An investigation of location effect on trip production using artificial neural networks

As traffic congestion exuberates and new roadway construction is severely constrained because of limited availability of land, high cost of land acquisition, and communities' opposition to the building of major roads, new solutions have to be sought to either make roadway use more efficient or reduce travel demand. There is a general agreement that travel demand is affected by land use patterns. However, traditional aggregate four-step models, which are the prevailing modeling approach presently, assume that traffic condition will not affect people's decision on whether to make a trip or not when trip generation is estimated. Existing survey data indicate, however, that differences exist in trip rates for different geographic areas. The reasons for such differences have not been carefully studied, and the success of quantifying the influence of land use on travel demand beyond employment, households, and their characteristics has been limited to be useful to the traditional four-step models. There may be a number of reasons, such as that the representation of influence of land use on travel demand is aggregated and is not explicit and that land use variables such as density and mix and accessibility as measured by travel time and congestion have not been adequately considered. This research employs the artificial neural network technique to investigate the potential effects of land use and accessibility on trip productions. Sixty two variables that may potentially influence trip production are studied. These variables include demographic, socioeconomic, land use and accessibility variables. Different architectures of ANN models are tested. Sensitivity analysis of the models shows that land use does have an effect on trip production, so does traffic condition. The ANN models are compared with linear regression models and cross-classification models using the same data. The results show that ANN models are better than the linear regression models and cross-classification models in terms of RMSE. Future work may focus on finding a representation of traffic condition with existing network data and population data which might be available when the variables are needed to in prediction.

A static traffic assignment model combined with an artificial neural network delay model

As traffic congestion continues to worsen in large urban areas, solutions are urgently sought. However, transportation planning models, which estimate traffic volumes on transportation network links, are often unable to realistically consider travel time delays at intersections. Introducing signal controls in models often result in significant and unstable changes in network attributes, which, in turn, leads to instability of models. Ignoring the effect of delays at intersections makes the model output inaccurate and unable to predict travel time. To represent traffic conditions in a network more accurately, planning models should be capable of arriving at a network solution based on travel costs that are consistent with the intersection delays due to signal controls. This research attempts to achieve this goal by optimizing signal controls and estimating intersection delays accordingly, which are then used in traffic assignment. Simultaneous optimization of traffic routing and signal controls has not been accomplished in real-world applications of traffic assignment. To this end, a delay model dealing with five major types of intersections has been developed using artificial neural networks (ANNs). An ANN architecture consists of interconnecting artificial neurons. The architecture may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system. The ANN delay model has been trained using extensive simulations based on TRANSYT-7F signal optimizations. The delay estimates by the ANN delay model have percentage root-mean-squared errors (%RMSE) that are less than 25.6%, which is satisfactory for planning purposes. Larger prediction errors are typically associated with severely oversaturated conditions. A combined system has also been developed that includes the artificial neural network (ANN) delay estimating model and a user-equilibrium (UE) traffic assignment model. The combined system employs the Frank-Wolfe method to achieve a convergent solution. Because the ANN delay model provides no derivatives of the delay function, a Mesh Adaptive Direct Search (MADS) method is applied to assist in and expedite the iterative process of the Frank-Wolfe method. The performance of the combined system confirms that the convergence of the solution is achieved, although the global optimum may not be guaranteed.

An automatic tuning strategy for local fuzzy logic ramp metering algorithm using Particle Swarm Optimization (PSO)

Freeway systems are becoming more congested each day. One contribution to freeway traffic congestion comprises platoons of on-ramp traffic merging into freeway mainlines. As a relatively low-cost countermeasure to the problem, ramp meters are being deployed in both directions of an 11-mile section of I-95 in Miami-Dade County, Florida. The local Fuzzy Logic (FL) ramp metering algorithm implemented in Seattle, Washington, has been selected for deployment. The FL ramp metering algorithm is powered by the Fuzzy Logic Controller (FLC). The FLC depends on a series of parameters that can significantly alter the behavior of the controller, thus affecting the performance of ramp meters. However, the most suitable values for these parameters are often difficult to determine, as they vary with current traffic conditions. Thus, for optimum performance, the parameter values must be fine-tuned. This research presents a new method of fine tuning the FLC parameters using Particle Swarm Optimization (PSO). PSO attempts to optimize several important parameters of the FLC. The objective function of the optimization model incorporates the METANET macroscopic traffic flow model to minimize delay time, subject to the constraints of reasonable ranges of ramp metering rates and FLC parameters. To further improve the performance, a short-term traffic forecasting module using a discrete Kalman filter was incorporated to predict the downstream freeway mainline occupancy. This helps to detect the presence of downstream bottlenecks. The CORSIM microscopic simulation model was selected as the platform to evaluate the performance of the proposed PSO tuning strategy. The ramp-metering algorithm incorporating the tuning strategy was implemented using CORSIM's run-time extension (RTE) and was tested on the aforementioned I-95 corridor. The performance of the FLC with PSO tuning was compared with the performance of the existing FLC without PSO tuning. The results show that the FLC with PSO tuning outperforms the existing FL metering, fixed-time metering, and existing conditions without metering in terms of total travel time savings, average speed, and system-wide throughput.

Incorporating variable peak -to -daily ratios in the equilibrium traffic assignment procedure of the Florida Standard Urban Transportation Modeling Structure (FSUTMS)

The standard highway assignment model in the Florida Standard Urban Transportation Modeling Structure (FSUTMS) is based on the equilibrium traffic assignment method. This method involves running several iterations of all-or-nothing capacity-restraint assignment with an adjustment of travel time to reflect delays encountered in the associated iteration. The iterative link time adjustment process is accomplished through the Bureau of Public Roads (BPR) volume-delay equation. Since FSUTMS' traffic assignment procedure outputs daily volumes, and the input capacities are given in hourly volumes, it is necessary to convert the hourly capacities to their daily equivalents when computing the volume-to-capacity ratios used in the BPR function. The conversion is accomplished by dividing the hourly capacity by a factor called the peak-to-daily ratio, or referred to as CONFAC in FSUTMS. The ratio is computed as the highest hourly volume of a day divided by the corresponding total daily volume. ^ While several studies have indicated that CONFAC is a decreasing function of the level of congestion, a constant value is used for each facility type in the current version of FSUTMS. This ignores the different congestion level associated with each roadway and is believed to be one of the culprits of traffic assignment errors. Traffic counts data from across the state of Florida were used to calibrate CONFACs as a function of a congestion measure using the weighted least squares method. The calibrated functions were then implemented in FSUTMS through a procedure that takes advantage of the iterative nature of FSUTMS' equilibrium assignment method. ^ The assignment results based on constant and variable CONFACs were then compared against the ground counts for three selected networks. It was found that the accuracy from the two assignments was not significantly different, that the hypothesized improvement in assignment results from the variable CONFAC model was not empirically evident. It was recognized that many other factors beyond the scope and control of this study could contribute to this finding. It was recommended that further studies focus on the use of the variable CONFAC model with recalibrated parameters for the BPR function and/or with other forms of volume-delay functions. ^

A Static Traffic Assignment Model Combined with an Artificial Neural Network Delay Model

As traffic congestion continues to worsen in large urban areas, solutions are urgently sought. However, transportation planning models, which estimate traffic volumes on transportation network links, are often unable to realistically consider travel time delays at intersections. Introducing signal controls in models often result in significant and unstable changes in network attributes, which, in turn, leads to instability of models. Ignoring the effect of delays at intersections makes the model output inaccurate and unable to predict travel time. To represent traffic conditions in a network more accurately, planning models should be capable of arriving at a network solution based on travel costs that are consistent with the intersection delays due to signal controls. This research attempts to achieve this goal by optimizing signal controls and estimating intersection delays accordingly, which are then used in traffic assignment. Simultaneous optimization of traffic routing and signal controls has not been accomplished in real-world applications of traffic assignment. To this end, a delay model dealing with five major types of intersections has been developed using artificial neural networks (ANNs). An ANN architecture consists of interconnecting artificial neurons. The architecture may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system. The ANN delay model has been trained using extensive simulations based on TRANSYT-7F signal optimizations. The delay estimates by the ANN delay model have percentage root-mean-squared errors (%RMSE) that are less than 25.6%, which is satisfactory for planning purposes. Larger prediction errors are typically associated with severely oversaturated conditions. A combined system has also been developed that includes the artificial neural network (ANN) delay estimating model and a user-equilibrium (UE) traffic assignment model. The combined system employs the Frank-Wolfe method to achieve a convergent solution. Because the ANN delay model provides no derivatives of the delay function, a Mesh Adaptive Direct Search (MADS) method is applied to assist in and expedite the iterative process of the Frank-Wolfe method. The performance of the combined system confirms that the convergence of the solution is achieved, although the global optimum may not be guaranteed.

Utilização de sismos regionais para a determinação de um modelo 1D de velocidades da onda P na Província Borborema - NE do Brasil

In this work it was performed a study to obtain parameters for an 1D regional velocity model for the Borborema Province, NE Brazil. It was used earthquakes occurred between 2001 and 2013 with magnitude greater than 2.9 mb either from epicentres determined from local seismic networks or by back azimuth determination, when possible. We chose seven events which occurred in the main seismic areas in the Borborema Province. The selected events were recorded in up to 74 seismic stations from the following networks: RSISNE, INCT-ET, João Câmara – RN, São Rafael – RN, Caruaru - PE, São Caetano - PE, Castanhão - CE, Santana do Acarau - CE, Taipu – RN e Sobral – CE, and the RCBR (IRIS/USGS—GSN). For the determination of the model parameters were inverted via a travel-time table and its fit. These model parameters were compared with other known model (global and regional) and have improved the epicentral determination. This final set of parameters model, we called MBB is laterally homogeneous with an upper crust at 11,45 km depth and total crustal thickness of 33,9 km. The P-wave velocity in the upper crust was estimated at 6.0 km/s and 6.64 km/s for it lower part. The P-wave velocity in the upper mantle we estimated at 8.21 km/s with an VP/VS ratio of approximately 1.74.

Utilização de sismos regionais para a determinação de um modelo 1D de velocidades da onda P na Província Borborema - NE do Brasil

In this work it was performed a study to obtain parameters for an 1D regional velocity model for the Borborema Province, NE Brazil. It was used earthquakes occurred between 2001 and 2013 with magnitude greater than 2.9 mb either from epicentres determined from local seismic networks or by back azimuth determination, when possible. We chose seven events which occurred in the main seismic areas in the Borborema Province. The selected events were recorded in up to 74 seismic stations from the following networks: RSISNE, INCT-ET, João Câmara – RN, São Rafael – RN, Caruaru - PE, São Caetano - PE, Castanhão - CE, Santana do Acarau - CE, Taipu – RN e Sobral – CE, and the RCBR (IRIS/USGS—GSN). For the determination of the model parameters were inverted via a travel-time table and its fit. These model parameters were compared with other known model (global and regional) and have improved the epicentral determination. This final set of parameters model, we called MBB is laterally homogeneous with an upper crust at 11,45 km depth and total crustal thickness of 33,9 km. The P-wave velocity in the upper crust was estimated at 6.0 km/s and 6.64 km/s for it lower part. The P-wave velocity in the upper mantle we estimated at 8.21 km/s with an VP/VS ratio of approximately 1.74.

Does attendance affect grade? An analysis of first year economics students in Ireland

This paper examines the relationship between attendance and grade, controlling for other factors, in first year economics courses in University College Cork. Determinants of both class attendance and grade are specified and estimated. We find that attendance is low, at least by comparison with US evidence. Hours worked and travel time are among the factors affecting class attendance. Class attendance, and especially tutorial attendance has a positive and diminishing marginal effect on grade, while hours worked in a part-time job have a significant negative effect on grade.

Table 2: Stream flow measurement at the gauge station Vernagtbach

From 1974 to 1982 repeated tracer tests using fluorescent dyes were carried out in the highly glaciated drainage basin of Vernagtbach. These tests enabled the quantitative determination of the runoff in the forefield of the Vernagtferner, the calculation of travel times of the stream water and estimations of the relative contributions to the entire runoff originating from individual streams. In addition, tracer tests were carried out in the firn area of the glacier resulting in data concerning the storage and travel time of meltwater inside the glacier.

The impacts of telecommuting in Dublin

Telecommuting has been perceived as an effective means of reducing commuter related trips, travel time and emissions. Previously, the lack of access to broadband Internet connection and teleconferencing software from home has acted as a barrier to telecommuting regularly or at all. However, with advances in information and communication technology in recent years telecommuting is becoming a viable option for employers and employees to undertake. This paper examines the current trends of full day and part day telecommuting in the Greater Dublin Area (GDA), and attempts to ascertain the most influential drivers and constraints related to telecommuting. The research presented estimates of the environmental benefits from individuals that telecommute. Finally, this paper seeks to determine the magnitude of carbon emissions savings from individuals adopting telecommuting and provides a social cost of carbon saving value. The survey results presented suggest that approximately 44% of the population of the GDA telecommute at least once a month. The findings also indicate that needing contact with colleagues is the most influential constraint to telecommuting, while greater flexibility and avoiding travelling in peak periods are the most important drivers in the propensity to telecommute. Finally, this study shows that there are substantial carbon reductions and social cost of carbon savings. Thus illustrating how telecommuting can be a viable and sustainable policy in the GDA or in other similar sized regions.

La perception du temps et sa modulation par la température chez les guêpes parasitoïdes

Les modèles d'optimalité postulent que les animaux en quête de ressources utilisent le taux de gain de valeur adaptative pour optimiser plusieurs comportements tels que la répartition du temps lors de l’exploitation d‘un agrégat et l'investissement en progénitures. Bien que la durée de plusieurs comportements doit être régulée, peu d’évidences de la perception du temps sont actuellement disponibles pour les insectes et aucune pour les guêpes parasitoïdes, et ce malgré leur importance en tant que modèles écologiques. De plus, puisque les guêpes parasitoïdes sont poïkilothermes, cette capacité pourrait être affectée par la température. Nous avons supposé que les guêpes parasitoïdes auraient la capacité de percevoir le temps, à la fois de façon prospective (mesure du temps écoulé) et rétrospective (durée d'un événement passé), afin d'optimiser les décisions liées à l'exploitation d’agrégats d’hôtes et à la reproduction. Nous avons également émis l'hypothèse que la température aurait une incidence sur la perception du temps des guêpes parasitoïdes. Pour la mesure prospective du temps, nous avons utilisé la capacité d’apprentissage associatif de Microplitis croceipes (Hymenoptera: Braconidae). Les guêpes ont été entraînées à associer une odeur à la durée d'un intervalle entre des hôtes. Après leur entraînement, elles ont été testées dans un tunnel de vol avec un choix d’odeurs. Les guêpes ont choisi majoritairement l'odeur associée à l'intervalle de temps auquel elles étaient testées. Nous avons également investigué le rôle de la dépense énergétique sur la mesure du temps. Suite à une restriction de mouvement des guêpes pendant l'intervalle de temps entre les hôtes, elles choisissaient aléatoirement dans le tunnel de vol. L'absence de dépense énergétique les aurait rendues incapables de mesurer le temps. La dépense d'énergie est donc un substitut essentiel pour mesurer le temps. Pour la mesure rétrospective du temps, nous avons utilisé le processus d'évaluation de l'hôte de Trichogramma euproctidis (Hymenoptera: Trichogrammatidae). Certains trichogrammes utilisent la durée du transit initial sur l'œuf hôte afin d’en évaluer la taille et d’ajuster le nombre d’œufs à y pondre. Nous avons augmenté artificiellement la durée de transit initiale de T. euproctidis en suspendant l'œuf hôte pour le faire paraître plus gros qu'un œuf de taille similaire. Une augmentation de la durée de transit initiale a augmenté la taille de la ponte. Ceci démontre la capacité de T. euproctidis de mesurer la durée du transit initial, et donc d’une mesure du temps rétrospective. Pour déterminer si la température modifie la mesure du temps dans les espèces poïkilothermes, nous avons utilisé le comportement d’exploitation d’agrégats d’hôtes de T. euproctidis. Les modèles d’optimalités prédisent que les guêpes devraient rester plus longtemps et quitter à un faible taux de gain de valeur adaptative suite à un déplacement de longue durée plutôt que pour un déplacement de courte durée. Nous avons testé l'impact d'un déplacement de 24 h à différentes températures sur l'exploitation d’agrégats d’hôtes. Un déplacement à température chaude augmente le temps de résidence dans l’agrégat et diminue le taux de gain de valeur adaptative au moment de quitter ; ces comportements sont associés à un trajet de longue durée. L'inverse a été observé lors d’un déplacement à une température froide. Les températures chaude et froide ont modulé la mesure du temps en accélérant ou ralentissant l'horloge biologique, faisant paraître le déplacement respectivement plus long ou plus court qu’il ne l’était réellement. Ces résultats démontrent clairement que les guêpes parasitoïdes ont la capacité de mesurer le temps, autant rétrospectivement que prospectivement. Des preuves directes de leur capacité sont maintenant disponibles pour au moins deux espèces de guêpes parasitoïdes, une composante essentielle des modèles d'optimalité. Le rôle de la dépense énergétique dans la mesure du temps a aussi été démontré. Nos résultats fournissent également la preuve de l'impact de la température sur la perception du temps chez les insectes. L'utilisation de la dépense énergétique en tant que proxy pour mesurer le temps pourrait expliquer une partie de sa thermosensibilité, puisque les guêpes parasitoïdes sont poïkilothermes. Cette mesure du temps sensible à la température pourrait affecter des stratégies de lutte biologique. Sur le terrain, au début de la journée, la température de l'air sera similaire à la température de l'air autour des plantes infestées par des parasites, alors qu'elle sera plus chaude pendant la journée. En lutte biologique augmentative, les guêpes parasitoïdes libérées resteraient plus longtemps dans les agrégats d’hôtes que celles relâchées en début de journée.

Iowa Motor Vehicle Fuel Reduction Program, 1989

This report documents the results of a three million dollar traffic signal improvement demonstration program, known as the Iowa Motor Vehicle Fuel Reduction Program (the program). The program was funded with the use of oil overcharge funds and administered by the Iowa Departments of Natural Resources and Transportation. The objective of the program was to provide restitution to overcharged motorists by improving the efficiency of traffic signals. More efficient traffic signals reduce fuel consumption, delay, travel time, and automobile pollution while improving traffic safety. The program demonstrated the effectiveness of improving traffic signals and resulted in a 14.20-to-1 benefit-to-cost ratio.

Propagation des ondes longitudinales dans le noyau terrestre d'après les séismes profonde des Iles Fidji

Observations from three deep focus earthquakes, of focal depth 600 km, originating in the Fiji Islands region, have permitted to trace the travel-time curves for the longitudinal waves travelling through the earth's core. Of principal importance is the travel-time table for the phase PKP1 which has been given upto 158° and for which the data so far were incomplete. Other important phases observed between 103 and 143° have been illustrated and their travel-time curves drawn.

Récents séismes proches du Vietnam d’après les données de la station de Nhatrang

During the years 1957-64, eight local earthquakes have been recorded at the station of Nhatrang. A description of these quakes has been done and a drawing of experimental travel-time curves of different phases has been attempted

Small strain elastic behaviour of unsaturated soil investigated by bender/extender element testing

The aim of this project was to investigate very small strain elastic behaviour of soils under unsaturated conditions, using bender/extender element (BEE) testing. The behaviour of soils at very small strains has been widely studied under saturated conditions, whereas much less work has been performed on very small strain behaviour under unsaturated conditions. A suction-controlled double wall triaxial apparatus for unsaturated soil testing was modified to incorporate three pairs of BEEs transmitting both shear and compression waves with vertical and horizontal directions of wave transmission and wave polarisation. Various different techniques for measuring wave travel time were investigated in both the time domain and the frequency domain and it was concluded that, at least for the current experimental testing programme, peak-to-first-peak in the time domain was the most reliable technique for determining wave travel time. An experimental test programme was performed on samples of compacted speswhite kaolin clay. Two different forms of compaction were employed (i.e. isotropic and anisotropic). Compacted kaolin soil samples were subjected to constant suction loading and unloading stages at three different values of suction, covering both unsaturated conditions (s= 50kPa and s= 300kPa) and saturated conditions (s=0). Loading and unloading stages were performed at three different values of stress ratio (η=0, η=1 and η=-1 ). In some tests a wetting-drying cycle was performed before or within the loading stage, with the wetting-drying cycles including both wetting-induced swelling and wetting-induced collapse compression. BEE tests were performed at regular intervals throughout all test stages, to measure shear wave velocity Vs and compression wave velocity Vp and hence to determine values of shear modulus G and constrained modulus M. The experimental test programme was designed to investigate how very small strain shear modulus G and constrained modulus M varied with unsaturated state variables, including how anisotropy of these parameters developed either with stress state (stress-induced anisotropy) or with previous straining (strain-induced anisotropy). A new expression has been proposed for the very small strain shear modulus G of an isotropic soil under saturated and unsaturated conditions. This expression relates the variation of G to only mean Bishop’s stress p* and specific volume v, and it converges to a well-established expression for saturated soils as degree of saturation approaches 1. The proposed expression for G is able to predict the variation of G under saturated and unsaturated conditions at least as well as existing expressions from the literature and it is considerably simpler (employing fewer state variables and fewer soil constants). In addition, unlike existing expressions from the literature, the values of soil constants in the proposed new expression can be determined from a saturated test. It appeared that, in the current project at least, any strain-induced anisotropy of very small strain elastic behaviour was relatively modest, with the possible exception of loading in triaxial extension. It was therefore difficult to draw any firm conclusion about evolution of strain-induced anisotropy and whether it depended upon the same aspects of soil fabric as evolution of anisotropy of large strain plastic behaviour. Stress-induced anisotropy of very small strain elastic behaviour was apparent in the experimental test programme. An attempt was made to extend the proposed expression for G to include the effect of stress-induced anisotropy. Interpretation of the experimental results indicated that the value of shear modulus was affected by the values of all three principal Bishop’s stresses (in the direction of wave transmission, the direction of wave polarisation and the third mutually perpendicular direction). However, prediction of stress-induced anisotropy was only partially successful, and it was concluded that the effect of Lode angle was also significant.