Hydroplaning on a pavement surface with a film of water occurs when a vehicle reaches a critical speed and results in a loss of contact between its tires and the pavement surface. Pavement groovings, especially transverse pavement groovings, have been used in practice to reduce the occurrences of hydroplaning. This paper presents the development of a three-dimensional finite-volume model to simulate the hydroplaning phenomenon on pavements with and without transverse groovings. The theoretical considerations involved in the flow simulation model are described. The flow simulation makes use of fluid dynamics theories, utilizing the continuity equation, the Navier–Stokes equations, and the standard $k\text{-}\epsilon$ turbulence model to model hydroplaning. The simulation results for the case of a smooth plane pavement surface are found to be in good agreement with experimental results in the literature and the well-known National Aeronautics and Space Administration (NASA) hydroplaning equation. The tire pressure-hydroplaning speed relationship predicted by the model is found to match very well with the empirical NASA hydroplaning equation. The model is applied to analyze pavement surfaces with three different transverse pavement groovings and verified against experimental results reported in the literature. The analysis also highlights the effectiveness of transverse pavement grooving in delaying hydroplaning occurrence (i.e., raising the speed at which hydroplaning occurs) and improving braking control during incipient hydroplaning. The analytical design of transverse pavement grooving to reduce the risk of hydroplaning is found in a companion paper.

This paper analyzes the effect of groove dimensions (width, depth, and spacing) of transversely grooved pavement surface on hydroplaning using a three-dimensional finite-volume hydroplaning simulation model. Groove widths varying from 2 to 10 mm, groove depths from 1 to 10 mm, and center-to-center spacings from 5 to 25 mm are examined. The effectiveness of a pavement groove design against hydroplaning can be assessed by its ability to raise the hydroplaning speed, which is the vehicle speed at which hydroplaning occurs. It is found that the hydroplaning speed can be raised by increasing the groove depth and width, and decreasing the groove spacing, thereby reducing the risk of hydroplaning occurrence. Among the three groove dimensions (i.e., width, depth, and spacing), changes in groove width is found to have the most significant effect, followed by groove spacing and groove depth. This paper next proposes an analytical procedure for the design of transverse pavement grooving using the simulation model based on the concept of risks of hydroplaning. An illustration of the proposed design procedure is presented in this paper, using a wet-weather freeway vehicle speed distribution, to determine the transverse pavement grooving designs for different risk levels from 0.001% upward. The design concept also allows one to assess the hydroplaning risk level of an existing transversely grooved pavement surface or a proposed groove design, with known wet-weather traffic speed distribution and water film thickness.

The multidepth deflectometer (MDD) is used to estimate flexible pavement response subjected to permitted overweight truck traffic (gross vehicle weight up to 556 kN). This study focuses on using material constitutive models to assess the most accurate and reliable pavement layer behavior. Deflections from MDDs installed on tested pavement section were compared with predicted ones using different material constitutive models to determine the best model. As a result, the best comparisons with the measured MDD deflections were achieved when base and subgrade materials were modeled as nonlinear cross anisotropic. In terms of pavement performance prediction, predicted rutting using a nonlinear cross-anisotropy model was matched reasonably well with measured values by generating a slightly higher compressive vertical strain from each subdivided layer. In addition, the cross-anisotropy characteristic of asphalt concrete material was introduced and applied to predict pavement performance. This results in larger rutting due to vertical strain within the asphaltic concrete layer. Thus, there is a need to take into account nonlinear cross-anisotropy characteristic of pavement materials in assessing pavement damage due to truck loadings.

One of the key functions of traffic management systems is to monitor traffic conditions and detect the presence of conditions that are abnormal or may not be expected. As archiving of traffic data becomes less costly and more commonplace, generation of short-term forecasts of traffic conditions in real-time conditions is also becoming increasingly possible. Use of condition monitoring information can enhance the performance of short-term traffic forecasting procedures. In this study, one of the most studied approaches to forecasting, the nearest neighbor form of nonparametric regression, is coupled with a condition monitoring method that characterizes the extent to which current traffic conditions deviate from those that may be expected based on historical data. When the normalcy-based approach to traffic condition monitoring was used in the selection of observations from a traffic data archive and in the determination of the nearness of those observations to the current condition, the mean absolute percentage errors for two of the four nearest neighbor forecasting procedures were reduced.

Most of the studies available in the literature indicate that the speed data on a highway follow the normal distribution. The present study indicates that the speed distribution may be a unimodal or a bimodal curve depending upon the variation in the speed of different categories of vehicles moving on the highway. The mathematical equations are suggested for unimodal and bimodal speed distribution curves, and their parameters are evaluated at 17 different sections of two-lane roads in India. It is observed that the proportion of slow moving vehicles is not a true indicator of bimodality in the speed data. The spread ratio defined as the ratio of the difference between 85th percentile and mean stream speed to the difference in mean stream speed and 15th percentile speed, is better correlated with the shape of the speed distribution curve. The speed data follow the unimodal curve only when the spread ratio is in the range of 0.69–1.35.

It is well known that the ambient air pollution attributable to road traffic depends on a number of factors such as the quality of fuel used, engine technology, driving conditions, emission control devices, and meteorological conditions. In spite of the efforts to control emissions from road traffic by way of stringent emission norms (such as Euro-III and IV) for automobile engines and improved fuel quality, the road traffic emissions form a significant proportion of urban air pollutants. This is primarily due to constant increase in number of motor vehicles and their use in the urban areas. Recognizing this aspect and with a view to provide clean air, the Supreme Court of India has issued an order in a public interest litigation matter, directing that public transport vehicles, namely intracity buses, should be run on compressed natural gas (CNG) in Delhi. The directive of the Supreme Court was implemented but along with it many other actions/measures were also implemented by the concerned authorities. These measures included operation of taxis and auto rickshaws on CNG, scrapping of all commercial vehicles including taxis aged 15 years and above, introduction of Euro-I emission norms for private passenger cars, use of unleaded petrol, and premixing of 2T oil with petrol for two wheeler motor vehicles. The result of the combined efforts is a perceivable change in the ambient air quality for the better. But questions and debates were frequent as to whether the improved quality of air is mainly due to CNG and if so how much is to be attributed to CNG. To answer these questions a detailed study was carried out to quantify the emissions and their reductions due to different measures. This paper presents an account of the study. In this study the quantity of criteria pollutants such as carbon monoxide, nitrogen oxides and particulate matter and hydrocarbons are estimated on the basis of vehicle kilometers traveled by different vehicles in the city during the course of time when the improvement measures were being effected on an incremental basis. The results of the study are discussed and the contribution of each of the measures is estimated. The implemented improvement measures were extremely successful. The improvement was, as made out to be, not simply because of CNG conversion of buses but due to the combined effect of many other steps like improved vehicle technologies and fuel quality, phasing out the old diesel vehicles, conversion of auto rickshaws to CNG, etc. The results are of interest to both the analysts and policy makers in appreciating the impact of each of the measures.

Recent interest in developing activity-based models of transport demand has encouraged research on the design and administration of activity diaries. Activities occur in time and space. Traditionally, these two dimensions have been bifurcated. Time-use diary researchers focused on activities whereas travel diary researchers centered on trips. However a combination of both time and travel diaries (time-space diary) could bring out the potential for alternative diary formats. This paper focuses on the development of a time-space diary describing the experience of a pilot survey conducted to identify the best data collection technique. Special attention has also been given to address the problem of nonresponse and missing data. The economic and efficiency analysis is also reported. The future modifications in the survey instrument and method of administration for the final survey are also discussed. Overall, the formulated time-space diary performed better than the conventional travel diary and also the face-to-face survey method emerged as the best way of administration.

Bicyclists consistently identify safety as one of their highest priorities in selecting bicycle routes. If transportation officials want to succeed in achieving the goal of increasing nonvehicular modes of travel, bicycle routes must be provided that are convenient and safe. In this study, a pilot study was undertaken to develop a tool to compare the relative safety of alternate bicycle routes. A multivariate logistic model was developed for urban bicycle routes based on four years of bicycle crash data from Jersey City, N.J. The resulting model meets a 90% confidence level by using various operational and physical factors (traffic volume, lane width, population density, highway classification, the presence of vertical grades, one-way streets, and truck routes) to predict the severity of an injury sustained by a bicyclist that would result from a motor vehicle crash occurring at a specific location. The model was used to rate proposed bicycle routes in Jersey City, N.J., assuming that a bicycle crash on the safest route would be the least likely to produce severe injuries. Both existing conditions and mitigated scenarios were rated and compared with field observations.

In highway construction, it is not only important to understand the factors that affect the schedule but also to evaluate their probable severity and impact on project duration. However, there is currently no standard or accepted model existing in the industry that can be used for this purpose. This paper presents a model that identifies various factors which have a potential to influence and impact the construction schedule in highway work zones. Also, a stochastic analysis of those factors is conducted by the model to determine probable changes, i.e., reduction or escalation, in the original estimated schedule for a given project. The analysis offers a revised schedule that is bound to be more meaningful and close to the expected value. The state Department of Transportation cannot only use the results to improve project scheduling but also improve the user cost calculations and decisions regarding contract types and requirements, e.g., liquidated damages, penalties, and incentives/disincentives.

In this research feeder routes and coordinated schedules were developed for integration of feeder public buses with suburban trains. A Heuristic Feeder Route Generation Algorithm was developed for generation of feeder routes. Optimal coordinated schedules for feeder buses were developed in coordination with the existing given schedules of suburban trains. Genetic algorithm, which is a robust optimization technique, is used for the optimizing coordinated schedules. Andheri and Vileparle suburban railway stations of Mumbai, India were selected as study areas. Feeder routes for public buses and coordinated schedules of public buses for the existing given schedules of suburban trains at the two suburban railway stations were successfully developed in this research.