The evaluation of alternative alignments for a proposed highway project in California required taking into account impacts on a variety of environmental and socioeconomic issues. Techniques of formal decision analysis were used to evaluate the overall impact of each alternative alignment and to rank the alignments in an ascending order of the overall impact. A multiattribute penalty function was calibrated using acceptable trade‐offs among impacts on different issues as assessed by a project team of scientists and planners. Results of decision analysis suggested that one of the alternative alignments should be most preferred under a variety of assumptions and value judgments. This alternative was recommended for further analysis and inclusion in a draft environmental impact report/statement. The application of decision analysis to this evaluation problem was effective because it: (1) Provided a rational procedure to address multiple and often conflicting environmental and socioeconomic issues; (2) facilitated sensitivity analysis to evaluate the impact of perceived value judgments of different concerned groups on the ranking of the alternatives; and (3) provided a full documentation of the evaluation process.

In order to qualify for federal operating assistance, transit operators in the United States are required to report annual unlinked passenger miles carried on bus and fixed guideway systems. In order to ensure fair apportionment of federal operating subsidies among various transit operators, the Federal Transit Administration (FTA) requires that annual unlinked passenger miles statistics be reported within an accuracy of ±10% at a 95% confidence interval. If a statistical sampling method is used to compute annual unlinked passenger miles, transit operators must select an adequate sample size that will yield the desired results. Guidelines for collecting and reporting unlinked passenger miles data for transit systems with controlled passenger access have been provided in UMTA Circular 2710.4. However, this revenue‐based method is not suitable for barrier‐free transit systems in operation. A partial ride check‐based methodology can be utilized to develop these statistics. From sample ride checks, an analyst can estimate the average number of boardings and the average trip length per trip. These averages can then be utilized to establish annual unlinked passenger miles. Using Los Angeles' Metro Blue Line data collected during the first year of operation, this paper provides the estimates of variance and covariance in boardings per trip, and sample size requirements. Issues pertaining to daily, monthly, and quarterly patronage estimation are also addressed.

Presented in this paper is an investigation of areawide seasonal traffic counts (STC) that are undertaken by all state highway agencies throughout the United States and in several other countries. The current practice of STC programs is very diverse and there is a little evidence of major research efforts in this area. A large number of permanent traffic counter (PTC) sites are studied in order to rationalize the length and frequency of STC schedules. A proposed method described in this paper can be used to assign STC sites to one of the PTC groups for estimation of traffic parameters. An index of assignment effectiveness is developed to evaluate the appropriateness of alternative STC schedules. Another criterion is suggested to ensure whether a given STC schedule provides a seasonally balanced traffic volume sample. Effect of the road type on the length and frequency of counts is also studied. A number of alternative STC schedules are suggested to be used by highway agencies for cost‐effective traffic monitoring.

The research described in this paper employed simulation modeling and empirical observations in an effort to: (1) Identify the traffic flow phenomena that characterize freeway weaving section capacity; and (2) determine appropriate traffic flow rate values that reflect weaving section capacity. The INTRAS microscopic simulation model was calibrated and validated using empirical data collected at a weaving site. Increasing traffic demands were then sequentially input into repeated simulation runs to identify the boundary between uncongested and congested operation. Where a weaving section exhibits a typical level of both merging and diverging traffic movements, capacity is defined as a function of flows and lane‐changing rates occurring in the vicinity of the weaving area's merge gore. Where a weaving section operates with a relatively low total weaving demand, capacity is defined as a maximum rate of vehicles per lane. Validation experiments described in this paper suggest that the derived values of capacity apply to any one‐sided freeway weaving section.

An interactive microcomputer program referred to as runway exit design interactive model (REDIM) has been developed to optimally locate and design high‐speed runway exits at airports. The model uses kinematic equations to characterize the aircraft landing dynamics and a polynomial‐time dynamic programming algorithm to find the optimal locations of the high‐speed exits. The objective of the optimization algorithm is to minimize the weighted average runway occupancy time (ROT) of an aircraft mix selected by the user. A data base of aircraft characteristics for four terminal airspace procedure (TERP) categories has been included in the model to facilitate its use in a large variety of airport environments and conditions. The data‐base file relieves the user's data‐input burden, specially when the aircraft mix consists of many different types of aircraft. The program is developed to be used as a design and a planning instrument by engineers. Hence, considerable effort has been devoted to user interface such as menu system, interactive data editing, and graphical and tabular outputs.

Collection and analysis of pavement distress data are receiving attention for their potential to improve the quality of information on pavement condition. We present an approach for the automated classificaton of asphalt pavement distresses recorded on video or photographic film. Based on a model that describes the statistical properties of pavement images, we develop algorithms for image enhancement, segmentation, and distress classification. Image enhancement is based on subtraction of an “average” background: segmentation assigns one of four possible values to pixels based on their likelihood of belonging to the object. The classification approach proceeds in two steps: in the first step, the presence of primitives (building blocks of the various distresses) is identified, and in the second step, classification of images to a distress type (using the results from the first step) takes place. The system addresses the following distress types: longitudinal, transverse, block, alligator cracking, and plain. Application of the models to a set of asphalt pavement images gave promising results.

The present paper illustrates the feasibility of using neural network models for priority assessment of highway pavement maintenance needs. Since neural networks are developed to mimic the decision‐making process of human beings and do not require users to predefine a mathematical equation relating pavement conditions to priority ratings, they offer an attractive means by which the priority setting process by highway maintenance personnel can be simulated. In the present study, the ability of a simple back‐propagation neural network was tested separately with three different priority‐setting schemes, using a general‐purpose microcomputer‐based neural network software. The priority‐setting schemes include a linear function relating priority ratings to pavement conditions, a nonlinear function, and subjective priority assessments obtained from a pavement engineer. For the first two schemes, noise was also introduced to examine how it would affect the performance of the neural network. Test results are positive and indicative of the potential of neural networks as a useful tool that highway agencies can use for priority rating in maintenance planning at the network level.

The purpose of this study is to investigate the use of industrial byproduct mixtures as construction materials. Fly ash, which is a by‐product of coal combustion, is mixed with fine‐grained material, a by‐product from an aggregate processing operation. Neither material exhibits satisfactory engineering properties by itself. However, if combined, the resulting material properties are improved and potential applications may be found within pavements, structural fill for embankment construction, or as backfill behind abutments and retaining walls. For this paper, the materials are investigated for use as highway materials within a flexible pavement system. In order to demonstrate the benefit of the material mixture toward improvement of overall pavement performance, predicted pavement lives for structures having subgrades consisting of aggregate waste, fly ash, and a mixture of aggregate waste and fly ash are compared.

Pavement deflection data are often used to evaluate pavement's structural conditions nondestructively. Pavement layers are characterized by their elastic moduli estimated from surface deflections through backcalculations. Results of various algorithmic backcalculation methods currently available are often dependent upon individual analyst's experience and judgments in supplying input parameters and they often do not agree with each other. Much of the empirical knowledge accumulated through decades of pavement research and practice has yet to be formalized to assist analytical backcalculations. To organize the various knowledge utilized by a human analyst to perform evaluation and to make nondestructive evaluation more accessible, a knowledge‐based system, Pavement Structural Evaluation System (PASELS), is developed. This rule‐based system can help provide rational estimation of pavement layer moduli and is particularly useful when algorithmic backcalculation methods do not give reasonable results. Although it still needs to be supervised by an experienced analyst and its performance is limited by the knowledge available in its knowledge base, such automated deflection analysis systems could greatly improve the efficiency of interpreting nondestructive test results.

In this paper, a comprehensive study of structural evaluation methods for jointed concrete airfield pavements is presented. A specially prepared concrete test pavement, consisting of six slabs with different size voids beneath the slabs at corners incorporated by variably spaced dowel joints, is loaded by the falling weight deflectometer (FWD) test system. By analyzing these FWD measurements with the finite element model, the usefulness of the FWD as a tool for measuring various important pavement properties is assessed. Based on the deflection basins measured by FWD, the resilient modulus of the foundation can be calculated, load transfer efficiency at joints of pavement can be determined, and the size of voids beneath the slab can be detected. Field measurements made at an in‐service airfield pavement indicate that the FWD is a suitable device for the structural evaluation of jointed concrete airfield pavements.

Investigated in this technical note is the yearly variation of directional distribution of traffic on rural highways. A total of 60 sites located in the province of Alberta, Canada, are investigated. Two measures of directional split are computed for each of the study sites, and their variation is studied over a period of six years, (1984–1989 inclusive). The results of analysis indicate that, in many cases, the directional split observed on rural roads during a selected design hour (such as the 30th highest volume hour) may be subject to a large variation from year to year. The data presented also indicate clearly that design directional split which is the other method described in this paper, experiences much less variation from year to year. Because of its greater stability over time, the design directional split can be considered as a superior measure of directional split.