Travel Time Model Research Articles

PS-wave processing and S-wave velocity inversion of OBS data from Northern South China Sea

Abstract It is very important to convert seismic data from the time domain to the depth domain so we can explain the geological information more obviously. This paper provides a method for time to depth conversion. PS-wave data from an Ocean bottom seismograph (OBS) survey of the Northern South China Sea was processed through the separation of PP and PS wavefields and the rotation of horizontal components. An inverse modeling of travel times was performed for the determination of the S-wave velocity (Vs). The migration section of the single channel seismic data was used to define the model horizons and to help control their geometry. Wide angle hydrophone data of OBS were used to determine the P-wave travel times and wide angle horizontal component data of OBS were used to determine the PS-wave travel times. The chosen travel times from various shots were inverted for P- and S-wave interval velocities using RayInvr , which calculates theoretical travel times via ray tracing. Damped least squares optimization is performed to fine-tune the fits between observed and calculated travel times. The achieved trends of the P-wave velocity (Vp) and Vs curves are similar and the velocity increases in the layer where gas hydrates are present.

Research on the Link Travel Time Model for High Occupancy Vehicle Lanes of Freeways

Due to the distinctive characteristics of high occupancy vehicles (HOVs), the existing link travel time models are not suitable for HOV lanes on freeway. The objective of this research is to provide a link travel time model for HOV lanes. Road and traffic data were collected from California Department of Transportation and dealt with using Highway Capacity Manual. By Bureau of Public Roads function, the link travel time model for freeway HOV lanes was established, considering both flow- to-capacity ratios on HOV lane and the adjacent mainline lane. Statistical methods including Pearson, Kendall and Spearman correlations, stepwise method were used for coefficient calibration. Through significance test and error test, the model effectiveness was demonstrated. The model proposed in this research can be applied to speed prediction, traffic assignment and some relevant fields.

Determining the location of suitable satellite centres for chronic kidney disease (CKD) treatment within Edo state, Nigeria

The study investigates the accessibility to healthcare for chronic kidney disease (CKD) patients within Edo state, Nigeria. This was done with the aim of determining the efficiency of the health service available to CKD patients in the area. It involves the use of travel time models to explore the efficiency of the structure of healthcare for CKD patients within the study area as well as evaluate potential scenarios that could improve the CKD healthcare service in the area. Therefore, the study attempted to identify a suitable method of remotely identifying potential locations that can be suitable for providing healthcare for CKD patients at the earlier stages of the disease. In order to minimise the distance between CKD patients and CKD healthcare facilities, there was the need to carry out a location–allocation analysis in order to locate satellite CKD centres close to population centres for each local government area, which would serve as population thresholds for the satellite CKD facilities. This objective was based on the argument that people tend to attend nearby health facilities than attend those that are farther away. The results indicated that the current healthcare structure was not efficient and identified potential locations among the available health centres within the state that would help reduce accessibility issues relating to the number of CKD patients that are being treated within the state.

Evaluating order throughput time with variable time window batching

Given increased pressure to provide short delivery times, minimising customer order throughput time is a very important objective in warehousing operations. There are many factors that may affect the performance of an order picking system, such as layout of the warehouse, the storage strategy, the routing policy, the zoning method and the batching policy. In this study, we propose a simple travel time model and analyse the effect of order batching on the expected customer order throughput time with variable time window batching. In addition, we discussed the impact of some parameters on the batch size and the expected customer order throughput time. In the practice of Wuhan Dong Hon Logistics co. Ltd, the storage rack in the warehouse has two levels: the low storage level and the high storage level. These two levels are visited by pickers and forklifts, respectively. The classification improves the performance of order picking. In this study, we build the model based on this practice.

Changes in population evacuation potential for tsunami hazards in Seward, Alaska, since the 1964 Good Friday earthquake

Pedestrian evacuation modeling for tsunami hazards typically focuses on current land-cover conditions and population distributions. To examine how post-disaster redevelopment may influence the evacuation potential of at-risk populations to future threats, we modeled pedestrian travel times to safety in Seward, Alaska, based on conditions before the 1964 Good Friday earthquake and tsunami disaster and on modern conditions. Anisotropic, path distance modeling is conducted to estimate travel times to safety during the 1964 event and in modern Seward, and results are merged with various population data, including the location and number of residents, employees, public venues, and dependent care facilities. Results suggest that modeled travel time estimates conform well to the fatality patterns of the 1964 event and that evacuation travel times have increased in modern Seward due to the relocation and expansion of port and harbor facilities after the disaster. The majority of individuals threatened by tsunamis today in Seward are employee, customer, and tourist populations, rather than residents in their homes. Modern evacuation travel times to safety for the majority of the region are less than wave arrival times for future tectonic tsunamis but greater than arrival times for landslide-related tsunamis. Evacuation travel times will likely be higher in the winter time, when the presence of snow may constrain evacuations to roads.

Diffraction traveltime approximation for TI media with an inhomogeneous background

Diffractions in seismic data contain valuable information that can help improve our modeling capability for better imaging of the subsurface. They are especially useful for anisotropic media because they inherently possess a wide range of dips necessary to resolve the angular dependence of velocity. We develop a scheme for diffraction traveltime computations based on perturbation of the anellipticity anisotropy parameter for transversely isotropic media with tilted axis of symmetry (TTI). The expansion, therefore, uses an elliptically anisotropic medium with tilt as the background model. This formulation has advantages on two fronts: first, it alleviates the computational complexity associated with solving the TTI eikonal equation, and second, it provides a mechanism to scan for the best-fitting anellipticity parameter [Formula: see text] without the need for repetitive modeling of traveltimes, because the traveltime coefficients of the expansion are independent of the perturbed parameter [Formula: see text]. The accuracy of such an expansion is further enhanced by the use of Shanks transform. We established the effectiveness of the proposed formulation with tests on a homogeneous TTI model and complex media such as the Marmousi and BP models.

Study of the western edge of the African Large Low Shear Velocity Province

It is well established that there is a large low shear velocity province (LLSVP) in the lowermost mantle beneath Africa, extending from beneath the southeastern Atlantic Ocean to the southwestern Indian Ocean. The detailed 3‐D geometry of the LLSVP is crucial to the understanding of how this prominent lower mantle feature developed and evolved. Most studies have concentrated on mapping the southern and eastern edges of African LLSVP using the Kaapvaal array at South Africa. Here we use data from recently deployed arrays in the western Mediterranean to study its northwestern edge and evaluate the sharpness of its boundaries. Travel time and waveform modeling of S and SKS phases suggest the existence of sharp low velocity anomalies in the lowermost mantle beneath the eastern Atlantic Ocean, which agrees with global tomography models. However, the S‐SKS differential times vary up to 6 s across the array. To match the large travel time variations and waveforms, the existence of a slow velocity structure with a sharp top is required. The structure has a 3.5% reduction in shear wave velocity and a height of ∼600 km above the core‐mantle boundary, which is lower in topography than the southern and eastern part of the African LLSVP. Further 3‐D synthetic waveforms and modeling calculations demonstrate the existence of these sharp boundaries for the northwestern portion of the African LLSVP. The strong lateral variation in both travel times and waveforms suggests that this part of the African LLSVP may be as complex as the mid‐Pacific LLSVP. To explain the observed sharp top and large dome‐like structure, a thermochemical origin of the African LLSVP is supported.

Modelling travel time distribution under various uncertainties on Hanshin expressway of Japan

Studying travel time distribution or variability in travel time is very much useful in travel time reliability studies of transportation system. The properties of this distribution are described by various uncertainties which are derived from supply side, demand side and other external factors of any road network. Present study investigates the development of stochastic response surface of travel time variation under uncertain factors of traffic volume and intensity of rain fall by using Stochastic Response Surface Method (SRSM). This model was applied to a section of Kobe Route (Nishnomiya to Awaza), Hanshin expressway, Japan. Besides hourly traffic volume data, incident data for the entire year 2006 were collected and multiple linear regression analysis for entire year data was initially performed to know the functional and significance relation between the input and output variable. Further SRSM analysis has been carried out for working days data. Results shows that travel time distribution obtained using SRSM model is better than distribution obtained by the regression model. It was observed from the results that SRSM model is efficient for analyzing the stochastic relation between the response variable and uncertain explanatory variables.

Modelling travel time in urban networks: comparable measures for private car and public transport

Analysing the accessibility disparity between different travel modes is recognised as an efficient way to assess the environmental and social sustainability of transport and land use arrangements. Travel times by different travel modes form an essential part of such an analysis. This paper aims to assess the comparability of different methods for calculating travel time by different travel modes. First, we briefly review the methods used in previous studies and identify different typical approaches, which we then compare. We use three computational models respectively for car and public transport (PT), implemented in our case study area, the capital region of Finland. In the car models, (1) the simple model ignores congestion and parking in travel time calculation; (2) the intermediate car model accounts for congestion but ignores parking; and (3) the more advanced car model takes into account all parts of the journey, including congestion and parking. For PT, (1) the simple model accounts for transit routes but ignores schedules; (2) the intermediate model incorporates schedule data in a simplistic way; and (3) the more advanced model adopts a door-to-door approach where true schedules (incl. congestion) and realistic route combinations are accounted for. Our results show that absolute differences in car and PT travel times are notable in the Greater Helsinki area, no matter which models are used for comparison. Modal travel time disparity appears smallest in the city centre area. We conclude that using conceptually corresponding models for car and PT travel time calculations is the key to achieving a reliable analysis of modal accessibility disparity. A door-to-door approach in travel time calculations (adopted in the most advanced models) also makes the results truly comparable in absolute terms. Finally, the more advanced the applied methods are, the more data hungry the analysis is. Here, recent developments in open data policies among urban transport data producers become very helpful.

Computation of traveltime covariances based on stochastic models of velocity heterogeneity

SUMMARY We formulate the error covariance for calculated seismic traveltimes (traveltime covariance) along any two propagation paths as a double integral of a covariance function describing velocity-model error (velocity covariance) with sensitivity distributions for the paths. Two numerical techniques are presented for evaluating the traveltime covariance matrix for multiple paths. The first technique evaluates the covariance matrix directly. The second evaluates the inverse of the covariance matrix summed with a covariance matrix for observational errors, as is utilized in event locators. Our approach takes the velocity covariance to be the Green’s function of a differential operator, which can be specified in terms of physically meaningful parameters, such as spatially variable velocity variance and correlation lengths. Our numerical algorithms reduce to solving finite-difference equations based on the differential operator. As a demonstration, we compute traveltime covariance using ray-based sensitivity distributions and a suite of depth-dependent models of velocity covariance. We compare our theoretical calculationstoempiricalestimatesoftraveltimevarianceversusevent-stationdistance,derived from observed residuals relative to the ‘ak135’ velocity model. Our calculations predict and explain some key features of the distance dependence of observed residual statistics, such as abrupt changes in variance at crossover points separating branches of the first-arrival traveltime curve. We find that the observed traveltime variances in the distance range 2 ◦ ‐33 ◦ are well matched by assuming a velocity standard deviation (relative to ‘ak135’) of >10 percent in the crust and decaying from ∼2 percent in the uppermost mantle to near 0 percent below the 410-km discontinuity. These variance estimates hold over a wide range of assumed correlation lengths of velocity error, which are not well constrained by traveltime variance observations. By providing a physical understanding of traveltime covariance, our approach may help in the development of improved methods for locating seismic events, for estimating path-specific corrections to baseline traveltime models, and for constraining the statistics of velocity variations in the Earth.

Multimodal accessibility modeling from coarse transportation networks in Africa

Accessibility is a key driving factor for economic development, social welfare, resources management, and land use planning. In many studies, modeling accessibility relies on proxy variables such as estimated travel time to selected destinations. In developing countries, estimating the travel time is hindered by scarce information about the transportation network, making it necessary to take into account off-network travel coupled with considerations of multimodal options available within the existing network. This research proposes such a hybrid approach that computes the travel time to selected destinations by optimizing together a fully modeled multimodal network and off-network travel. The model was applied in a region around Kisangani located in northeastern Democratic Republic of the Congo. Travel times to Kisangani from the hybrid approach were found to be in close agreement with field-based information (R 2 = 0.98). The developed approach also proved to better support real-world transportation constraints (such as transfer points between travel modes or barriers) than cost-distance-based travel-time modeling. Demonstration results from the hybrid approach highlight the potential for impact assessment of road construction or rehabilitation, development of secondary towns or markets, and for land use planning in general.

A Heuristic Algorithm to Study the Influence of Road Preference on Network Capacity

In this study, an algorithm was proposed to study the influence of road preference on the network capacity in urban transportation system. Of particular interest is to model the discrete choice model with respect to the road preference and the travel time. New formulations are presented in terms of the multi-objective road preference modeling and the travel time modeling for multi vehicle types. Compared with existing techniques, an improved heuristic method is put forward to explore the network capacity.

Racial disparities in travel time to radiotherapy facilities in the Atlanta metropolitan area

Low-income women with breast cancer who rely on public transportation may have difficulty in completing recommended radiation therapy due to inadequate access to radiation facilities. Using a geographic information system (GIS) and network analysis we quantified spatial accessibility to radiation treatment facilities in the Atlanta, Georgia metropolitan area. We built a transportation network model that included all bus and rail routes and stops, system transfers and walk and wait times experienced by public transportation system travelers. We also built a private transportation network to model travel times by automobile. We calculated travel times to radiation therapy facilities via public and private transportation from a population-weighted center of each census tract located within the study area. We broadly grouped the tracts by low, medium and high household access to a private vehicle and by race. Facility service areas were created using the network model to map the extent of areal coverage at specified travel times (30, 45 and 60 min) for both public and private modes of transportation. The median public transportation travel time to the nearest radiotherapy facility was 56 min vs. approximately 8 min by private vehicle. We found that majority black census tracts had longer public transportation travel times than white tracts across all categories of vehicle access and that 39% of women in the study area had longer than 1 h of public transportation travel time to the nearest facility. In addition, service area analyses identified locations where the travel time barriers are the greatest. Spatial inaccessibility, especially for women who must use public transportation, is one of the barriers they face in receiving optimal treatment.

Crustal structure of the northern margin of the North China Craton and adjacent region from SinoProbe02 North China seismic WAR/R experiment

Abstract The SinoProbe02 North China seismic experiment consisted of three seismic recording efforts along a 450 km long profile. The profile extended from northwest of Beijing, across the northern margin of the North China Craton (NCC), and across the southeastern portion of the Central Asian Orogenic Belt (CAOB) to the Solonker suture zone. We processed, analyzed, and modeled the data collected during a wide-angle reflection and refraction effort. The recording of seismic waves from 8 explosions was conducted in 4 deployments of 300 Texan recorders with station spacings of 1–1.5 km. The P-wave field provided good quality data for most of the profile. Arrivals of refracted and reflected waves from sediments and basement (Pg), intracrustal phases (PcP, PlP), and the Moho (PmP, Pn) were typically observed. Travel time modeling was done layer-by-layer using the top to bottom approach and was constrained by a coincident deep reflection seismic profile. The initial velocity model was altered by trial and error, and the forward model was updated by damped least-squares inversion. In our modeling, calculated travel times fit observed arrivals for all 1439 traces with an average RMS error of 0.113 s. The final 2-D P-wave velocity model contains many features of tectonic significance: (1) the velocity structure varies significantly from the NCC to the CAOB; (2) thicker crust appears beneath the Yinshan–Yanshan belt and was probably generated by compression in the early Jurassic and modified during the craton's destabilization and extension; the flat and relatively shallow Moho in the CAOB may be attributed to the extension; (3) strong velocity variations beneath the Bainaimiao arc and Ondor Sum subduction accretion complex indicate that multiple pulses of magmatism occurred during the complex tectonic evolution of this area.

On the suboptimality of full turnover-based storage

Full turnover-based storage has been widely claimed to outperform the commonly used ABC class-based storage policy in terms of the resulting storage and retrieval travel time. In the first paper describing the full turnover-based policy, simultaneously implicitly assuming shared storage (that is to say storage space that can be used by other products once the original product's inventory is depleted) was modelled, since no specific space was reserved to store the maximum inventory of a product. However, full turnover-based storage is a dedicated storage policy where the storage space allocated to one product must be able to accommodate its maximum inventory level. Since then, many authors have cited the results of the full turnover-based storage policy while often overlooking its incompatible shared-storage assumption. This paper adapts classic travel time models to accommodate full turnover-based dedicated storage. We consider different warehousing system configurations such as square-in-time (SIT) and non-SIT racks, and speed acceleration and deceleration effects to calculate the storage/retrieval (S/R) machine's travel time. Surprisingly, but in line with practice, the results of the adapted travel time models show that random and class-based storage normally outperform full turnover-based storage.

Mw 8.6 Sumatran earthquake of 11 April 2012: Rare seaward expression of oblique subduction

The magnitude 8.6 and 8.2 earthquakes off northwestern Sumatra on 11 April 2012 generated small tsunami waves that were recorded by stations around the Indian Ocean. Combining differential travel-time modeling of tsunami waves with results from back projection of seismic data reveals a complex source with a significant trench-parallel component. The oblique plate convergence indicates that ∼20–50 m of trench-parallel displacement could have accumulated since the last megathrust earthquake, only part of which has been taken up by the Great Sumatran fault. This suggests that the remaining trench-parallel motion was released during the magnitude 8.6 earthquake on 11 April 2012 within the subducting plate. The magnitude 8.6 earthquake is interpreted to be a result of oblique subduction as well as a reduction in normal stress due to the occurrence of the Sumatra-Andaman earthquake in 2004.

Development of Recurrent Neural Network Considering Temporal‐Spatial Input Dynamics for Freeway Travel Time Modeling

Abstract: The artificial neural network (ANN) is one advance approach to freeway travel time prediction. Various studies using different inputs have come to no consensus on the effects of input selections. In addition, very little discussion has been made on the temporal–spatial aspect of the ANN travel time prediction process. In this study, we employ an ANN ensemble technique to analyze the effects of various input settings on the ANN prediction performances. Volume, occupancy, and speed are used as inputs to predict travel times. The predictions are then compared against the travel times collected from the toll collection system in Houston. The results show speed or occupancy measured at the segment of interest may be used as sole input to produce acceptable predictions, but all three variables together tend to yield the best prediction results. The inclusion of inputs from both upstream and downstream segments is statistically better than using only the inputs from current segment. It also appears that the magnitude of prevailing segment travel time can be used as a guideline to set up temporal input delays for better prediction accuracies. The evaluation of spatiotemporal input interactions reveals that past information on downstream and current segments is useful in improving prediction accuracy whereas past inputs from the upstream location do not provide as much constructive information. Finally, a variant of the state‐space model (SSNN), namely time‐delayed state‐space neural network (TDSSNN), is proposed and compared against other popular ANN models. The comparison shows that the TDSSNN outperforms other networks and remains very comparable with the SSNN. Future research is needed to analyze TDSSNN's ability in corridor prediction settings.

Travel Time Model for Right-Turning Vehicles of Secondary Street at Unsignalized Intersections

The travel time of right-turning vehicles on secondary street at unsignalized intersection is discussed in this paper. Under the assumption that the major-street through vehicles’ headway follows Erlang distribution and secondary-street right-turning vehicles’ headway follows Poisson distribution. The right-turning vehicles travel time model is established on the basis of gap theory and M/G/1 queue theory. Comparison is done with the common model based on the assumption that the major-street vehicles’ headway follows Poisson distribution. An intersection is selected to verify each model. The results show that the model established in this paper has stronger applicability, and its most relative error is less than 15%. In addition, the sensitivity analysis has been done. The results show that right-turning flow rate and major-street flow rate have a significant impact on the travel time. Hence, the methodology for travel time of right-turning vehicles at unsignalized intersection proposed in this paper is effective and applicable.

Travel Time Modeling and Simulation of a Mobile Racks Automated Storage/Retrieval System

AS/RS systems are devices designed for automated storage and retrieval of parts and items in manufacturing, distribution, retail, wholesale and institutions. This paper consists in studying a storage system with Mobil racks (M-AS/RS) which are a variation of the multi aisles AS/RS. This mobile storage system is composed of racks moving laterally on rails so that one can open an aisle between any two adjacent racks, it makes it possible to optimize the use of space; the characteristic of these systems is that the aisles of service appear only when one operation of storage or retrieval is envisaged in the corresponding racks. One of the most important criteria of performances of these systems is the average cycle time of the storage/Retrieval machine. In this paper our interest is concerned with the mathematical modeling of M-AS/RS system. We presented a closed form analytical expression allowing an approximate calculation of the travel time of a Mobil Racks-AS/RS. This expression was compared with simulation results and an exact discrete expression developed earlier by one of the authors.

Empirical Validation of Three Macroscopic Dynamic Network Loading Models

The macroscopic dynamic network loading (DNL) model is the essential component to perform dynamic traffic assignment (DTA). The popular DNL models widely used in literature of DTA are Point-Queue (PQ) and Linear Travel Time (LTT) models because they fulfil of all the required desirable properties and require lesser computational cost. The Divided Linear Travel Time (DLT) model is presented as a variant model to overcome theoretical deficiencies found in PQ and LTT models. Literature of DTA focused on theoretical properties of these models; however, empirical validation of these models with real traffic data is scarce. This study prime objective is to validate PQ, LTT and DLT models with collected data in terms of inflow and outflow profiles from simultaneous recorded videos at both ends of the link under various conditions of link volume. The obtained results indicated that models are not able to replicate observed travel time profiles as Root Mean Square Error (RMSE) values are quite higher in almost all analysed cases. Investigation of properties such as FIFO and heterogeneity in transport modes using a fastest lane experiment indicated that model predictions are better when extent of these measures were lower. It implies that incorporation of these notions in future models are means to further progress in this direction.