In this thesis, fluid flow and solute transport in heterogeneous aquifers and particularly in frac-tured rock have been investigated using Lagrangian Stochastic Advective-Reaction (LaSAR) framework. The heterogeneity of the aquifer structure or fracture configuration, as well as the various reaction/retention processes have been considered in the modelling approach. Advection and retention processes are considered to be the dominant transport processes. Monte-Carlo simulation results for transport of nonreactive tracers in 2D generic heterogeneous aquifers indicate that the travel time τ can be well approximated by a lognormal distribution up to a relative high degree of heterogeneity of the aquifers. Comparison between the Monte-Carlo simulation results and the results of first-order approximation reveals that the analytical solutions of the statistical moments of τ are valid only when the variability of the aquifer properties is small. For reactive tracers, Monte-Carlo simulations have been conducted by accounting for spatial variability of both hydraulic conductivity and one sorption parameter simultaneously. The simulation results indicate that the reaction flow path μ is a nonlinear function of distance for shorter distance, linear function for longer distance, and also that μ and τ are well correlated over the considered parameter range. The parameter β, which is purely determined by the flow condi-tions, quantifies the hydrodynamic control of retention processes for transport of tracers in frac-tures. Numerical simulations have been performed to study the statistical properties of the pa-rameter β, travel time τ and flow rate Q in a single heterogeneous fracture and in a sequence of fractures. The results of Monte-Carlo simulations indicate that the parameter β and τ are corre-lated with a power-law relationship β ∼ τm. The correlation between β and the flow rate Q have also been studied and an inverse power-law relationship β ∼ Q-m is proposed. The establishment of these relationships provides a link between the parameter β and measurable parameters τ (or Q). The LaSAR approach has been applied for prediction, evaluation and interpretation of the results of a number of tracer tests (TRUE-1, TRUE Block Scale and TRUE Block Scale Continuation) conducted by SKB at the Äspö site for tracer transport in fractures. The breakthrough curves may be predicted reasonably well, provided that the retention parameters, boundary conditions and hydraulic properties of the domain are given. The evaluation of TRUE tests indicates that the retention occurs mainly in the rim zone on site characterization time scales, while on the per-formance assessment time scale, diffusion and sorption in the unaltered rock matrix are likely to become dominant retention mechanisms. / QC 20100624

Travel demand forecasting is essential for many decisions, such as infrastructure investments and policy measures. Traditionally travel demand modelling has considered trip frequency, mode, destination and route choice. This thesis considers two other choice dimensions, hypothesised to have implications for travel demand forecasting. The first part investigates how the increased possibilities to overcome space that ICT (information and communication technology) provides, can be integrated in travel demand forecasting models. We find that possibilities of modelling substitution effects are limited, irrespective of data source and modelling approach. Telecommuting explains, however, a very small part of variation in work trip frequency. It is therefore not urgent to include effects from telecommuting in travel demand forecasting. The results indicate that telecommuting is a privilege for certain groups of employees, and we therefore expect that negative attitudes from management, job suitability and lack of equipment are important obstacles. We find also that company benefits can be obtained from telecommuting. No evidences that telecommuting gives rise to urban sprawl is, however, found. Hence, there is ground for promoting telecommuting from a societal, individual and company perspective. The second part develops a departure time choice model in a mixed logit framework. This model explains how travellers trade-off travel time, travel time variability, monetary and scheduling costs, when choosing departure time. We explicitly account for correlation in unobserved heterogeneity over repeated SP choices, which was fundamental for accurate estimation of the substitution pattern. Temporal constraints at destination are found to mainly restrict late arrival. Constraints at origin mainly restrict early departure. Sensitivity to travel time uncertainty depends on trip type and intended arrival time. Given appropriate input data and a calibrated dynamic assignment model, the model can be applied to forecast peak-spreading effects in congested networks. Combined stated preference (SP) and revealed preference (RP) data is used, which has provided an opportunity to compare observed and stated behaviour. Such analysis has previously not been carried out and indicates that there are systematic differences in RP and SP data. / QC 20100825

I storstadsregionerna blir trafikläget allt mer ansträngt för vart år som går. Inflyttningen fortsätter i oförändrad takt och fler människor måste försöka samsas om samma utrymme. Situationen på vägarna börjar bli ohållbar och det måste till att dessa problem löses snart för att utvecklingen i regionerna inte ska stagnera. Möjligheter för ytterligare utbyignationer finns dock i en begränsad grad och man måste börja se till andra lösningar. Inom området för intelligenta transportsystem(ITS) erbjuds många nya tillämpningar där man med ny teknik försöker hitta lösningar till dagens trafikproblem. Ett led i detta är att samla in och distribuera information om restider på vägarna, för att försöka fördela trafiken mer jämt över hela vägnätet. Det finns olika metoder för att hämta in den här typen av information, men den här rapporten fokuserar sig vid att beskriva system baserat på Floating Car Data(FCD). Arbetet som beskrivs i rapporten har i huvudsak analyserat fyra olika restidsuppskattnings-modeller och jämfört dessa med varandra. Modellerna baserar sina beräkningar på observationer från oidentifierade fordon, dvs att observationerna inte har någon identitetsstämpel som kan kopplas till ett specifikt fordon. Två av modellerna betraktar länkarna som en helhet och utför beräkningarna med detta som grund, medan de två andra delar upp varje länk i mindre segment vilket skapar möjlighet för en större noggrannhet. Modellerna testades inledningsvis på simulerad data baserat på trafikmätningar i Göteborgstrakten. Alla beräkningar begränsades ner till länknivå och inte hela vägnät. Detta p.g.a. att det initialt var för komplicerat att skapa en map- matchingmetod som skulle krävas för genomföra beräkningar på olika länkar samtidigt. Efter genomförda tester på simulerad data prövades modellerna även på en reella datamängd hämtad från projektet Probe i Stockholmsområdet. Resultaten från de utförda testerna visar på att det inte skiljer sig nämnvärt i restidsuppskattningarna mellan de olika modellerna. Sträckan som valdes att analyseras i de simulerade fallen, påverkades inte av några större störningar eller flödesvariationer. Det resulterade i att alla modellerna genererade likvärdiga restider. Även i fallet med den reella datamängden, som innehöll större flödesvariationer över tiden, kunde de olika modellernas uppskattningar inte skiljas åt nämnvärt. Slutsatsen är att trafiken i allmänhet inte har så kraftiga förändringar i flödet över tiden, att det krävs särskilt avancerade modeller för att beräkna restider på länknivå. I alla fall inte om man bortser från incidenter. De framräknade restiderna och den information som dessa ger, bör främst användas för direkt trafikstyrning för att uppnå önskat resultat. Människor förlitar sig mer till sina egna erfarenheter i kända områden, så information av den här typen lämpar sig mer som hjälpmedel för den enskilde individen vid resor i okänd trafik.

Conditioning geologic models to production data and assessment of uncertainty is generally done in a Bayesian framework. The current Bayesian approach suffers from three major limitations that make it impractical for field-scale applications. These are: first, the CPU time scaling behavior of the Bayesian inverse problem using the modified Gauss-Newton algorithm with full covariance as regularization behaves quadratically with increasing model size; second, the sensitivity calculation using finite difference as the forward model depends upon the number of model parameters or the number of data points; and third, the high CPU time and memory required for covariance matrix calculation. Different attempts were used to alleviate the third limitation by using analytically-derived stencil, but these are limited to the exponential models only. We propose a fast and robust adaptation of the Bayesian formulation for inverse modeling that overcomes many of the current limitations. First, we use a commercial finite difference simulator, ECLIPSE, as a forward model, which is general and can account for complex physical behavior that dominates most field applications. Second, the production data misfit is represented by a single generalized travel time misfit per well, thus effectively reducing the number of data points into one per well and ensuring the matching of the entire production history. Third, we use both the adjoint method and streamline-based sensitivity method for sensitivity calculations. The adjoint method depends on the number of wells integrated, and generally is of an order of magnitude less than the number of data points or the model parameters. The streamline method is more efficient and faster as it requires only one simulation run per iteration regardless of the number of model parameters or the data points. Fourth, for solving the inverse problem, we utilize an iterative sparse matrix solver, LSQR, along with an approximation of the square root of the inverse of the covariance calculated using a numerically-derived stencil, which is broadly applicable to a wide class of covariance models. Our proposed approach is computationally efficient and, more importantly, the CPU time scales linearly with respect to model size. This makes automatic history matching and uncertainty assessment using a Bayesian framework more feasible for large-scale applications. We demonstrate the power and utility of our approach using synthetic cases and a field example. The field example is from Goldsmith San Andres Unit in West Texas, where we matched 20 years of production history and generated multiple realizations using the Randomized Maximum Likelihood method for uncertainty assessment. Both the adjoint method and the streamline-based sensitivity method are used to illustrate the broad applicability of our approach.

An arterial traffic control system influences the travel time characteristics of a corridor, including the average corridor travel time and the travel time reliability. However, reliability measures have typically been outside of the focus of arterial control system performance evaluation studies. To assess the effectiveness of arterial traffic control performance evaluation studies are normally limited to average measures of travel time, speed, or delay. As an advanced traffic management system, adaptive traffic control has been developed to address real time demand variability. Thus, an evaluation of the adaptive traffic control system based on reliability may be as important as evaluation based on average travel time or delay. In addition, arterial control systems may also affect the performance of side street traffic as well as arterial corridor traffic. The performance of side street traffic is another measure that should be used in the assessment of the effectiveness of any arterial traffic control system. Finally, an arterial's operational performance often changes throughout a day and over the arterial length. Thus, a system-wide measure that reflects the range of observed operations is needed to thoroughly assess the performance. Given these issues the goal of this research is the development of procedures to evaluate adaptive traffic control's effect on arterial characteristics such as travel time distribution, reliability, side street performance, and system-wide performance. The developed procedures were applied to the evaluation of an adaptive traffic control system, SCATS (Sydney Coordinated Adaptive Traffic System) in Cobb County, Georgia that replaced a semi-actuated coordinated control system. After the procedures were applied, it was found that SCATS produced a less extreme shape of travel time distribution, possibly due to the adaptive feature, but that it did not make statistically significant changes in the selected overall analysis measures. Also, it was found that the results of the performance evaluation can vary depending on the measures selected or the study period and location.

<p>I storstadsregionerna blir trafikläget allt mer ansträngt för vart år som går. Inflyttningen fortsätter i oförändrad takt och fler människor måste försöka samsas om samma utrymme. Situationen på vägarna börjar bli ohållbar och det måste till att dessa problem löses snart för att utvecklingen i regionerna inte ska stagnera. Möjligheter för ytterligare utbyignationer finns dock i en begränsad grad och man måste börja se till andra lösningar. Inom området för intelligenta transportsystem(ITS) erbjuds många nya tillämpningar där man med ny teknik försöker hitta lösningar till dagens trafikproblem. Ett led i detta är att samla in och distribuera information om restider på vägarna, för att försöka fördela trafiken mer jämt över hela vägnätet. Det finns olika metoder för att hämta in den här typen av information, men den här rapporten fokuserar sig vid att beskriva system baserat på Floating Car Data(FCD). </p><p>Arbetet som beskrivs i rapporten har i huvudsak analyserat fyra olika restidsuppskattnings-modeller och jämfört dessa med varandra. Modellerna baserar sina beräkningar på observationer från oidentifierade fordon, dvs att observationerna inte har någon identitetsstämpel som kan kopplas till ett specifikt fordon. Två av modellerna betraktar länkarna som en helhet och utför beräkningarna med detta som grund, medan de två andra delar upp varje länk i mindre segment vilket skapar möjlighet för en större noggrannhet. Modellerna testades inledningsvis på simulerad data baserat på trafikmätningar i Göteborgstrakten. Alla beräkningar begränsades ner till länknivå och inte hela vägnät. Detta p.g.a. att det initialt var för komplicerat att skapa en map- matchingmetod som skulle krävas för genomföra beräkningar på olika länkar samtidigt. </p><p>Efter genomförda tester på simulerad data prövades modellerna även på en reella datamängd hämtad från projektet Probe i Stockholmsområdet. Resultaten från de utförda testerna visar på att det inte skiljer sig nämnvärt i restidsuppskattningarna mellan de olika modellerna. Sträckan som valdes att analyseras i de simulerade fallen, påverkades inte av några större störningar eller flödesvariationer. Det resulterade i att alla modellerna genererade likvärdiga restider. Även i fallet med den reella datamängden, som innehöll större flödesvariationer över tiden, kunde de olika modellernas uppskattningar inte skiljas åt nämnvärt. </p><p>Slutsatsen är att trafiken i allmänhet inte har så kraftiga förändringar i flödet över tiden, att det krävs särskilt avancerade modeller för att beräkna restider på länknivå. I alla fall inte om man bortser från incidenter. De framräknade restiderna och den information som dessa ger, bör främst användas för direkt trafikstyrning för att uppnå önskat resultat. Människor förlitar sig mer till sina egna erfarenheter i kända områden, så information av den här typen lämpar sig mer som hjälpmedel för den enskilde individen vid resor i okänd trafik.</p>

In Florida, the increased installation of non-traversable medians and directional median opening has produced an increased number of U-turns on multilane highways. Arguments have been advanced by some opponents of median modification projects that the increased numbers of U-turns may result in safety and operational problems on multilane highways. The primary objective of this study is to evaluate the operational effects of U-turn movement on multilane roadways. To achieve this research objective, extensive data were collected. Field measurements were conducted at 40 sites in the Tampa Bay area of Florida to collect traffic operations data. Besides, the crash histories of 179 selected roadway segments in central Florida were investigated. Statistical analysis was conducted based on the collected traffic operations data and crash data to quantitatively evaluate the operational performance of U-turn movement. Delay and travel time were compared for different driveway left- turn alternatives that are widely used in Florida and nationally. Crash rate models were developed to evaluate how the separation distance between a driveway exit and the downstream U-turn bay impacts the safety performance of vehicles making right-turns followed by U-turns (RTUT). With the crash data analysis results, the minimum separation distances under different roadway conditions were determined to facilitate driver use of RTUTs. The capacity of U-turn movement was analyzed under two different situations: (1) U-turns are provided at a signalized intersection; and (2) U-turns are provided at an unsignalized intersection. Adjustment factors were developed to quantify the impacts of the presence of U-turning vehicles on the capacity of a signalized intersection. The critical gaps and follow-up time for U-turn movement at unsignalized intersections were estimated. With the estimated critical gaps and follow-up time, the Harders model was used to determine the capacity of U-turn movem ent at an unsignalized intersection. This study also looks extensively at the minimum roadway width and median width required by vehicles to perform U-turn maneuvers on 4-lane divided roadways. It was found that a roadway width of 46 ft is generally sufficient for most types of design vehicles (except heavy vehicles) to perform a continuous U-turn maneuver without impedance.

The objective of the research described in this dissertation is to improve the travel-time prediction process using machine learning methods for the Advanced Traffic In-formation Systems (ATIS). Travel-time prediction has gained significance over the years especially in urban areas due to increasing traffic congestion. The increased demand of the traffic flow has motivated the need for development of improved applications and frameworks, which could alleviate the problems arising due to traffic flow, without the need of addition to the roadway infrastructure. In this thesis, the basic building blocks of the travel-time prediction models are discussed, with a review of the significant prior art. The problem of travel-time prediction was addressed by different perspectives in the past. Mainly the data-driven approach and the traffic flow modeling approach are the two main paths adopted viz. a viz. travel-time prediction from the methodology perspective. This dissertation, works towards the im-provement of the data-driven method. The data-driven model, presented in this dissertation, for the travel-time predic-tion on freeways was based on wavelet packet decomposition and support vector regres-sion (WPSVR), which uses the multi-resolution and equivalent frequency distribution ability of the wavelet transform to train the support vector machines. The results are compared against the classical support vector regression (SVR) method. Our results indi-cate that the wavelet reconstructed coefficients when used as an input to the support vec-tor machine for regression (WPSVR) give better performance (with selected wavelets on-ly), when compared against the support vector regression (without wavelet decomposi-tion). The data used in the model is downloaded from California Department of Trans-portation (Caltrans) of District 12 with a detector density of 2.73, experiencing daily peak hours except most weekends. The data was stored for a period of 214 days accumulated over 5 minute intervals over a distance of 9.13 miles. The results indicate an improvement in accuracy when compared against the classical SVR method. The basic criteria for selection of wavelet basis for preprocessing the inputs of support vector machines are also explored to filter the set of wavelet families for the WDSVR model. Finally, a configuration of travel-time prediction on freeways is present-ed with interchangeable prediction methods along with the details of the Matlab applica-tion used to implement the WPSVR algorithm. The initial results are computed over the set of 42 wavelets. To reduce the compu-tational cost involved in transforming the travel-time data into the set of wavelet packets using all possible mother wavelets available, a methodology of filtering the wavelets is devised, which measures the cross-correlation and redundancy properties of consecutive wavelet transformed values of same frequency band. An alternate configuration of travel-time prediction on freeways using the con-cepts of cloud computation is also presented, which has the ability to interchange the pre-diction modules with an alternate method using the same time-series data. Finally, a graphical user interface is described to connect the Matlab environment with the Caltrans data server for online travel-time prediction using both SVR and WPSVR modules and display the errors and plots of predicted values for both methods. The GUI also has the ability to compute forecast of custom travel-time data in the offline mode.

No abstract available. / Thesis (M.T.R.P.)-University of Natal, Durban, 1997.

This dissertation is concerned with the problem of estimating travel time per links in urban context using sparsely sampled GPS data. One of the challenges in this thesis is use the sparsely sampled data. A part of this research work, i developed a digital map with its new geographic information system (GIS), dealing with map-matching problem, where we come out with an enhancement tecnique, and also the shortest path problem.The thesis research work was conduct within the project PUMAS, which is an avantage for our research regarding the collection process of our data from the real world field and also in making our tests. The project PUMAS (Plate-forme Urbaine de Mobilité Avancée et Soutenable / Urban Platform for Sustainable and Advanced Mobility) is a preindustrial project that has the objective to inform about the traffic situation and also to develop an implement a platform for sustainable mobility in order to evaluate it in the region, specifically Rouen, France. The result is a framework for any traffic controller or manager and also estimation researcher to access vast stores of data about the traffic estimation, forecasting and status.