Despite the widespread use of in-place recycling, limited information is available in the literature on in situ and laboratory properties of materials placed through in-place recycling. The main objectives of present study were to investigate the in situ recycled material characteristic that includes the potential of asphalt mixtures for permanent deformation, fatigue cracking, and low-temperature cracking, and the effect of a special technique of hot in-place recycling and rejuvenation on asphalt binder rheological properties. To accomplish these objectives, a two-phase experimental program was designed to determine the performance-related parameters of 100% in-place recycled mixtures using one of the in-place recycling techniques in which overlay is not needed. The experimental program included the measurement of mixtures’ mechanical properties and binder rheological properties. The present study revealed that the stiffness of the asphalt mixtures after recycling had increased compared to that before recycling. In general, specimens exhibited a low permanent deformation potential of 2–3 mm after 20,000 loading cycles by using the Hamburg wheel-track test. Stable crack propagation could not be obtained in the fracture tests at $-12°\mathrm{C}$, which indicates the asphalt mixtures’ brittleness at that temperature. Asphalt binder and aggregates, extracted from the samples as collected at various stages of construction, were characterized to assess the effect of the recycling process on mixtures’ properties. Results obtained from the asphalt binder frequency sweep test indicate an increase in the modulus value, which was primarily caused by a heating process at surface layer. This increase in the modulus value of asphalt binder was efficiently compensated by an addition of a rejuvenator. Alternative additives or rejuvenators may also be considered to improve blending and compatibility between the old and new binder, and to reduce the mixture’s stiffness to avoid any possible premature deterioration. The selected rejuvenator should achieve several goals, including complete blending with existing binder and reducing the combined binder performance grade below the binder performance grade of existing mixes.

Consistency is the relationship between the geometric characteristics of a highway and the conditions a driver expects to encounter. In this study, based on operating speed, consistency was calculated in two-lane rural highways of the province of Granada, Spain. Three consistency measures were calculated for 506 homogeneous road sections: the relative area, which represents the area bounded by the speed profile and average speed of a road segment; the standard deviation of the operating speed in each design element along the road segment; and a consistency model based on the previous measures introduced. Some discrepancies regarding the obtained results lead the authors to propose a new model of consistency that overcomes the identified disagreements.

This paper presents a solution methodology that can be used to determine the optimal solution for the combined congestion pricing and capacity expansion problems. A bilevel genetic algorithm (GA)-based optimization solution methodology is proposed to determine the optimal toll location, toll rate, percentage capacity expansion, and location for the expansion simultaneously. The upper-level subprogram minimizes the total system travel cost given certain budget and toll constraints. The lower-level subprogram is a user equilibrium problem where all users try to find the route that minimizes their own travel cost (or time). The budget constraint is handled using a penalty parameter. The demand is assumed to be fixed and given a priori. The proposed GA model is applied to Sioux Falls network, which has 76 links and 24 origin-destination (OD)-pairs, assuming homogeneous users. The optimal solution is thus identified. Sensitivity analyses are conducted for the budget and penalty parameter. The proposed methodology will be a very useful tool for transportation network planners for allocation of budgets and prioritization of links for improvements and congestion pricing.

Generalized linear models (GLMs) are the most widely used models utilized in crash prediction studies. These models illustrate the relationships between the dependent and explanatory variables by estimating fixed global estimates. Since crash occurrences are often spatially heterogeneous and are affected by many spatial variables, the existence of spatial correlation in the data is examined by means of calculating Moran’s I measures for dependent and explanatory variables. The results indicate the necessity of considering spatial correlation when developing crash prediction models. The main objective of this research is to develop different zonal crash prediction models (ZCPMs) within the geographically weighted generalized linear model (GWGLM) framework in order to explore the spatial variations in association between number of injury crashes (NOICs) (including fatal, severely, and slightly injured crashes) and other explanatory variables. Different exposure, network, and sociodemographic variables of 2,200 traffic analysis zones (TAZs) are considered as predictors of crashes in the study area, Flanders, Belgium. To this end, an activity-based transportation model framework is applied to produce exposure measurements while the network and sociodemographic variables are collected from other sources. Crash data used in this study consist of recorded crashes between 2004 and 2007. The performances of developed GWGLMs are compared with their corresponding GLMs. The results show that GWGLMs outperform GLMs; this is due to the capability of GWGLMs in capturing the spatial heterogeneity of crashes.

This paper presents a departure time choice analysis, based on the notion of a latent carpooling preference. The study is based on combined revealed preference and stated preference survey data collected on the Maryland side of the Capital Beltway (I-495). A conditional logit model is estimated to identify drivers’ choice when tolls and congestion management strategies, including high-occupancy vehicle (HOV) lanes and high-occupancy toll (HOT) lanes, are implemented. Then a latent class model accounting for heterogeneity across groups of drivers is proposed and estimated to examine the difference in behavioral preferences across groups. The latent class model reveals significant heterogeneity in drivers’ latent preference toward ride-sharing, which can potentially support ranges of transportation policy and incentive design related to congestion management strategies such as HOV/HOT lane usage.

This paper presents an application of continuum traffic equilibrium model for the design of optimal recovery plan after a disaster. The continuum traffic equilibrium model is adopted for its strength in defining: (1) alternative routes after disaster; (2) spatially varied impacts of the disaster; and (3) continuously distributed demand. In this study, demands for emergency services, reconstruction activities, and normal-travel activities are separately modeled throughout the recovery period. A bilevel model is set up for designing the optimal recovery plan in the modeled region. At the lower-level model, sets of differential equations are constructed to describe the traffic equilibrium problems at different times of the recovery period. In the upper-level model, a constrained minimization problem is set up to find the optimal recovery plan such that the total travel cost is minimized and the demand of normal/reconstruction traffic is maximized throughout the recovery period. A sensitivity-based solution algorithm that adopts the finite element method (FEM) is proposed to solve the bilevel model, and a numerical example is completed to demonstrate the characteristics of the proposed model.

Speed humps are in widespread use around the world. Despite their effective performance in increasing safety, they cause considerable damage to vehicles and discomfort to drivers and passengers. This paper investigates the dynamic response of vehicles on different types of speed humps using a multibody simulation software package that is popular in the automotive industry. Following this evaluation, two new profiles are recommended to optimize the dynamic performance of speed humps. A series of formulas are also presented to estimate the dynamic performance of passenger cars on flat-topped and parabolic humps based on vehicle speed, hump dimensions, and driving behavior while traversing the hump. The results show that, for flat-topped humps, the ramp length (or entrance slope) has the greatest effect on vehicle performance. It is found that the dynamic performance of the recommended profiles is much better than that of conventional humps.

With the increase in multilane expressways the use of overhead signs has also increased. A driver can miss an overhead sign because of occlusion of the sign by a leading heavy vehicle. Little or no research has been carried out to mathematically analyze conditions under which the driver of a light vehicle will not be able to read a sign because of a leading heavy vehicle. The lack of an analytical understanding of this phenomenon is reflected in the available design standards of the day. This paper analyzes the conditions that lead to occlusion of overhead signs because of a leading heavy vehicle. Next, the duration for which the occlusion occurs is determined. Subsequently, the results for duration of occlusion are used to evaluate whether enough time is left for the driver to read the sign. If enough time is not available then the driver is said to have “missed” the sign. Assuming that the speeds of the light and heavy vehicles and the distance headway between them vary randomly (around some expected values), the probability of missing a sign can be obtained using the analysis presented in this paper. Information on probability of missing a sign is used to determine alternative sign designs (in terms of sign characteristics and number of repetitions of the sign) that keep the probability of missing the information on a sign below a threshold.

A reliable pavement performance prediction model is needed for road infrastructure asset management systems or pavement management systems. In this study, the data on roughness progression of asphalt pavements in the long-term pavement performance (LTPP) database was analyzed in order to develop such a model. The international roughness index (IRI) is a reasonable measure of the ride comfort perceived by occupants of passenger cars and hence used as the basis for the pavement performance prediction model developed in this research. A quantitative relationship between roughness progression and accumulative traffic load, structural number, annual precipitation, and freezing index was developed and validated. Five pavement performance levels were developed to express the extent of asphalt pavement deterioration. This is coupled with a reliability analysis based on the Weibull model to estimate the remaining service life of asphalt pavements. Effective treatments of pavements at the project level for each condition state level were also proposed, which can aid network level optimization of the overall condition and corresponding budget allocations.

Toll plazas create a number of bottlenecks on highways. They can induce motor vehicle crashes and also put workers such as toll collectors at risk. Enhancing safety at toll plazas is crucial to improving safety on tolled roadways. This study aims to evaluate the safety effects of removing mainline barrier toll plazas on highways using empirical Bayesian (EB) methodology. Recent removals of barrier toll plazas on the Garden State Parkway in New Jersey were used as a case study. Multiple-year traffic and crash data before and after the removals of the barrier toll plazas were used for evaluation. Toll plaza crash frequency models as a function of traffic flow and other relevant factors were developed, with the modeling results suggesting that there is a nonlinear relationship between toll plaza crash occurrences and both traffic flow as well as tollbooth configurations. The EB approach is also used to predict crash frequency assuming that the barrier tollbooths were not removed. These EB-based estimates were compared with the observed number of crashes after the removals of the toll plazas. Individual comparisons show reductions in crash occurrence at almost all of the toll plazas and an estimated reduction of 42.1% overall at all toll plazas due to the removal of the barrier tollbooths. The estimated crash cost was reduced by 40.1%. These estimated reductions demonstrate that the removal of barrier toll plazas is a very beneficial countermeasure towards improving safety of toll roads. As the study was performed based on multiple sites along a highway, it would be helpful to learn more lessons from other locations given the availability of reliable data for model development and validation.