Journal of Transportation Engineering, Part A: Systems

Horizontal curves tend to be associated with a disproportionate number of severe crashes. Roadway departure crashes are the most frequent crash types on horizontal curves and are highly influenced by driver behavior in conjunction with roadway and environmental factors. Failure to maintain proper lane position along the curve is one of the reasons for an increase in roadway departure crashes. The primary aim of any curve-related treatment is to influence vehicle travel paths by reducing the undesirable paths and thus assist in improving vehicular safety along horizontal curves. To date, an analysis of vehicle travel paths as a function of various factors that influence travel path behavior has not been conducted. The objective of this study is to develop models to predict vehicle travel paths along horizontal curves as a function of curve geometric, pavement, and traffic control characteristics. Lane width, curve sharpness, and speed differential have been identified as key geometric variables. Skid number, which describes the skid resistance of a pavement, was found to significantly influence vehicle travel paths.

The Mechanistic-empirical pavement design guide (MEPDG) provides theoretically superior methodology, as compared with its predecessor, for the design and analysis of pavement structures. The mechanistic part refers to simulating pavement–tire interaction to calculate critical responses within pavement. The empirical part means prediction of pavement distress propagation over time using transfer functions that link a critical pavement response to a particular pavement distress. The mechanistic part of MEPDG simulates tire–pavement interaction in three steps: subdivision of pavement layers; complex modulus calculation at the middepth of each sublayer, considering velocity and temperature; and running the multilayered elastic theory (MLET) software, JULEA. Although MEDPG has a grounded methodology for pavement analysis, it has a number of limitations and unrealistic simplifications that result in inaccurate response predictions. These limitations are primarily related to the pavement analysis approach used in the MEPDG framework, MLET. By contrast, finite-element (FE) analysis has proven to be a promising numerical approach for overcoming these limitations and simulating pavement more accurately and realistically. Although comparison of MLET with FE analysis has been studied, the difference between FE and MEPDG simulations has not been quantified. This study fills that gap by developing linear equations that connect pavement responses produced by these two approaches to pavement analysis. The equations are developed for ten different pavement responses, using a total of 336 cases simulated using FE and MEPDG analyses. The cases modeled in simulations were selected to capture extreme conditions, i.e., thick and thin pavement structures with strong and weak material properties. The equations developed can help pavement researchers understand quantitatively the effect of MEPDG limitations. In addition, the equations may be used as adjustment factors for MEPDG to compute pavement responses more realistically without using computationally expensive approaches, such as FE analysis.

This paper develops and validates a deterministic model that estimates the delay incurred by platoon vehicles due to pedestrian activity at midblock crosswalks on urban street segments. The developed model is validated using midblock delay data measured at an urban street segment in Newark, New Jersey. The model validation involves both quantitative and qualitative statistical analyses to compare the delay values measured in the field with those estimated using the developed model. The quantitative statistical analysis involves performing the t-tests using commercially available statistics software. The qualitative analysis involves the use of a diagonal plot to compare the measured and estimated delay data sets. Sensitivity analysis is performed to study the relationship between estimated midblock delay and the model’s variables and parameters. The sensitivity analysis involves estimating the delay by increasing and decreasing the baseline values of the model variable and parameters by 50%. Results of the t-test show no statistically significant difference between the measured and estimated delays. Result of the sensitivity analysis shows pedestrian walking time significantly impacts vehicular delay.

In this study, to calibrate the acceleration/deceleration rates in operating speed prediction models, driving tests were performed on two-lane mountain highways using passenger cars, and continuous longitudinal acceleration data were collected. The acceleration/deceleration rates of large vehicles such as coaches and heavy trucks were also measured from the roadside. The collected data were used to determine the cumulative frequency profiles and statistical distribution characteristics of the peak acceleration for different types of vehicles. Based on the established correlations, models of acceleration/deceleration versus road geometry features were developed. The key findings of this study are as follows: First, for passenger cars, the deceleration rate is obviously greater than the acceleration rate. Therefore, it would be inappropriate to use the same value for both the rates in speed prediction models. Instead, acceleration and deceleration should be calibrated separately. Second, none of the breakpoints on the acceleration/deceleration cumulative frequency curves appears at the 85th percentile; rather, they appear closer to the 95th percentile. Therefore, the common practice of using the 85th percentile in highway design should probably be reconsidered. Third, for large coaches, the acceleration and deceleration rates are quite similar, whereas for heavy trucks, the deceleration rate is significantly larger than the acceleration rate. The acceleration and deceleration rates of heavy trucks are both lower than those of coaches. Finally, for passenger cars driving around a curve, a negative correlation exists between the acceleration/deceleration rate and curve radius and a positive correlation exists between the acceleration/deceleration rate and deflection angle.

A number of discrete choice models, including a multinomial logit model (MNL), a nested logit model (NL), and a latent choice set model (LCS), are applied to the representation of gap acceptance by merging vehicles (MVs) on urban expressways and their results are compared. The results show that all models give consistent signs to the estimated parameters. It is evident that the LCS model is capable of representing gap acceptance and allows exploration of the latent choice made by MVs. Comparison of the models shows that LCS is superior to the traditional MNL and NL models in terms of goodness of fit and provides a more realistic simulation of MV behavior. The effects of geometry and traffic conditions are fully considered in this study, and they are found to significantly influence the choices made by MVs. A longer acceleration lane may provide a relatively larger gap for MVs and, therefore, motivate them to accept the gap. With respect to traffic conditions, an MV tends to reject a gap under low ($<20\mathrm{vehicles}/\mathrm{km}/\mathrm{lane}$) or high density ($>40\mathrm{vehicles}/\mathrm{km}/\mathrm{lane}$) conditions. However, gap acceptance is more likely when the density is from 20 to $40\mathrm{vehicles}/\mathrm{km}/\mathrm{lane}$. With regard to safety, the concept of time to collision (TTC) is adopted to capture the reactions of MVs to mainline vehicles (MLVs). Both leading and following TTCs (between the MV and the leading/following MLV, respectively) are implemented in the models. Analyses indicate that the TTC thresholds for an MV to reject or accept a gap are 5 and 6 s for the leading and the following TTC, respectively.

Different codes and railways specify different maximum curvatures for their track systems. The curve-negotiating capability of the vehicle dictates the absolute minimum radius used on a track system; other factors may also be considered to decide the minimum radius. In this paper, a minimum radius labeled as the threshold radius is determined when a ballasted, continuously welded curved track would not move under the action of thermal load in an unladen track. Thus, the curve with the threshold or flatter radius would not require hot-weather or cold-weather patrolling or other measures to augment the lateral strength of the track. A formula is derived in this paper to determine the threshold value: the temperature limits at which hot-weather or cold-weather patrolling is to be enforced if the radius happens to be sharper than the threshold radius. Formulas are also used to determine the desirable temperature range for tamping. The paper also presents a review and analysis of the current literature to be able to choose a practical value for lateral resistance of monoblock concrete ties; it also presents a literature review on recently developed forms of concrete ties. A typical application is then presented to demonstrate the utility of the formulas. Finally, on the basis of the formulation and analyses, curves are then classified into three groups based on a maintenance point of view—Group I (least desirable), Group II (desirable), and Group III (most desirable). The research presented here will be useful for both design and maintenance engineers.

This paper presents an improved model for pedestrian crossing time that is used to establish preliminary guidelines for lateral clearance needs on railroad-highway grade crossings. The improved model includes new elements that are lacking in existing models such as pedestrian observation-reaction time, length of pedestrian unit, and safety margin. A general model for the required lateral clearance, that is applicable to any number of tracks on crossings located on horizontal curves or on tangent sections, was developed. The model can be used to determine the required lateral clearance to the right and to the left of the crossing, including maximum lateral clearance, its location, and lateral clearance at a specified location. A comparison of pedestrian crossing sight distance with intersection (vehicle) sight distance shows that lateral clearance needs for pedestrians are not generally satisfied by those currently available for vehicles. The presented design guidelines promote pedestrian safety and should be of interest to highway and railroad professionals.

Reinforcement learning (RL) has been applied to solve ramp-metering problems and attracted increasing attention in recent studies. However, improving traffic efficiency is the main concern of these applications, and the issue relating to user equity has not been well considered. A new RL-based system is developed in this paper to deal with equity-related problems. With the definition of three RL elements, including reward, action, and state, this system can capture the information of user equity and balance it with traffic efficiency. Simulation experiments using real traffic data collected from a real-world motorway stretch are designed to test the performance of the new system. Compared with a widely used ramp-metering algorithm ALINEA, the new system shows superior performance on improving both traffic efficiency and user equity. Specifically, with suitable parameter settings, the new system can reduce the total time spent (TTS) by motorway users by 18.5% and maintain an equally distributed total waiting time (TWT) with a low standard deviation for TWT across on-ramps close to 0.

This paper presents the quantification of the impact of subgrade stiffness on the prevalence of track geometry defects and degradation of track quality indices (TQIs). The data included in this study come from two high-traffic subdivisions [$>50$ million gross tonnes (MGT)/year] in Canada with a total length of 800 km and consist of vertical track deflection (VTD) measurements and 3 years of track geometry measurements. The VTD measurements were used to derive two indices that represent the magnitude and variability of the subgrade stiffness. An analysis of the data shows that the locations at which defects occur correspond to locations with low modulus (higher VTD) and high variability of track modulus. A similar correlation is shown with track roughness represented by a TQI. However, the correlation with the spectrum of TQI calculated was found to be poor. This was attributed to maintenance activities carried out to improve track conditions. The correlation with the TQI greatly improved when arbitrary thresholds were applied and TQI values above this were treated as geometry defects. These results show that the locations that have a low modulus and high variability in the modulus are those that are the most difficult to maintain and at which maintenance is not always able to keep up with the degradation of track geometry. Thus, VTD measurements evaluate the underlying causes that result in the degradation of track conditions and allow for the identification of sections where poor track conditions are most likely to develop.