Existing design policies determine the speed variation of vehicles on upgrades solely as a function of specific values: initial speed, grade, and weight to power ratio. This paper establishes a dynamic model that considers in addition the influence of the roadway’s horizontal alignment. The model was validated on both tangents (using existing speed-distance profiles and similar simulation models) and curves (by an existing simulation model and field measurements). The model output was examined on a roadway alignment. It was found that sharp horizontal curves influence the speed of heavy vehicles significantly on mild upgrades. Therefore the conventional speed profile determination has to be supplemented by incorporating the horizontal alignment as well. The proposed model can be used to provide solutions in a more efficient and realistic way than does the current practice.

Evaluating the performance of a detection and warning system designed specifically to detect and warn no-passing zone violations on vertical curves of two-lane rural roads is the focus of this paper. The evaluation is mainly based on the unique simulation developed for that purpose. Many roadway, vehicle, and driver-related parameters were introduced in this simulation to reflect as close as possible what is occurring in the real world. More than 19,500 violation case simulation runs were made for the base scenario to reflect and calibrate the actual conditions of the parameters involved. The simulation runs were made for both “with” and “without” the warning system cases. The simulation outcome for the “without the system” case was very close to the actual real-world condition (1.41 versus 0.71 crash per year). The simulation runs of the “with the system” case showed also that the system could virtually eliminate all head-on collisions, should the violators obey the early warning messages displayed. Eleven sensitivity tests showed that the simulation is robust in describing the system performance. An economic feasibility analysis revealed a high benefits–cost ratio of 38.9, and modified internal rate of return of 65%.

TransGuide is San Antonio’s multifunctional citywide center that manages traffic through surveillance, incident detection/management, and dissemination of traffic information. This paper reviews automatic incident detection technologies deployed in San Antonio freeways and managed by TransGuide. Traffic and incident data collected from the San Antonio network are used to compare the performance of inductive loop detectors (ILDs) and automatic vehicle identification (AVI) for automated incident detection. California No. 8 and the Texas algorithms were calibrated and tested using the ILD data collected for incident detection. The upper confidence limit algorithm and the Texas algorithm were calibrated and tested using the AVI data collected. When traffic and incident data from the San Antonio network are processed by the four different algorithms, the California No. 8 algorithms applied to ILD data performed best in terms of detection rate and false alarm rate. Automated incident detection (AID) is not currently worth implementing in the AVI system studied, but AID based on AVI data is generally feasible with denser tag penetration and sensor installation.

Travel time prediction has been an interesting research area for decades during which various prediction models have been developed. This paper discusses the results and accuracy generated by different prediction models developed in this study. The employed real-time and historic data are provided by the Transportation Operations Coordinating Committee, which collected them using road side terminals (RST) installed on the New York State Thruway. All the tagged vehicles equipped with EZ pass are scanned by RSTs, while dynamic information (e.g., vehicle entry times and associated RST numbers) are recorded. The emphasis of this study is focused on modeling real-time and historic data for travel time prediction. Factors that would affect the prediction results are explored. The Kalman filtering algorithm is applied for travel time prediction because of its significance in continuously updating the state variable as new observations. Results reveal that during peak hours, the historic path-based data used for travel-time prediction are better than link-based data due to smaller travel-time variance and larger sample size.

To convert HOV (high-occupancy vehicle) lanes to HOT (high-occupancy toll) lanes, it is necessary to evaluate the relevant benefits to drivers, to highway maintenance, to traffic management, and to the whole society under various combinations of tolls, motorists’ perception error, and travel demand. This paper assesses the benefit and effect of an HOV/HOT lane project on the I-394 corridor network in the Twin Cities by using an analytical multiclass stochastic dynamic transportation network model with Monte Carlo simulation and the method of successive averages. Specifically, the effects of various toll schemes for HOT lane design and operations are investigated. The results are analyzed, yielding useful insights for the design and evaluation of HOT lanes.

Over the past 50 years, many different “car-following” models have been proposed to describe driver behavior in a traffic stream. A number of inherent assumptions about human constraints and preferences in existing car-following models have hampered their relevance for use in the design and evaluation of different Intelligent Transportation Systems technologies and/or controls such as Advanced Vehicle Control and Safety Systems. In this paper we introduce a new Systems Dynamic (SD) car-following model that addresses many of the shortcomings of existing car-following models and provides a more relevant platform for simulating driver behavior in all types of car-following situations. The proposed SD model was developed and validated based on observed vehicle tracking data. Preliminary results suggest that the proposed model yields speed and spacing profiles for vehicles in “real time” that compare well with those observed empirically.

A recursive nonlinear model was developed for the prediction of pavement performance as a function of traffic characteristics, pavement structural properties, and environmental conditions. The model highlights some of the advantages of relaxing the linear restriction that is usually placed on the specification form of pavement performance models. First, a functional form that better represents the physical deterioration process can be used. Second, the estimated parameters are unbiased, owing to a proper specification and the use of sound statistical techniques. Finally, the standard error of the prediction is reduced by half that of the equivalent existing linear model. This improved accuracy has important economic implications in the context of pavement management. The model developed as part of this research enables the determination of an unbiased exponent of the so-called power law and of the equivalent loads for different axle configurations. The estimated exponent confirms the value of 4.2 traditionally used. However, it should be noted that this exponent is only to be used for determining damage in terms of serviceability. On the other hand, equivalent loads estimated for different axle configurations tend to differ from traditionally used values.

Policies to reduce levels of traffic congestion and pollution in major urban areas often focus strongly on the concept of a sustainable transport system, but to achieve this vision a significant modal shift from private car to public transport will be required. This paper reports on a recent research study which provides a framework within which to model the behavioral responses of travelers following the implementation of strong bus priority measures (where road capacity is deliberately removed from general traffic and given to buses). A summary of the different behavioral responses which can be expected is given and results from a practical implementation of the framework which has been based on two commercial transport modeling packages (CONTRAM and TRIPS) are discussed. These results suggest firstly that the effect of implementing such strong bus priority measures is as dependent on the characteristics of the local travelers as on the scheme itself and secondly that implementing too strong a scheme may not benefit public transport overall.

This paper presents the findings of a before-and-after study which evaluated the impacts of installing and operating red light cameras (RLC) at two “T” and one “X” signalized intersections. The red running violations and vehicle entry times were gathered before and shortly after RLC installation along each individual approach. After RLC installation, red running violations were substantially reduced by more than 40% at camera approaches but not the case for the opposing noncamera approaches. Overall, there was still an aggregated net reduction of about 7% across all approaches. The RLC was found to be more effective in curbing violations during weekends at camera approaches as well as encouraging red-running violators to speed up and clear the camera approaches more speedily. This had generally resulted in lower entry times of red running vehicles. From the results obtained using generalized linear modeling, it was found that the presence or absence of RLC significantly influenced the after-red times, and lower mean after-red times were observed for camera approaches. In effect, the higher the mean after-red time the higher the rate of red running violations.

In the current Highway Capacity Manual (HCM) 2000, level of service (LOS) is defined as a quality measure describing operational conditions within a traffic stream. It is also stated in the HCM that “each level of service represents a range of operating conditions and the driver’s perception of those conditions.” However, the drivers’ perception of traffic operational conditions has not been explicitly considered in defining the LOS categories. This study develops and implements a methodology based on fuzzy clustering to define LOS boundaries based on user perception. The methodology is implemented for determining appropriate LOS categories at signalized intersections. These categories are also compared to the existing HCM 2000 LOS categories. An existing database was used containing user perception-related data on estimated delays and ratings of LOS for signalized intersections, and a fuzzy c-means clustering technique was employed to partition the data sets of the estimated delays and of the quality-of-service ratings into LOS categories. It was found that, based on the fuzzy clustering results, each estimated delay is classified into one major LOS category with one minor LOS category. Conclusions drawn from this study are that (1) users can perceive six levels of service in a fuzzy domain in terms of drivers’ time-estimating capabilities; (2) the current HCM LOS categories are appropriate for signalized intersections in terms of category range and number; and (3) revision of the HCM LOS definitions with consideration of fuzzy clustering would accommodate subjective variations and uncertainties in user perception and alleviate the existing concerns related to the rigid LOS boundaries.

This article presents the theoretical basis for modeling univariate traffic condition data streams as seasonal autoregressive integrated moving average processes. This foundation rests on the Wold decomposition theorem and on the assertion that a one-week lagged first seasonal difference applied to discrete interval traffic condition data will yield a weakly stationary transformation. Moreover, empirical results using actual intelligent transportation system data are presented and found to be consistent with the theoretical hypothesis. Conclusions are given on the implications of these assertions and findings relative to ongoing intelligent transportation systems research, deployment, and operations.

Selecting an appropriate measure of short term maintenance effectiveness and determining its value constitute the first in a three-step process for evaluating maintenance effectiveness in the short term. The second and third steps are to determine if the measured values of effectiveness are significant, and expressing such measured values as a function of pavement or treatment attributes. In addressing the first step, this paper investigates and brings into focus various ways in which response variables for maintenance effectiveness models could be formulated with a view to providing a more reliable means of assessing short-term effectiveness of maintenance treatments. For each of three measures of effectiveness, deterioration reduction level, performance jump, and deterioration rate reduction, the paper discusses computational methods and synonymous terms, identifies past studies that have implicitly or explicitly utilized the measure, and discusses associated merits and demerits. Furthermore, the paper argues that the relative timing between pavement maintenance and performance monitoring reported for a given year, is crucial in the computation of any measure, particularly if the interval of monitoring is relatively large. For each of two relative timing scenarios, the paper derives mathematical formula for computation of each measure. Also, relationships between each pair of the three measures are derived for each scenario. Finally, the paper uses field data from Indiana to illustrate the computations and to demonstrate the implications of incorrect relative timing specification on computation of maintenance effectiveness.

This paper analyzes the travel characteristics of commuters accessing transit stations in Mumbai, India, with a view to identifying the policies that can improve the condition of the transit access environment. The access travel characteristics are discussed with respect to mode use pattern, availability of access modes, satisfaction with the access environment, and characteristics of the access leg of a trip in comparison to primary and egress legs. It is attempted to bring out the underlying preferences of commuters in accessing transit stations based on their access trip characteristics. Acceptable trip lengths by walk and bicycle modes in accessing transit stations are computed from their cumulative frequency distribution of trip lengths. The commuters are segmented into different socioeconomic subgroups using characteristics like occupation, type of house, vehicle availability, and household income. The mean and acceptable walking and bicycling distances found for different subgroups in the present study are compared with those reported in the literature.

Practically all current design for and analysis of thermally induced stresses in rigid pavements are based on an assumed linear temperature distribution across the thickness of the pavement slab. Actual temperature distributions across the thickness of a pavement slab are not linear, and studies have shown that the errors in the computed maximum warping stresses caused by the assumption of linear temperature distribution could be as high as 30% or more. Finite-element models have been developed to analyze the effects of nonlinear temperature distribution. These are numerical methods and are generally not user friendly, as they require skills to design the finite-element mesh and good judgment to ascertain convergence of the solutions. This paper describes a closed-form theoretical model to compute the warping stresses caused by a nonlinear temperature distribution. The model is derived based on the Reissner thick-plate theory for a concrete pavement slab with four free edges resting on either a Pasternak or a Winkler foundation. The nonlinear temperature distribution across the slab thickness is divided into three components that are analyzed separately. The final solutions are obtained by superposition of the stresses caused by the three components of temperature distribution.

A review of the genesis of Marston’s theory for soil loading of pipe in trenches found that the almost 90-year-old theory contains various flaws, including assumptions about lateral pressures and shear strengths that can be developed in trenches. The testing conducted at the time was found to be imprecise, raising questions that the findings may be spurious. The ensuing observations and evaluations of some of the pertinent parameters, including internal and side friction, and the use of Rankine’s formula suggest that faulty data were used to sanction the theory. The same factors that produced the false correlation apparently continue to permit engineers to design installations that in most cases are satisfactory. Some interim modifications to Marston’s formula are suggested to compensate for some of the discrepancies until further research is conducted and verified.