Search

Providing an appropriate length of highway entrance ramps is an important feature that should be considered in freeway design. The recommended minimum acceleration lane length in the Green Book of the American Association of State Highway and Transportation Officials (AASHTO) is currently used for designing entrance ramp terminals. However, in some cases, traffic congestion and crashes are observed when heavy trucks enter freeways, which indicates they could not accelerate enough and did not reach the merge speed at the end of the acceleration lane. Therefore, several scenarios were simulated using a dynamic simulation model (TruckSim) for heavy vehicles with weight to power ratios of 61, 67, 86, and 108 (kg/kW) and grades of zero, ±3, and ±5%. Subsequently, a linear regression model was presented to calculate acceleration lane lengths. The results showed that the acceleration rate of heavy vehicles is not adequate, especially in upgrades. For example, at +5% upgrades, heavy trucks cannot accelerate to the merge speed mentioned in the AASHTO. Conversely, the acceleration rate of heavy vehicles increased in downgrades; therefore, some heavy vehicles were able to achieve merge speed along the proposed length of AASHTO.

High collision rates on horizontal curves compared with other roadway elements make them one of the most critical elements in a transportation network and thus good candidates for new studies, especially of the stability of a vehicle driving on a horizontal curve. In this regard, spiral transition curves as facilities to enter horizontal alignments are very important. While the superelevation changes in these curves have always been linear, the aim of this study was to evaluate non-linearity in the superelevation attainment function (SAF). Various scenarios were used in order to cover different situations. As a simulation tool, the CarSim software package was used to model three kinds of passenger cars (sport utility vehicle, utility truck and sedan). In addition, 16 types of spiral–curve–spiral road plans for three different conditions of road slope, six types of warping in the SAF and two types of functional speed were examined (a total of 1728 scenarios). The results showed that non-linearity might produce better results than other proposed methods; for example, it was found that a parabolic function reduced the lateral acceleration rate by over 50% for high superelevation and design speed. [ABSTRACT FROM AUTHOR]

Reverse Horizontal Curves (RHCs) are among the most accident-prone road points, with many annual fatalities and injuries. These fatalities can increase dramatically if the RHCs and longitudinal slopes are combined. The importance of increasing the safety of RHCs, especially in mountainous routes, is doubled due to the possibility of combining RHCs with vertical extensions or combining them with so-called steep slopes. This study used vehicle dynamic modeling to evaluate the lateral friction of various vehicles. Including the E-Class Sedan, E-Class SUV, Truck, and Bus, moving on RHCs combined with a longitudinal slope (downgrade, upgrade, and direct distance). Then, the RHC lateral friction model was presented using the multiple regression model based on the effective parameters, including design speeds, direct distance, and different longitudinal slopes. The results showed that speed, longitudinal slope, and vehicle type had the most impact, and direct distance had the most negligible impact in friction coefficient models. Based on the modeling results, the higher the design's speed and the shorter the direct distance, the lower the lateral friction coefficient for the Sedan and SUV. Hence, the safety of the vehicles is greater. For trucks, reduced speed, increased direct distance, and reduced slope led to increased safety. In the results, the most critical state was the lateral friction coefficient at a speed of 80km/h and a direct distance of 116m for the SUV., Author(s): Maziyar Khanjari (corresponding author) [1]; Ali Abdi Kordani [2]; Saeed Monajjem [3] 1. Introduction The road factor, along with both human and vehicle factors, plays an influential role in [...]

Freeze-Thaw Damage (FTD) is one of the most important factors that can reduce the Warm Mix Asphalt's (WMA) crack resistance. In this study, modified WMA and WMA mixtures' fracture behavior containing vertical and angular cracks was evaluated using semi-circular bend geometry (SCB). For this purpose, SCB samples containing vertical cracks (Pure mode II) and angular cracks (Pure mode I) were made first; Then, FTD conditions were applied to the samples to condition them. The results showed that all the mixtures modified with Calcium Lignosulfonate (CL) and polyester fibers (PE) had a better crack resistance than the base sample under FTD conditions. As a result, the fracture energy of WMA mixtures containing 6% CL increased by about 146, 141, 75, and 93%, respectively, while the fracture toughness of WMA mixtures containing 3% CL increased by about 103, 95, 97, and 92%, respectively. The results of the brittleness indices showed that mixtures containing 6% CL, 0.25% PE-6% CL, and 0.25% PE had a more flexible behavior than other mixtures under FTD conditions, respectively. Therefore, using these mixtures, in addition to improving the fracture performance, was also recommended for environmentally friendly purposes. [ABSTRACT FROM AUTHOR]

An understanding of the change in follower behaviour as a driver characteristic in traffic simulations is necessary because these behavioural changes are frequently observed in traffic oscillations. The change in follower behaviour due to traffic acceleration and deceleration waves can be classified according to different behavioural patterns resulting from different driver reactions. Combinations of existing behavioural patterns (under-reaction–timid, over-reaction–timid and constant over-reaction–timid patterns) were thus analysed. The method of analysis was based on an artificial neural network model at the microscopic level in order to simulate the extent to which follower behaviour deviates from Newell's car-following model. The most influential parameters of all the behavioural patterns were determined. Based on the under-reaction–timid pattern, decreasing the reaction speed resulted in a change in behaviour due to the development of safe spacing at the reaction point. In addition, follower spacing was the most influential in the over-reaction–timid pattern, resulting in increasing and then decreasing behavioural change. In the constant over-reaction–timid pattern, the follower's speed resulted in increasing and then decreasing the change in behaviour. The application of behavioural change to an intelligent transportation system would improve safety. [ABSTRACT FROM AUTHOR]

Steep downgrades are known as a part of mountain roads with a significant number of severe crashes. Generally, using speed limiters such as speed bumps and speed humps are considered the most effective (considering both the time and cost) ways to reduce the number of victims. The efficiency of speed limiters depends on the driver's consciousness and the car's braking system; the latter could be problematic in wet and dark conditions of the road. The main goal of the current study is to propose an approach to correct the longitudinal profile of roads by replacing the consecutive downgrades and upgrades with a continuous downgrade. The vehicle's speed is reduced by using this method before entering an accident-prone site without the driver's involvement and breaking. To this end, a well-known software program is used under two speeds (70 and 100 km/h) in 68 different routes to analyze speed along the proposed routes. Also, another computer model is used for dynamic simulation. Dynamic analyses and regression models show that the vehicle's speed in the new proposed route is significantly reduced compared with the continuous downgrade. Moreover, results indicate that the upgrade slope of the proposed route has the most impact on reducing the final speed of the vehicles. [ABSTRACT FROM AUTHOR]

The use of fibers and polymers in asphalt mixtures leads to improved quality, higher lifespan, and lower maintenance costs by making mechanical, physical, and chemical changes. This results in eliminating or reducing the weaknesses of mixtures in the production, implementation, and service phases. In this study, the Stone mastic asphalt mixtures with the same gradation curve, but different additives are evaluated. In the first, second, and third groups of experiments, SEBS elasto-plastomer polymer (SEBS), SEBS elasto-plastomer polymer with cellulosic fibers (SEBS-CF), and SBS elasto-plastomer polymer with cellulosic fibers (SBS-CF) were added to the mixture in various weight percentages, respectively. Also, Stone mastic asphalt mixtures without any additives (SMA-S) and SBS-modified mixtures (SBS) as the most common modifiers were considered as the control mixtures. To evaluate the designated mixtures related to moisture sensitivity, several tests including saturated marshal, indirect tensile strength, resilient modulus, and drain down tests were applied. The results showed that the designated asphalt mixtures meet the requirements for the moisture sensitivity and resilient modulus tests successfully, and it is concluded that among these samples of mixtures, 4% SEBS has the best performance compared to other mixtures; it had even better performance than the SBS mixtures, which are the most common modifiers. Therefore, this issue can be a great help considering the advantages of this polymer over other modifiers to select and use it to modify asphalt mixtures among the mixtures although SEBS-CF had a higher percentage of optimum bitumen achieved less drain down, which shows that the bitumen of these mixtures has become more behaviorally stable due to modification with polymer and fiber at the same time. [ABSTRACT FROM AUTHOR]

The aim of this research was to predict operating speed by considering geometric and roadside factors. Although most previous studies have employed linear regression modelling (LRM) to predict operating speed, this study recommends structural equation modelling (SEM) for the prediction of operating speed on rural multi-lane highways. In addition to geometric variables, LRM takes roadside variables into account. When employing SEM in this work, two latent variables were defined, namely 'roadside effects' and 'geometric effects'. The first latent variable was the combination of land-use type, land-use density and number of accesses per segment, while the second was extracted from the segment length, highway grade, curvature, the presence of a guardrail and flat roadside slope, and the posted speed limits. The residual analysis and R2 values for LRM and SEM suggest that SEM demonstrates superior modelling performance compared with LRM. These results show the significant role of latent variables in predicting speed, which cannot be achieved through ordinary LRM. [ABSTRACT FROM AUTHOR]