that the other factor is smooth in the source neighborhood. Through this iterative procedure, we obtain an accurate solution to the TTI eikonal equation. Numerical tests show significant improvement in accuracy due to factorization. The idea can be easily extended to compute accurate traveltimes for models with lower anisotropic symmetries, such as orthorhombic, monoclinic, or even triclinic media.

1D layered velocity models and microseismic event locations: synthetic examples for a case with a single linear receiver array

We discuss various aspects of 1D velocity-model building for application to microseismic data analysis. We generate simple synthetic example data using a widely used single linear array geometry. The synthetic data contain 30 sources with known locations for a reference model based on previous studies of the Barnett shale. We investigate several key factors that should be considered, including selection of the calibration technique, inclusion of a priori information such as lateral heterogeneity and parameter ranges, and choice of algorithm for travel time computations. For the source–receiver geometry considered here, hypocenter location errors (±6 m in X and ±12 m in Z) can result from differently calibrated models only and without including the errors in picked arrival times and polarization estimates. We find that the errors in hypocenter locations are reduced (±3 m in X and ±6 m in Z) when a model calibrated with multiple shots simultaneously is used. Using four different models (vertical fault, dipping layers, channels, and these effects combined), we demonstrate that systematic errors in hypocenter locations can result when a 1D layered model is used in lieu of a laterally heterogeneous subsurface. Finally, we show that event locations from a velocity model calibrated using direct-arrival times are more stable than from a model calibrated with first-arrival times.

Evaluating the Evacuation and Rescue Capabilities of Urban Open Space from a Land Use Perspective: A Case Study in Wuhan, China

This study proposes an innovative integrated method for evaluating the evacuation and rescue capabilities of open spaces through a case study in Wuhan, China. A dual-scenario network analysis model was set up to calculate travel time among communities, open spaces, and rescue facilities during peak and non-peak hours. The distribution of traffic flow was derived on the basis of a gravity model and used to construct supply-demand indexes (SDIs). SDIs such as evacuation (ESDI), rescue (RSDI), and comprehensive SDIs (CSDI) were used to evaluate the suitability of open space locations. This study drew five major findings as follows: (1) ESDI, RSDI, and CSDI can effectively evaluate the spatial suitability of open spaces when these SDIs are integrated with the gravity model. (2) The quadrant distribution analysis of ESDI can be an effective method for determining the reasons for the change in values in the two traffic scenarios and for helping planners in adjusting their policies to enhance the capability of an area. (3) The impact of the different β values on SDIs can show positive, negative, and inconspicuous correlations with large, moderate, and minimal variations, respectively. (4) The analysis of the supply-demand relationship of open spaces in Wuhan indicates a spatial mismatch in comprehensive evacuation and rescue capacities. (5) Traffic congestion can be a significant impact factor on evacuation and rescue capabilities but not on comprehensive capability.

Manoeuvres in manual person-to-parts order picking systems: Is there a significant influence on travel time and metabolic rates?

In current planning models for travel time calculation in manual person-to-parts order picking systems it is assumed that the order picker travels at constant velocity through the warehouse. Curves and turn manoeuvres that are necessary for changing the aisles are neglected in operating strategies so far. For order pickers that use a cart for transporting the items a more realistic approach would be to consider additional time for those manoeuvres due to a reduced gait velocity as well as additional physical exposure due to higher pushing/pulling forces. The paper at hand investigates if those influences should be further deliberated in travel time calculation and in ergonomic evaluation by the means of a simulation study. First results show that especially for small warehouse dimensions and random storage assignment policies warehouse operators could prefer heuristic routing policies (combined/composite/traversal) instead of the optimal (minimal travel distance) policy when taking curves/turn manoeuvers into account.

Comparison of Full Wavefield Synthetics with Frequency-Dependent Traveltimes Calculated Using Wavelength-Dependent Velocity Smoothing

Ray theory-based traveltime calculation that assumes infinitely high frequency wave propagation is likely to be invalid in the near-surface (upper tens of meters) due to the relatively large seismic wavelength compared with the total travel path lengths and the scale of the near-surface velocity heterogeneities. The wavelength-dependent velocity smoothing (WDVS) algorithm calculates a frequency-dependent, first-arrival traveltime by assuming that using a wavelength-smoothed velocity model and conventional ray theory is equivalent to using the original unsmoothed model and a frequency-dependent calculation. This paper presents comparisons of WDVS-calculated traveltimes with band-limited full wavefield synthetics including the results from 1) different velocity models, 2) different frequency spectra, 3) different values of a free parameter in the WDVS algorithm, and 4) different levels of added noise to the synthetics. The results show that WDVS calculates frequency-dependent traveltimes that are generally consistent with the first arrivals from band-limited full wavefield synthetics. Compared to infinite-frequency traveltimes calculated using conventional ray theory, the WDVS frequency-dependent traveltimes are more consistent with the first arrivals picked from full wavefield synthetics in terms of absolute time and trace-to-trace variation. The results support the use of WDVS as the forward modeling component of a tomographic inversion method, or any seismic method that involves modeling first-arrival traveltimes.