A quantitative methodology to select a suitable terminal geometry for a pier‐type airport terminal is presented. Given the size of a terminal in terms of aircraft gates, the geometry that minimizes the passenger walking distance is obtained based on: the fraction of arriving‐departing and transferring (hub and nonhub) passengers; gate spacing; and spacing between piers. The passenger walking distance is considered as the selection criterion as it is the major level of service factor that is affected by the terminal geometry. A continuum approximation is used to model passenger walking within piers. Walking distances between piers is modeled using discrete methods. It is shown that the optimum geometry for a centralized‐radial pier configuration consists of a set of uniform pier lengths. For centralized parallel and semicentralized configurations it consists of a set of nonuniform pier lengths. The optimum number of piers is nearly proportional to the square root of the total number of gates. The probability distribution of the walking distance of a passenger can be generated by simulation. Several statistical parameters that are suitable to choose the best configuration, given the optimum geometry for each configuration, are reported.

A detailed comparison of moduli measured in the laboratory by resilient modulus testing with moduli measured in the field by falling weight deflec‐tometer (FWD) testing is made. This comparison includes an analysis of whether good agreement between lab and field values should be expected as well as an assessment of relative quality of the results and relative testing costs. Good agreement between lab and field measured moduli should not be expected when following the usual practice of sampling and testing only the top 1 or 2 ft (0.3 or 0.6 m) of the subgrade. Agreement is not to be expected because different volumes of the material are being tested in the laboratory compared to field testing by FWD. Because different volumes of material are tested, heterogeneity in any layer contributes to different measured moduli by lab and field testing. It is also concluded that the cost of determining moduli by laboratory resilent modulus testing is typically 60–80 times greater than the cost of an equivalent field testing program with the FWD. When the added costs of traffic control during sampling and project delays are included, the cost ratio may exceed 100. Furthermore, the moduli from field FWD testing are typically of higher quality and more appropriate for mechanistic pavement design than lab‐measured moduli. This conclusion arises from the fact that it is very difficult, if not impossible, to erase completely the effects of sample disturbance on lab‐measured moduli. In addition, when moduli are back‐calculated from FWD testing, a proper weighting factor is automatically applied to all zones contributing to deformations, it is also possible to take advantage of compensating errors in back‐calculated moduli.

This study applies image‐analysis techniques to classify vehicles on highways. The procedure of image analysis includes four stages: image acquisition, data processing, feature extraction, and object classification. An infrared image device system is used to record vehicle images on highways. A modified edge‐sharpening technique is derived in this study to filter out noise and to locate edges of bridge clusters simultaneously. A true classifier, including a modified kNN (k nearest neighbor) method, is also established for the classification of vehicles. The time complexity of the proposed algorithm is linear. The accuracy of the algorithm is examined for the classification of a single vehicle per image. The possibility of real‐time analysis for infrared image analysis is also discussed. The results of this study show that the image analysis has potential in the area of automatic traffic‐monitoring systems.

For an efficient traffic operation in intelligent highway systems, traffic signals need to respond to the changes in roadway and traffic demand. The phasing and timing of traffic signals requires the use of heuristic rules of thumb to determine what phases are needed and how the green time should be assigned to them. Because of the need for judgmental knowledge in solving this problem, this study has used knowledge‐based expert‐system technology to develop a system for the phasing and signal timing (PHAST) of an isolated intersection. PHAST takes intersection geometry and traffic volume as input and generates appropriate phase plan, cycle length, and green time for each phase. The phase plan and signal timing change when intersection geometry or traffic demand changes. This paper describes the intended system functionality, the system architecture, the knowledge used to phase and time an intersection, the implementation of the system, and system verification. PHAST's performance was validated using phase plans and timings of several intersections, including the examples within the Highway Capacity Manual (HCM). A comparison of delays and levels of service of the phase plans and signal timings generated by PHAST to those of HCM indicate that very comparable optimal solutions are being generated by the PHAST system. A potential use of the PHAST system would be in the design of demand‐responsive intersection controllers for intelligent‐vehicle highway systems (IVHS).

In 1983, the Connecticut Department of Transportation (ConnDOT), in cooperation with the Federal Highway Administration, began developing a pavement management system (PMS) tor use on state‐maintained highways. A major offshoot from the project was the Connecticut photolog laser videodisc (PLV) retrieval system, which is changing the means and methods for storing, retrieving, and using highway photolog images. The PLV retrieval system formed the backbone for a network‐level pavement‐condition rating system, which allows ConnDOT engineers or technicians to rate pavement distress inside the office under ideal, controlled working conditions. Under these conditions, and with the aid of computers, ConnDOT personnel can perform more objective evaluations of pavement conditions than with previous windshield surveys. This pavement rating system has been successfully used for two years. Although research is under way to determine how the sun's position affects rating results, ConnDOT engineers are convinced that videodisc photolog images yield superior image quality over other systems that use video images.

City officials must allocate the limited pavement maintenance and repair funds, available among numerous sections of roadways, streets, and highways and determine future pavement maintenance and repair needs. The use of a well‐designed and developed pavement management system can result in a more effective allocation of the available funds and more accurate estimates of future needs. A pavement management system for small communities (PMSC) is presented. PMSC consists of seven modules: (1) Inventory; (2) distress survey; (3) maintenance/rehabilitation; (4) unit costs; (5) deterioration rates; (6) priority ratings and goals; and (7) backup. The developed system is user‐friendly and practice‐oriented, and it is designed to demonstrate the accessibility and applicability of data‐base management systems.

Certain inappropriate driving behaviors (IDBs) can result in unsafe driving conditions and increased accident potential. It is believed that some IDBs may be reduced by educating the general public (specifically, high‐risk driver groups) about the potential consequences through increased public awareness. Twenty‐five IDBs were identified and ranked according to: (1) The opinions of experts in the field of driver behavior considering accident potential, seriousness of consequences, and ease of correction; and (2) accident frequencies and rates using Pennsylvania accident data for 1984–86. A comprehensive literature search supplemented these efforts. A synthesis of all the analyses led to the following key statements to be used in the development of strategies for the campaign: (1) Young drivers consistently overrate their own ability and level of risk. (2) Younger males and older females have the highest accident rates; drivers under 19 and over 70 also have the highest accident costs. (3) Males are most often responsible across all age groups. (4) Speeding is the most frequent IDB of the IDBs causing accidents. (5) Over 50% of all accidents in Pennsylvania (1984–86) were the result of failure‐to‐yield situations, tailgating, or driving in the wrong lane, and (6) IDBs that appear to be the easiest to modify currently represent the smaller portions of total accidents.

The time period between an urban road accident and death due to it, is investigated. Age and sex of injured persons were found to have no significant effect on time till death. The analysis distinguishes between a set of data that includes persons killed on site and a data set from which they are excluded. The probability density function (pdf) of the length of these time periods, when expressed in hours, was found to be satisfactorily described by a Weibull distribution for both cases. When these lengths are expressed in days the Gamma distribution gave the best fit. Linear relationships between the cumulative percentage of injured persons dead by time (and log(r) are also established with very high correlation coefficients, but are proposed only for time period lengths less than 30 days. Ways in which the results of this analysis can be used towards unification of road accident death recording in the various countries, so that valid international accident statistics comparisons are possible, are indicated.

A mixed‐integer mathematical model is presented to optimally schedule long‐term bridge deck rehabilitation and replacement activities. This model is applicable to multiple bridge decks and is driven by overall cost considerations. Activities are scheduled based on the current condition and perceived future deterioration of each bridge deck. The model uses logical constraints to incorporate an “if‐then‐else” scenario into the rehabilitation model. These constraints directly relate the maintenance decisions in any year to the perceived condition of each individual bridge deck. Model structure and solution method were discussed, and an example using three highway bridges in North Carolina is presented. Model solutions indicate bridge deck replacement and rehabilitation activities throughout the planning horizon for each deck considered. Model results include the development of a trade‐off relationship between long‐term costs and the level of deterioration at which a bridge deck is replaced.

The investigation presented in this paper considers the temporal and spatial characteristics of directional distribution of traffic on rural highways. A total of 60 highway locations, representing a wide range of traffic‐stream characteristics, were investigated. The results of this study clearly indicate that directional distribution varies from hour to hour during the day, day to day and month to month during the daily peak volume hours, and from one road type to another. In general, directional distribution does not remain stable even during the highest‐volume hours of the year. A sensitivity analysis was carried out to study the effect of changes in the value of design directional split on the number of highway congestion hours in a year. It was also found that, in some cases, the current practice of taking the value of directional split during the design hour as the design directional split can result in very large errors of estimates. A method was developed in this study to determine the design directional split for use in highway traffic analysis.