Technology already exists to capture and communicate a variety of information from motor vehicles. Automobiles are equipped with sensors and can reliably report their location, velocity, and condition via cellular telecommunications. Truck location tracking with global positioning systems is common, and prototype systems exist for characterizing surrounding traffic and roadway conditions. Given these advancements, we expect that future motor vehicles will be capable of reporting a wide variety of information about their own condition and the local environment, including the condition of the infrastructure on which they travel. Many uses exist for the vehicle- and infrastructure-related information that can be transmitted from motor vehicles. For example, fleet operators can take advantage of this information for better management of their own fleet, subject to privacy agreements with their own drivers. Similarly, this information can be used for traffic control purposes to improve travel times and safety. Even though it is becoming technologically feasible to use motor vehicles to transmit a variety of information collected through sensors, social, technical, and organizational barriers exist currently that limit the availability of this information mostly to the private use of the motor vehicle and drivers. In this paper, we describe our vision of how motor vehicle information and communications technology can be exploited for transportation engineering. We also discuss the social, technical, and organizational barriers that need to be overcome to achieve this vision.

This paper presents an improved algorithm for matching individual vehicle measurements at a freeway detector station with the vehicles’ corresponding measurements taken at another detector station located upstream. The improvements consist of four new tests to identify incorrect matches and either replace them with the correct matches or discard the errors. The result is a higher number of reidentified vehicles with a lower frequency of errors compared to our earlier work. Although this algorithm is potentially compatible with many vehicle detector technologies, the paper illustrates the method using existing dual loop detectors to measure vehicle lengths. Due to the limited accuracy of the existing loop detector measurements under free flow conditions, this presentation is restricted to matching vehicles during congested traffic conditions. The algorithm is applied to individual lanes and exploits information about the sequence that vehicles pass the detectors. As such, the effect of vehicles changing lanes between stations is also considered in this paper. Of course once a vehicle has been matched across neighboring detector stations, the difference in its arrival time at each station defines the vehicle’s travel time on the intervening segment. Thus, the algorithm extracts travel time data without requiring the deployment of new detector technologies. The approach described herein has been extensively tested on I-80 in the Berkeley Highway Laboratory (BHL). This paper presents some of the results obtained over two different segments of the BHL and demonstrates that the algorithm matches a sufficient number of vehicles for the purpose of travel time measurement.

The work zone capacity cannot be described by any mathematical function because it is a complicated function of a large number of interacting variables. In this paper, a novel adaptive neuro-fuzzy logic model is presented for estimation of the freeway work zone capacity. Seventeen different factors impacting the work zone capacity are included in the model. A neural network is employed to estimate the parameters associated with the bell-shaped Gaussian membership functions used in the fuzzy inference mechanism. An optimum generalization strategy is used in order to avoid over-generalization and achieve accurate results. Comparisons with two empirical equations demonstrate that the new model in general provides a more accurate estimate of the work zone capacity, especially when the data for factors impacting the work zone capacity are only partially available. Further, it provides two additional advantages over the existing empirical equations. First, it incorporates a large number of factors impacting the work zone capacity. Second, unlike the empirical equations, the new model does not require selection of various adjustment factors or values by the work zone engineers based on prior experience.

An adaptive computational model is presented for estimating the work zone capacity and queue length and delay, taking into account the following factors: number of lanes, number of open lanes, work zone layout, length, lane width, percentage trucks, grade, speed, work intensity, darkness factor, and proximity of ramps. The model integrates judiciously the mathematical rigor of traffic flow theory with the adaptability of neural network analysis. A radial-basis function neural network model is developed to learn the mapping from quantifiable and nonquantifiable factors describing the work zone traffic control problem to the associated work zone capacity. This model exhibits good generalization properties from a small set of training data, a specially attractive feature for estimating the work zone capacity where only limited data is available. Queue delays and lengths are computed using a deterministic traffic flow model based on the estimated work zone capacity. The result of this research is being used to develop an intelligent decision support system to help work zone engineers perform scenario analysis and create traffic management plans consistently, reliably, and efficiently.

This paper presents a study of two important roundabout performance issues: (1) the impact of the waiting time of drivers on the approach leg, on the critical gap they accept before entering a roundabout and (2) the entry capacity of the approach. The main hypothesis is that an increase in drivers’ average waiting times reduces the average accepted gap and, consequently, the critical gap. A model for a change in the critical gap at busy roundabouts, with long approach queues and long waiting times, is provided. The model for a change in the critical gap was found to be logistic; i.e., it had an s-shape between a maximum and a minimum critical gap. The parameters of each site studied in the present investigation were found to correlate in regard to geometric complexity and traffic intensity. The parameters were the outside diameter, pedestrian volume, and circulating flow of vehicles around the central island. A reduction in the critical gap because of increased waiting times results in a significant increase in entry capacity, which is particularly significant in high circulating volumes. A model for the entry capacity that depends on the circulating flow, the outside diameter, and the critical gaps (which, in turn, depend on the waiting times) was calibrated and presented. This model was found to be sensitive in high circulating volumes to the critical gap; and in low circulating volumes, to the geometry, represented by the outside diameter. The use of this model is recommended when estimating the entry capacity of either new or existing roundabouts.

In this paper we propose a new model showing how genetic algorithms can be manipulated to help optimize bus transit routing design, incorporating unique service frequency settings for each route. The main lesson is in the power that can be given to heuristic methods if problem content is exploited appropriately. In this example, seven proposed genetic operators are designed for this specific problem to facilitate the search within a reasonable amount of time. In addition, headway coordination is applied by the ranking of transfer demands at the transfer terminals. The model is applied on a benchmark network to test its efficiency, and performance results are presented. It is shown that the proposed model is more efficient than the binary-coded genetic algorithm benchmark, in which problem content cannot be utilized.

As accelerated pavement testing (APT) devices emerge as possible candidates for a supplemental performance test, questions related to the ability to assess resistance of hot mix asphalt to permanent deformation under full-scale trafficking remain. Toward addressing this question, performance data under full-scale trafficking collected for several replacement sections at WesTrack were compared with test results for mixtures fabricated in the laboratory using WesTrack materials and tested at a critical temperature for permanent deformation. The asphalt pavement analyzer (APA) and repeated simple shear test at constant height (RSST-CH) were validated as useful APT tools by comparing measured field performance and laboratory predicted performance of laboratory mixed-laboratory compacted specimens at field (in-place) air void and asphalt contents. Test results from the APA and RSST-CH showed good agreement with downward rut depths measured under full-scale trafficking. Based on a simple statistical analysis, the APA test can be used to assess adequate rutting performance. Rutting performance was also assessed by determining the expected number of design equivalent single axial loads (ESALs) for each section from relationships between permanent shear strain in the RSST-CH and ESALs in the field. Both APT devices demonstrated the ability to differentiate between mixtures with good and poor rutting performance.

With increasing use of modified asphalt binders, the correct compaction temperature range for asphalt mixtures containing these binders needs to be determined. The current procedure uses asphalt binder viscosities to determine the compaction temperature range. However, the current procedure often provides unacceptably high temperatures for modified binders. Past work showed that lower temperatures can be used and that the volumetric properties of Superpave gyratory-compacted specimens can be the same over a very wide range in compaction temperatures, even when the mixtures are short-term oven aged at the compaction temperature. However, that study did not examine the effect of temperature on the internal characteristics and mechanical properties of the mixtures. The present study addressed these issues for one of the mixtures used in the previous study. The shear properties of the mixture compacted at four temperatures were evaluated. These properties improved to some extent with an increase in temperature, except for strain-controlled fatigue damage, which did not change significantly with temperature. The effect of temperature on aggregate orientation and the effect of aggregate orientation on shear properties were also investigated. Based on these analyses, a narrower range of optimum compaction temperatures was found compared to the range based on volumetric properties alone. The changes in the shear stiffness of the asphalt binder, in the vertical air void distribution, and in the preferred orientation of the aggregates with compaction temperature were the responsible factors for the changes in mixture shear properties.

Fly ash is a waste produced in coal-fired thermal power stations. It has pozzolonic properties and can therefore be stabilized with either cement or lime to achieve the strength required for use as base courses in pavements. Agencies such as the Electric Power Research Institute (EPRI) have specified criteria and guidelines for the determination of the stabilizer content. This requires carrying out unconfined compression tests on stabilized fly ash specimens prepared and cured as per standard procedures. The stabilizer content is the minimum amount of the stabilizer for which the unconfined compressive strength of the specimens complies with the specified values. The actual curing conditions of the stabilized fly ash bases in the field, however, will differ from those of the laboratory specimens. This will affect the strength development of the bases, their durability, and their performance. The paper explains the details and results of a laboratory experimental program carried out to study the influence of curing conditions and other factors on the development of strength. The program comprised compaction tests and unconfined compression tests. Two Indian fly ashes and a commercial portland cement were used in the study. Six different curing conditions, including controlled and ambient conditions, were adopted. The influence of differences in the dry unit weight and water content was also investigated.

A series of linear-elastic plane-strain finite-element analyses were conducted on a newly developed fiber optic traffic sensor whose potential uses include traffic classification and weigh-in-motion. These sensors have performed well in the pavement when placed in six-foot-long narrow vertical grooves. The objective of this research was to determine how the sensor functions in this vertical configuration. Results from three finite-element models were correlated to laboratory and field results showing that the pavement groove closes, thereby squeezing the sensor as tires load the pavement around it. As the fiber optic sensor deforms, the intensity of the light passing through the fiber decreases, allowing roadside computer systems to use this intensity for vehicle classification or weigh-in-motion. Laboratory testing of sensors was performed pneumatically to simulate tire pressures, enabling comparable load, optical light intensity, and deflection data to be obtained for bare and encapsulated sensors. In the field, load-deflection data from falling weight deflectometer testing was used to validate the finite-element modeling.

This research presents the test results of a laboratory and field study performed to investigate the characteristics and performance of dry and wet recycled concrete aggregate (RCA) as base and subbase materials for concrete pavement. The physical properties of the RCA were investigated in terms of the moisture-density relationship, particle index, and fine aggregate angularity. Performance concerns have focused on compactibility, stability, shear resistance, and particle breakage of the RCA. These were evaluated in the laboratory using the U.S. Army Corps of Engineers Gyratory Testing Machine. The falling weight deflectometer was used to measure the deflection of pavement sections constructed with RCA base and subbase in the subbase material and may be comparable to crushed stone aggregate.

In highway projects, economic considerations are as important as other design controls and elements of design. As a result, the highway designer should consider cut and fill balance along with minimizing earthwork which may significantly decrease construction costs. In practice, one way to reduce the amount of earthwork is to set the grade line as closely as possible to the ground line while also considering cut and fill balance. However, this practice may be misleading since balancing is achieved along the centerline of the road. In reality, the centerline ground elevation rarely represents the whole cross section in terms of cut and fill balancing. Especially in mountainous terrain, transverse changes in ground elevation with respect to the centerline elevation of cross section are abrupt. The aim of this paper is to propose a method that considers a hypothetical “weighted ground elevation” representing the average of transverse changes in the ground elevation rather than the elevation at the centerline. Consequently, conforming the grade line to the weighted ground line (integration of the weighted ground elevations along the centerline) would give balanced cut and fill and lesser amount of earthwork, resulting in a much more cost effective result.

This paper reports findings from recent investigations into freeway capacity at several reconstruction zones in Ontario, Canada. The aim is to provide guidelines for estimating freeway capacity at reconstruction sites. Findings are presented in two parts. The first involved results of individual investigations to estimate a base capacity at freeway reconstruction sites and the individual effect of several important factors that are believed to affect this capacity, namely; the effect of heavy vehicles, driver population, rain, site configuration, work activity at site, and light condition. In the second part, attempts to model work zone capacity are presented. Initially, two types of “site-specific” capacity models were developed using different analytical techniques at sites that have the most extensive and comprehensive capacity data. Finally, a “generic” capacity model for freeway reconstruction sites is proposed based on results from the individual investigations and the site-specific models. The proposed model suggests a base capacity value of 2,000 passenger cars per hour per lane for reconstruction sites under favorable conditions. Heavy vehicles and driver population were found to have the most significant effect on capacity.