This paper provides a comprehensive guide to the design of shared facilities. Shared facilities serve many users (aircraft, airlines, or types of services) in several functions (arrivals, departures, international and domestic, and so on). They significantly increase the utilization of facilities, thus reducing the amount needed for any level of traffic. They also increase the flexibility of the building, thus enabling it to accommodate easily to variations in traffic composition (the fractions associated with specific airlines or international and domestic services). Shared facilities reduce capital expenditures by up to 30%, and correspondingly increase the return on the investment. Two main factors motivate the use of shared facilities. One is peaking; that is, variations in the levels of traffic (either in hours or a day). The other is uncertainty in the timing of the traffic (either in the short run or in the long run). The paper details the appropriate analyses in each instance. It presents analytic results showing that the design of passenger buildings should normally include shared space, swing gates, and shared facilities that buffer uncertain demands.

This paper uses a novel analysis to define the optimal configuration of airport passenger buildings for travelers. The approach explicitly recognizes two significant practical facts omitted in previous work—(1) the importance of transfer passengers, who may comprise 50% or more of the travelers; and (2) the way airlines intelligently position aircraft at gates to minimize the walking distances between connecting flights. The analysis breaks the issue of finding the walking distances of travelers into two parts. The “impedance” matrix defines the distance or level of difficulty in transiting between gates and results from architectural considerations. The “flow” matrix defines the number of passengers going between gates. Multiplication of these matrices results in a “passenger-impedance” matrix that defines the distribution of walking distances or travel time for travelers. Comparison of these distributions shows the relative advantage of different configurations. Results suggest that from the perspective of the travelers, intelligently managed linear midfield concourses generally provide the best overall configuration for significant airport passenger buildings.

Parallax error is a distance-related measurement error when the measurement has to rely on field of view, such as video-image systems. This paper provides a detailed investigation of the geometric elements associated with parallax error in video-image systems. A field-of-view calibration model is presented based on a study of various geometric elements, including camera height, camera location, view of image, and vehicle dimension. The study found that parallax error ranges between 10 and 50% based on normal camera setup. The model presented provides a better understanding of the parallax error; thus the accuracy of distance-related measurements could be improved when video-image systems are deployed. The proposed model has special application values at signalized intersections where video-image systems are deployed. One of the applications is to identify the range of possible blockage by a leading vehicle, which is one of the major causes of missed detections. Another application is to identify the conditions that result in vehicle occlusion, which is a source of false detections.

A critical element in assessing traffic performance at the individual lane level at signalized intersections is the knowledge of traffic volumes in each lane. Typically, turning movement volumes are available only for the entire approach, not for each individual lane. Collecting turning movement volumes by lane is costly and, for future year analyses, is unattainable. This paper summarizes the results of an empirical study of lane volume data that were collected at three intersections and provides an evaluation of six lane selection strategies used to estimate lane flows. The lane selection strategies are used as part of the subgroup approach for estimating saturation flow. This limited evaluation indicates that a lane selection strategy based on equal back of queue or cycle-average queue provides the best prediction of individual lane volumes in the field. This result is intriguing, given that at least three international capacity guides currently use an equal flow ratio or degree of saturation strategy for estimating lane flow and indicates a need for a larger data collection effort to confirm the results of this study.

Automatic freeway incident detection is an important component of advanced transportation management systems (ATMS) that provides information for emergency relief and traffic control and management purposes. Earlier algorithms for freeway incident problems have produced less reliable results, especially in recurrent congestion and compression wave traffic conditions. This article presents a new two-stage single-station freeway incident detection model based on advanced wavelet analysis and pattern recognition techniques. Wavelet analysis is used to denoise, cluster, and enhance the raw traffic data, which is then classified by a radial basis function neural network. An energy representation of the traffic pattern in the wavelet domain is found to best characterize incident and nonincident traffic conditions. False alarm during recurrent congestion and compression waves is eliminated by normalization of a sufficiently long time-series pattern. The model is tested under several traffic flow scenarios including compression wave conditions. It produced excellent detection and false alarms characteristics. The model is computationally efficient and can readily be implemented online in any ATMS without any need for recalibration.

The population of the U.S. is aging, and the number of older persons licensed to drive keeps increasing. With the aging population and increase in the number of older licensed drivers, addressing safety issues related to older drivers is becoming more crucial every day. This paper reports on the analysis of 1990–1999 crash data from the State of Iowa in which an older driver (age ⩾65 years) was injured. The main focus of the study was to isolate factors that contribute to more severe injuries to older drivers involved in traffic crashes. The ordered probit modeling technique was used to investigate factors from vehicle, roadway, driver, crash, and environmental characteristics that can potentially contribute to older driver crash injury severity. Model findings were primarily as expected. New findings from this study were that older drivers who consumed alcohol were more likely to be seriously injured and older driver injuries in farm vehicles were more severe as compared with other types of vehicles. The writers discuss implications of the findings for the safety of older drivers.

This paper presents a state-of-the-art review of recent developments in three-dimensional (3D) analysis for transportation planning and highway design. As background, the concept of dimension is briefly discussed and examples of transportation-related disciplines are given in zero, one, two, three, and four dimensions. Two types of 3D models are described: visualization models and analytical models. Transportation planning applications include system planning (e.g., data collection modeling), corridor/project planning (e.g., traffic calming), and environmental analysis (e.g., air quality assessment). Highway design applications include route planning (e.g., preliminary route selection), geometric design (e.g., combined alignment), and structural design (e.g., pavement design). This paper is sponsored by the ASCE Urban Transportation Division’s Planning Committee and the Highway Division’s Geometric Design and Operations Committee. By summarizing current and emerging developments of 3D analysis in transportation, the committees hope to raise awareness of this powerful tool and to help stimulate its applications in other transportation areas.

This paper investigates a number of issues associated with jointly estimating disaggregate logit mode choice models for two periods using data collected at two points in time in independent cross-sectional travel surveys in a given urban area. These include: (1) the effect socio-economic characteristics of travelers have on the predictive and forecast performance of jointly estimated models; and (2) the effect of allowing the variance of the random utilities in the different time periods to differ and, more broadly, the impact transfer-bias scale parameters could have on joint-model predictive performance. The results show that well-specified jointly estimated models using data from two time periods yield comparable disaggregate and aggregate forecasts to those obtained from conventional forecasting models, estimated with data from a single cross-sectional survey. Socio-economic variables and transfer-bias scale parameters are found to enhance model fit to estimation data as well as precision of predictions. The shorter the intervening period between when the two cross-sectional data sets used in joint estimation are collected, the better the jointly estimated models are able to predict the travel choices in each of the survey years.

This paper explores the potential applications of rough set theory and neural networks in concrete-faulting-performance modeling. The rough set can be used to reduce the dimension of the original pavement database in terms of attributes and rows. The reduced table can then be used as an input into the neural network. Since there are no universal rules for neural network construction, this approach is very important. Constructive and destructive methods have been used in the construction of neural network architecture. Although these methods are appropriate, they do not have a strong scientific proof. The key characteristics of the proposed method is that the new decision table created by using the rough set analysis will free the neural network paradigm from redundancy. A simple example for faulting performance in concrete pavement is presented.

The objective of this study was to consider evaluation methods for intelligent transport system (ITS) investments, to point out some shortcomings of traditional methods (mainly benefit-cost analysis), to develop alternative methods, and to make recommendations for how the profitability of ITS investment should be evaluated. The results can be used when ITS investments are compared with each other and also when ITS investments are compared with road building investments. This work identifies the fundamental differences between ITS and road infrastructure investments and how they impact on the profitability evaluation. The conclusion is that traditional cost-benefit analysis (BCA), which was developed for investments in physical infrastructure, does not capture all the benefits or costs related to ITS. Economic evaluation methods for ITS investments need improving. This work illustrates how BCA could be used to take into consideration the option value of ITS investment and risks caused by, for example, different time horizons of investments. The work also discusses and demonstrates the use of multicriteria analysis in profitability evaluation. It illustrates how a method called analytical hierarchy process could be utilized to evaluate other risks that do not have specific monetary values and to compare the results of different profitability analyses. These evaluation methods can be used within the project assessment framework in the transport sector to highlight different aspects of the profitability and efficiency of transport investments. None of the methods themselves can reflect all aspects in decision making, but by using a suitable set of different methods depending on the decision situation and by comparing the results, a wider and more realistic picture of investments can be obtained.

A new box-beam guardrail end terminal, known as the box-beam bursting energy absorbing terminal (BEAT), was designed and shown to meet current United States impact safety standards according to guidelines provided by the National Cooperative Highway Research Program (NCHRP). The BEAT is placed on the end of a box-beam guardrail system. When impacted by an errant vehicle, the head of the BEAT pushes down the box-beam rail causing the rail to expand and burst at the corners at a desired energy absorbing rate. Details of the bursting concept are provided along with descriptions of the new terminal and the performed crash tests. Three crash tests were needed to qualify the BEAT terminal according to Test Level 3 evaluation criteria provided by the NCHRP.

Rapid growth in arid and semiarid regions has brought increased focus on volume change characteristics of moisture sensitive unsaturated soils. One such soil type of concern is collapsible soil. There are numerous reports of pavement problems resulting from soil wetting-induced collapse. The purpose of this paper is to review methods for detecting moisture sensitive collapsible soils and to explore the value and feasibility of various testing and evaluation methods and mitigation alternatives for highway design applications. Findings on site variability for several collapsible soil deposits are presented. The advantages and disadvantages of laboratory and in-situ direct response to wetting tests are discussed. The advantages and limitations of qualitative and nondestructive methods for assessing soil collapsibility are also addressed.