Traffic flow rate, the equivalent hourly rate of vehicles passing a point during a given time interval, is a fundamental measure of traffic status that plays a critical role in many aspects of transportation engineering. The time interval used in measuring the flow rate, defined as the measurement interval, is influential in the characteristics of flow rate measures. In fact, the Highway Capacity Manual recommends that transportation engineers use a minimum of 15-min measurement intervals in order to ensure “stable” traffic flow rates. In addition, numerous researchers have commented about the lack of stability of flow rates resulting from short measurement intervals. However, there is not a quantitative understanding of the impacts of short (less than 15 min) measurement intervals on traffic flow rate. This paper presents the results of a study using nearly 30,000 flow rate measurements collected at multiple freeway locations to quantify the impact of measurement interval. It was found that stable freeway flow rates may be calculated using measurement intervals as short as 10 min, and that statistically significant improvements in stability can be achieved by adding 2 min to any measurement interval.

A new freeway work zone traffic delay and cost optimization model is presented in terms of two variables: the length of the work zone segment, and the starting time of the work zone using average hourly traffic data. The total work zone cost defined as the sum of user delay, accident, and maintenance costs is minimized and the number of lane closures, darkness factor, and seasonal variation travel demand normally ignored in prior research are included. To find the global optimum solution, a Boltzmann-simulated annealing neural network is developed to solve the resulting mixed real variable–integer cost optimization problem for short-term work zones. The new model can be used as an intelligent decision support system to (1) find the optimum work zone segment length and optimum starting time; (2) study the impact of various factors such as number of lane closures and darkness; and (3) quickly observe the relation between the total work zone cost and the work zone segment length and starting time in a quantitative and rational way.

A policy of building frontage roads alongside freeway mainlanes avoids the purchase of access rights when upgrading existing highways to freeway standards and can supplement local street networks. It also may affect corridor operations, land values, and development patterns. The purpose of this paper is to provide a comprehensive evaluation of frontage-road design policies by (1) summarizing research results related to legal statutes affecting public access to roadways, (2) discussing access policies and practices across the states, (3) comparing land development and operations of corridors with and without frontage roads, (4) summarizing studies on access-right valuation, and (5) comparing total construction costs. In a literature review, a wide variety of options are available to agencies for limiting access to and improving flow and safety along freeway corridors. In statistical analyses of paired corridors, land near frontage roads is associated with lower household incomes, lower population densities, lower percentages of bike trips to work, lower vehicle occupancies for work trips, and higher unemployment rates than those without frontage roads. Lower employment densities along freeway corridors also emerged when frontage roads were present. Operational simulations of various freeway systems demonstrated that frontage roads may improve the operation of freeway mainlanes in heavily developed areas but not in moderately developed areas (e.g., mainly residential). Arterial systems in these simulations were supplemented by frontage roads and thus also performed better. The financial costs associated with frontage road facilities were considerably higher than those associated with non-frontage-road facilities, except in cases of extremely high access-right-of-way values. These results, in addition to efforts by other researchers, should assist in constructing a solid, formal policy for all states and regions to follow in providing access along new and existing freeways in the future.

A simulation model incorporating determination of a dynamic dilemma zone and algorithms to determine gate operation parameters for train-vehicle collision avoidance at highway-rail intersections (HRI) is developed, validated, and applied to two crossings on the Chicago-St. Louis High Speed Passenger Rail Corridor. A dynamic dilemma zone, as opposed to a static dilemma zone, is a road segment on approach to an intersection, which varies in length based on fluctuations in vehicle speeds and the number of vehicles within a road segment. Findings from the system simulation indicate that the proposed operating policy of control devices at highway-rail intersections is appropriate to provide advance warning and theoretically, detection parameters for eliminating high risk of a collision between vehicles within a dynamic dilemma zone and a train. Application to intelligent transportation system safety algorithms for HRI should be considered.

This paper provides a hierarchical framework for studying the impact of traveler information on network reserve capacity. The framework comprises a two-level mathematical program—the upper-level program maximizes the reserve capacity multiplier subject to a link capacity constraint, and the lower-level program generates user equilibrium flow patterns under the influence of traveler information. The two-level program is solved by a genetic algorithm-based solution method. Numerical results indicate that the reserve capacity of a road network does not increase monotonically with the increase of information level. The implications of this finding, including its dependence on the characteristics of the road network, are discussed.

In Hong Kong, the annual traffic census report is published in the middle of the year and used to present the results of traffic volume recorded at the automatic traffic counter stations. The type of traffic volume data being widely used is the annual average daily traffic (AADT), which is estimated on the basis of the daily flows by 12 months in the whole surveyed year. In this paper, time series, neural network, nonparametric regression, and Gaussian maximum likelihood (GML) methods were adapted to develop four models for short-term prediction of the daily traffic flows by day of week and by month, as well as the AADT for the whole current year. The historical data (1994–1998) and available current-year data for 1999 partial daily flows are the input data used for model development. The results of the four models were compared with the real data for validation. The daily flows estimated by the four models were used to calculate the AADT for the current year of 1999. Based on the comparison results, the GML model appears to be the most promising and robust of these four models for extensive applications to provide the short-term traffic forecasting database for the whole territory of Hong Kong.

The ability to exert real-time, adaptive control of transportation processes is the core of many intelligent transportation systems decision support tools. Reinforcement learning, an artificial intelligence approach undergoing development in the machine-learning community, offers key advantages in this regard. The ability of a control agent to learn relationships between control actions and their effect on the environment while pursuing a goal is a distinct improvement over prespecified models of the environment. Prespecified models are a prerequisite of conventional control methods and their accuracy limits the performance of control agents. This paper contains an introduction to Q-learning, a simple yet powerful reinforcement learning algorithm, and presents a case study involving application to traffic signal control. Encouraging results of the application to an isolated traffic signal, particularly under variable traffic conditions, are presented. A broader research effort is outlined, including extension to linear and networked signal systems and integration with dynamic route guidance. The research objective involves optimal control of heavily congested traffic across a two-dimensional road network—a challenging task for conventional traffic signal control methodologies.

This paper examines the influence of taxi behavior on urban traffic conditions. Using computer simulation and the Taxi Equivalence Factor (TEF), a concept similar to the passenger car equivalents for heavy vehicles, the impacts of taxi traffic on the capacity, and delays at urban road sections is quantified. The taxi equivalence factor is based either on capacity or on delay. Through extensive simulation analysis, the effects of various traffic parameters on the magnitude of the TEF were examined. The results suggest that the TEF is significantly higher for one-lane roads than it is for two-lane roads. Further, the capacity based TEF takes on very low values, while the delay based TEF takes on values that under specific traffic conditions may approach 2. This indicates that the presence of taxis does not seem to affect road capacity, but it significantly affects traffic delay. In any case, the maximum TEF values are found, as expected, when flow approaches capacity.

This paper introduces a planning model to estimate the total distance traveled by prime movers in transporting import and export containers between a port, warehouses, and container yards. The total distance includes the empty trip distances traveled by the prime movers, which occur between jobs of towing containers. As the actual data of empty trips and their distances are often difficult to obtain, the gravity model has been used in the estimation process. This model has been applied to estimate the total distance traveled by all of the prime movers in Singapore, based on the existing container volume, port locations, terminal capacities, land use pattern, and road network. Comparison has also been made with a hypothetical scenario where all of the port operations are consolidated into a single terminal. The results show that, if the container ports near the central business district are shifted to a megaterminal nearer to the major industrial zones, approximately 4.9–6.8% savings in the total distance traveled could be achieved.

A method for segmentation of a road based on surface measurements is presented. This method is based on a statistical model of the measurement series and acknowledges that neighboring measurements are dependent. Sudden changes in the level, in the variance, or in the autocorrelation of a series are detected. No prior knowledge about these quantities is required, and no distributional assumptions about the nature of the sudden change are made. The method allows for an assessment of the information contained in the measurements themselves. Uncertainties about the existence and possible location of a change-point are communicated to the user in terms of probabilities. The road engineer may then match the extracted information with available complementary information about, e.g., the age of the pavement and traffic volumes. The focus is on the situation where it is known beforehand that, at most, one change points is present. Thus, the suggested method is best suited to assist the engineer in a detailed study of selected parts of a given measurement series, or may be used iteratively when several change points are suspected. The application of this method is demonstrated using a measurement series for the international roughness index, collected with the Swedish road surface tester known as the laser RST-vehicle.

The clogging of the void spaces within the permeable base by foreign particles can severely reduce its drainage capacity. This will, in turn, reduce the service life of the permeable base layer within the pavement. In this paper, the reduction in the vertical permeability of several permeable base mixes as a result of clogging has been studied. The clogging materials used are mixtures of sand and residual soil. An empirical theoretical formulation has been derived from the Kozeny-Carmen equation in order to predict the reduction in permeability of the permeable bases. The equation has been expressed in terms of the initial vertical permeability of the permeable base specimen, porosity, amount of clogging material retained, and an experimental empirical coefficient. This coefficient is found to be dependent on the ratio of the $D_{15}$ size of the permeable base to the $d_{85}$ size of the clogging material and coefficient of uniformity, $C_u\text{,}$ of the clogging material. The theoretical predictions have been compared with experimental results, with good agreement.

The British pendulum test is one of the most common laboratory test methods for the determination of low-speed microtexture-related skid resistance properties of pavement surface materials. This paper presents the development of a three-dimensional finite-element model that simulates the British pendulum test. The procedures for determining different model parameters are described. Besides the constant parameter values representing the characteristics of the British pendulum tester, only a relatively simple static friction test is needed to provide the necessary input to the computer model. Three different pavement materials were studied in the model validation program. Results of the validation program showed that there was very good agreement between the laboratory measured British pendulum test data and the computed values by the finite-element model. The output variables verified included the energy loss, British pendulum number (BPN), sliding distance, time taken to cover the sliding distance, inclination of rubber slider, and contact pressure. The findings suggest that the skid resistance BPN of a pavement material can be determined without having to physically perform the British pendulum test.

This paper presents an evaluation of the falling weight deflectometer testing data using the AASHTO and WESDEF back-calculation procedures. General concepts of each procedure are highlighted, together with data utilized in the analysis. The back-calculated layer moduli and effective structural number $\left({\mathrm{SN}}_{\mathrm{eff}}\right)$ of an existing flexible pavement were determined from both procedures and compared to see the difference between the procedures. The average subgrade modulus of resilience $\left(M_R\right)$ obtained from WESDEF was found to be about 0.7–0.9 of the value obtained from AASHTO with the factor (C) of 1.0. Modulus values obtained from California bearing ratio tests were in close agreement with AASHTO values only when the factor (C) was set to 0.33, the AASHTO recommended value. The analysis also suggests that a similar factor, about 0.5, for WESDEF should be used. WESDEF, without adjustment, produced higher ${\mathrm{SN}}_{\mathrm{eff}}$ values compared to AASHTO, with the difference being significant only at higher levels of reliability. This difference could reach 0.44 and 0.66 for reliability levels of 95 and 99%, respectively, and could result in a difference in the overlay thickness by up to 25 and 38 mm, respectively.