This paper presents deterministic models for estimating airspace and airport capacity and delays during equipment outages. The National Airspace System (NAS) is very complex and consists of almost 48,000 reportable facilities and services that support air traffic control with very diverse functions and technologies. To better understand NAS performance and develop a methodology for estimating degraded capacity, previous studies about equipment outages and about airspace and airport performance are first reviewed. A deterministic aircraft separation model is used to estimate degraded capacity. It is useful for quick estimates of the number of aircraft operations per facility under some predefined conditions (i.e., mile-in-trail separation and aircraft mix), but does not estimate delays. A deterministic queuing approach is used for estimating delays due to single outages for a hypothetical airport and terminal airspace area. It can also estimate the number of aircraft experiencing queuing and the queue duration, while considering arrival and service rates that vary over time.

Determination of a runway orientation is a critical task in the planning and design of an airport. The direction of the runway controls the layout of the other airport facilities, such as passenger terminals, taxiways/apron configurations, circulation roads, and parking facilities. This paper presents a geographic information systems (GIS)-based system called airport runway optimization (ARO) that determines the best runway orientation for the effective layout of airport facilities. The paper first provides an overview of the previous research efforts with regards to runway orientation and investigates Federal Aviation Administration standards, wind conditions, airspace obstructions, topographic settings, and other factors that apply to runway design. It then addresses a GIS-based wind rose method that automates the determination of runway placement. The ARO system uses the GIS-based wind rose method and customized GIS functions and database management tools to successfully solve the “partial coverage” problem. The ARO system significantly improves the current efforts of using “trial and error” and computation-intensive methods to determine runway alignment.

In a disaster situation, road networks play a critical role in maintaining routes for evacuation and logistics. In the event of a catastrophic disaster such as an earthquake, part of the road network may be easily broken into isolated components. In this situation, it is critical that individuals in each district have access to vital facilities in their local neighborhood so that no district is isolated. In this paper, we propose using a topological index (TI) to quantify road network dispersiveness/concentration. Dispersiveness/concentration evaluated by the TI is a valuable approach to evaluate the isolation of districts in a city. We used the index to evaluate dispersiveness/concentration of a road network in the Hanshin region in Japan, which experienced severe damage in the 1995 Hanshin-Awaji Earthquake. In order to construct the graph for calculating TI, we also present the methodology for specifying effective road links for avoiding functional isolation of districts.

A common travel analysis technique is to ascribe capacities to links in a planning network based on functional classification or facility type, under which a four-lane divided arterial, for example, would be assigned the same capacity everywhere, irrespective of the surrounding land use, the presence of traffic signals, and whether turning lanes are provided or not. While this practice has been used for many years and is typically adequate for the analysis of large road networks, there are penalties (in terms of lost accuracy) that accompany its use. The objective of this research was to evaluate different techniques to determine what information was necessary to reasonably estimate link capacity while decreasing the time, effort, and cost of data collection. It was found that assigning capacities on a link-specific basis produced significant differences when compared to the practice of assigning average capacities, suggesting that travel demand modeling could be improved by using link-by-link estimates of capacity. The results of this study also supported the concept that improvements gained by using all Highway Capacity Manual adjustment factors were marginal compared to the improvement achieved by including only the $g/C$ ratio and number of lanes; suggesting further that ignoring other factors like lane widths, heavy vehicles, turning movements, etc. will still result in reasonably accurate estimates of volume, travel time, and travel speed.

An emerging technology known as wireless location technology has been developed to allow mobile wireless devices (the most common of which are cellular telephones) to be geolocated. Over the past decade, a number of research studies and operational tests have attempted to develop probe-based traffic monitoring systems using wireless location technology, but there still exist significant misperceptions concerning its capabilities. To address this problem, in this paper we seek to provide an assessment of wireless location technology-based traffic monitoring. The specific purposes of this paper are to (1) describe the concept of wireless location technology-based traffic monitoring, (2) present a critical assessment of past studies of this technology, (3) document the evaluation of one of the most recent operational tests—the 2001 Virginia Department of Transportation, Maryland State Highway Administration, and U.S. Wireless Corporation effort in the Washington, D.C., region, and (4) discuss the challenges that these systems pose to traffic engineering.

This paper is concerned with implementation challenges related to using dynamic traffic assignment on actual large urban networks. Such challenges include the manipulation of network and demand data, the modeling of turning movements, the efficient computation of link travel times, and the handling of complex path data. The basic simulation-assignment based approach introduced by Mahmassani et al. in 1993 was enhanced to address the challenges outlined above. The model is used on applications presently performed by agencies with static transportation planning models, such as infrastructure improvements, demand management, and congestion pricing. In addition, various applications that are difficult to perform with static models are explored, such as the evaluation of Intelligent Transportation Systems technologies. Computational tests are performed on the Columbus, Ohio urban network and the results are analyzed.

Traffic adaptive control for oversaturated intersections (TACOS) is a hybrid optimization and rule-based strategy that addresses weaknesses of existing adaptive control strategies by having attributes such as: (1) the information used for decision-making is not dependent on forecasts; (2) intersection utilization is used explicitly in the objective function; (3) phase sequencing is optimized; and (4) operational anomalies are detected and responded to. A new intersection simulator that emulates NETSIM, INTEGRATION, and TACOS was developed to compare TACOS with pretimed and actuated control strategies. Demand scenarios consisted of light to heavy flow, cyclical arrivals, and arrivals with an upstream incident. Throughput-to-demand ratio, speed, delay, queue time, and percent stops were examined. Traffic adaptive control for oversaturated intersections showed significant improvements over pretimed and actuated control in terms of all examined measures of effectiveness under all flow scenarios. Demanding parameter specifications required in other adaptive control strategies are unnecessary in TACOS.

The increasing use of roundabouts for plane junctions calls for an evaluation of the potential accident rate for this kind of intersection. This gives a further element for the choice between alternative typologies of intersection for the requalification and the adjustment of road junctions. This paper presents a model for the potential accident rate evaluation in large and medium roundabouts. The model is based on dynamical considerations and on the user’s behavior crossing the intersection. The model’s response to the traffic conditions in the intersection and to capacity formulations is also analyzed.

Horizontal reverse curves are used in all types of highways either in mainline alignments or in freeway interchange ramps. At present, minimum radius requirements for reverse curves are determined based on vehicle performance on each arc of the reverse curve individually without giving any consideration to the nature of the reverse curvature. This paper determines the required minimum radius for reverse curves on freeway mainlines based on vehicle stability using computer software to simulate truck behavior on different alignments. It was found that an increase to the minimum radius requirements of horizontal reverse curves is required to maintain the driver comfort levels suggested by design guides and to prevent potential rollover. That increase ranges from 8.3 to 28.8% depending on the geometric configuration of the highway as well as on the design vehicle. The design guidelines developed for horizontal reverse curves should be useful in improving road safety on highways, especially for freeway interchanges.

There is a growing need for automated procedures that can update road databases in Geospatial Information Systems (GIS). Such procedures are in a great demand when the GIS database needs to be updated very frequently and should comprise automated means for extracting road data from satellite images and updating GIS databases using the collected data. In this paper, the requirements for developing an automated procedure which (1) extracts road data from high-resolution satellite images and (2) prepares the extracted data for use in GIS is presented. The procedure includes a region growing algorithm to obtain road features, an edge detection algorithm, an image enhancement algorithm, a vectorization algorithm, and a georeferencing algorithm. The edge detection, image enhancement and vectorization algorithms are tested using three different high-resolution satellite images and the results are presented. Their performance is measured and analyzed individually.

The proliferation and increased precision of global positioning system (GPS) devices enable the technology to be used in new and innovative applications. In the past few years, the Kansas Department of Transportation collected spatial data on a highway system using annual GPS surveys. This research deals with the problem of handling very large amounts of geographical data (latitude, longitude, elevation, and additional attributes) that are not entirely consistent. This paper describes the methodology for cleaning up this large amount of data, condensing it, and generating a B-spline approximation of the highway. This data mining effort results in two separate two-dimensional models of the highway, represented as B-spline curves. The highway approximation methodology is validated using a comparison between the B-spline approximation and the actual design data for the highway.

Under near-saturated or saturated conditions, the optimal cycle length formulation proposed by Webster becomes infeasible because (1) it generates an unreasonably large cycle length as the intersection critical flow ratio approaches one, and (2) it becomes inapplicable if the intersection critical flow ratio is equal to or greater than one. An attempt is made here to rectify this deficiency by providing a simplistic but reasonably accurate formulation for optimal cycle length under saturated conditions. Using the optimal timing variables obtained based on the delay minimization criterion, the functional relationship between optimal cycle lengths and traffic flow parameters, including intersection critical flow ratio, total lost time, and duration of analysis period, is established through a nonlinear regression analysis. The resulting formulation generates fairly accurate estimates of optimal cycle length with 5.7% average deviation from the analytical solutions. The corresponding average delay, however, only deteriorates about 0.9%. The timing plans consisting of the proposed optimal cycle estimates and the equalized degree-of-saturation green splits produce near-optimal delay performance with 3.3% degradation from the optimal solutions.

This paper presents an investigation into the different factors that affect sign occlusion by large-dimension vehicles on multilane highway facilities. Parametric analyses were conducted to explore these effects using a simulation model that was developed specifically for this research. The variables investigated involved legibility distance, maximum divergence angle, average speed of passenger cars, relative speed of trucks with respect to passenger cars, lateral offset of traffic sign, number of words in message, traffic level, and percentage of large-dimension vehicles. In general, research results show that the occlusion of ground-mounted traffic signs by larger vehicles is remarkable for conditions that can be described as typical. Also, results suggest that the factors that have most important effect on sign occlusion involve legibility distance, average speed of passenger cars, relative speed of trucks with respect to passenger cars, and number of trucks on the lane of interest.

The objective of this study was twofold: (1) quantify the benefits of a specially designed geocomposite membrane [a low modulus polyvinyl chloride (PVC) layer sandwiched between two nonwoven geotextiles] to act as a moisture barrier in flexible pavement systems; and (2) quantitatively measure the moisture content of unbound granular materials nondestructively. The geocomposite membrane was installed over half the length of a pavement test section at the Virginia Smart Road, while the other half of the test section consisted of the same design without the interlayer system. An air-coupled ground penetrating radar (GPR) system with 1 GHz center frequency was used to monitor and detect the presence of moisture within the pavement system over different periods of time corresponding to different levels of water accumulation. Results of GPR data analysis indicated that the use of the geocomposite membrane reduced water infiltration to the aggregate base layer by as much as 30% when measurements were performed after rain. It was also found that the moisture content underneath the interlayer was almost constant and therefore independent of the amount of rainwater, which is the primary source of moisture in pavement systems that have a low water table. The impact of moisture in the granular layers was investigated using the results of a deflection monitoring program. The results indicate that the area with the geocomposite membrane always showed less deflection than the area without the interlayer. The study recommends that any pavement drainage layer must be backed by an impermeable interface, given that the water table is low.

The paper reports the results of several repeated load triaxial tests performed on a crushed rock aggregate at different stress levels. The development of the resulting permanent deformation that accumulates with the repeated loading is described and compared with the types of responses usually described by the shakedown approach. It is shown that the existing shakedown approach can describe some, but not all, of the observed responses. Thus a modified set of possible responses is defined in shakedown terms and some explanations of the differences from the conventional approach are given. The elastic shakedown limit can be used to predict whether or not stable behavior occurs in the unbound granular material layer of a pavement construction or whether rutting will occur. With this information a pavement’s granular base may be dimensioned. The elastic shakedown limit of a Granodiorite has been used in this manner and the resulting design compared with an empirical German design procedure. The paper concludes with an assessment of the benefits and limitations of the new approach.

Past research has shown that the concept of $C-\varphi$ (cohesion and angle of friction) can be applied for asphalt paving mix design. It has also been established that the $C-\varphi$ model is able to analyze the behavior of asphalt pavement under load, thereby permitting the incorporation of mechanistic or semimechanistic distress models into asphalt mix design as well as pavement thickness design. Therefore the $C-\varphi$ concept offers a useful basis for an integrated procedure for asphalt paving mix design and asphalt pavement design. This paper further illustrates the usefulness of the $C-\varphi$ based approach by developing a rutting prediction model based on the $C-\varphi$ model. The proposed rutting prediction model employs the widely adopted expression of power relationship as the basic equation for prediction of cumulative damage. The basic expression is modified by incorporating the following effects: (1) the effect of load through a stress ratio computed using the $C-\varphi$ concept, (2) the effect of temperature, and (3) the effect of loading speed. The applicability of the model is demonstrated using laboratory wheel tracking tests on three different mix types. A proposed procedure of applying the rut depth prediction model for estimation of rut depths in in-service pavements is also outlined.