The Impact of Traffic & Vehicle Loads on Pavements
When designing a pavement, it is important to understand the expected loads it will bear as load distribution is one of its primary functions. Loads refer to the forces exerted on the pavement by vehicles such as trucks, heavy machinery, and airplanes. There are a number of traffic and load related factors that have a negative impact on the pavement, including:
Tyre loads
Axle configurations
Repetition of wheel loads
Traffic distribution
Vehicle Speed
To gain insights into the effect of loads on pavement, let's examine the following key factors in further detail. We also discuss how to evaluate the structural impact caused by loads in the subsequent section.
Tyre Loads
Tyre loads refer to the stresses transmitted by the tyre at contact points on the pavement. For ease of calculations, it is often assumed that the load is distributed evenly over a circular area. Figure 1 shows that it is actually more elliptical in shape, and the highest vertical stresses are found in the centre and/or on the sides of the tyre imprint (Huhtala, 1995). Additionally, the load distribution will depend on the wheel load or tyre inflation pressure. The speed of a vehicle also affects the stress distribution.
Figure 1: Vertical stress Distribution between a tyre and pavement
Axle and Tyre configurations
The number and contact points per vehicle have a direct effect on pavement performance. As the tyre loads become more closely positioned, their impact areas on the road start to intersect. At this stage, the design feature of importance shifts from the individual tyre load to the collective impact of all the interconnected tyre loads.
A 2019 study of the effect of axle and tyre configurations on flexible pavement by Tajudin and Priyatna produced several outcomes worth noting. First, in the case of a single axle with a single tyre, the highest strain value is observed at the centre of the tyre. For a single axle with dual tyres, the greatest strain occurs at the tyre radius. Tandem and tridem axles with dual tyres show the most significant strain values at a distance halfway between the tyres. Additionally, the study highlights the inverse relationship between strain values and the number of allowable repetitions, indicating that higher strain values reduce the number of vehicle repetitions that can traverse the road without causing rutting damage. The study also emphasises that vertical and horizontal strain values are influenced by both vehicle loading and axle configuration. Another study by Salama, Chatti and Lyles (2006) that uses traffic and pavement performance data of Michigan flexible pavements suggests that trucks equipped with multiple axles such as tridem or above, seem to cause greater rutting damage compared to trucks with only single or tandem axles. However, trucks with single and tandem axles tend to be associated with a higher incidence of cracking in the pavement. Increased axles can also cause pore water pressure in the road structure to rise.
Repetition of wheel loads
The impact of traffic on pavements is determined not only by the size of the wheel load but also by the frequency at which the loads are applied. Each instance of a load application results in some level of deformation, and the overall deformation is the sum of these individual deformations. While the deformation caused by a single axle load may be minimal, the cumulative effect of repeated load applications becomes significant. As a result, contemporary pavement design considers the total number of standard axle loads (typically 80 kN for a single axle) as a key factor. However, note that the relationship between repetitions is not arithmetically proportional to the axle loading (WSDOT, 1995). Furthermore, several studies have shown that repeated loads can lead to pore water pressure due to the insufficient recovery time between loads (Cary 2011, Saarenketo et al. 2012, Varin & Saarenketo 2014, Krechowiecki-Shaw et al. 2016, Lei et al. 2017). Saarenketo (2012) suggests that heavier trucks cause higher displacement in the subgrade, thus increasing the recovery times of the subgrade.
Traffic distribution
In addition to considering the type of load and its repetitions, it is important to estimate how loads are distributed across a specific pavement. For example, on a 6-lane interstate highway with 3 lanes in each direction, the total number of loads is unlikely to be evenly distributed in both directions. Often, one direction carries a higher load volume compared to the other. Furthermore, within that particular direction, not all lanes bear the same load. Typically, the outermost lane carries the highest number of trucks and experiences the heaviest loading. Consequently, the structural design of the pavement should consider these uneven load distributions.
Vehicle Speed
The presence of slow-moving loads and static loads can have negative effects on pavements, as they are primarily designed to withstand the impact of moving loads. Usually, when vehicles move at slower speeds or come to a complete stop, they exert a load on a specific area of the pavement for an extended duration, leading to increased damage. This effect can be observed in bus stops on hot mix asphalt (HMA) pavements where buses stop to load and unload passengers, and where vehicles stop and wait to cross an intersection. In cases where the mix design or structural design of the HMA pavement is inadequate, this damage becomes more apparent.
How to evaluate the structural impact of loading
The Falling weight deflectomer (FWD) in action
The assessment of pavement structural condition plays a crucial role in the evaluation and implementation of effective rehabilitation strategies. Over the years, the falling weight deflectometer (FWD) has emerged as the preferred device for accurately gauging pavement structural condition and determining the optimal treatment options at the project level. By subjecting pavements to dynamic loading and measuring their deflection responses, the FWD provides valuable insights into the structural integrity and performance of road surfaces.
The effect of loading on a pavement is a key aspect addressed by the FWD. By simulating the dynamic loads experienced by pavements under actual traffic conditions, the device enables engineers and researchers to understand how different loading scenarios impact the structural condition of the pavement. This knowledge is essential for making informed decisions regarding pavement maintenance, rehabilitation, and design, ultimately contributing to safer and more durable road networks.
By utilising the FWD's capabilities, pavement engineers can accurately assess the structural condition of roads, identify areas of weakness, and tailor appropriate treatment options accordingly. This optimisation of treatment strategies not only helps to prolong the lifespan of pavements but also ensures cost-effective allocation of resources.
As technology continues to advance, it is important to explore and develop further innovations in pavement structural assessment. By incorporating new techniques and methodologies, we can enhance our understanding of the effect of loading on pavements, leading to more efficient and sustainable transportation infrastructure.
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References
Cary, C. (2011). Pore water pressure response of a soil subjected to traffic loading under saturated and unsaturated conditions. PhD thesis, Arizona State University, Tempe, AZ, USA.
Huhtala, M. (1995). The Effect of Wheel Loads on Pavement. https://hvttforum.org/wp-content/uploads/2019/11/The-Effect-Of-Wheel-Loads-On-Pavements-Huhtala-.pdf’
Krechowiecki-Shaw, CJ, Jefferson, I, Royal, A, Ghataora, GS & Alobaidi, IM. (2016). Degradation of soft subgrade soil from slow, large, cyclic heavy-haul roads loads. Canadian Geotechnical Journal, vol. 53, no. 9, pp. 1435-49.
Lei, H, Liu, M, Zhang, W & Li, B. (2017). Dynamic properties of reclaimed soft soil under the combined frequency cyclic loading. Road Materials and Pavement Design, vol. 18, supplement 3, pp. 54-64.
Matthew, T. V. (2009). Factors affecting pavement design. Lecture notes in Transportation Systems Engineering. Indian Institute of Technology Bombay. <https://www.civil.iitb.ac.in/tvm/1100_LnTse/402_lnTse/plain/plain.html.>
Pavement Interactive (2022). Loads. <https://pavementinteractive.org/reference-desk/design/design-parameters/loads/ >
Saarenketo, T, Matintupa, A, Varin, P, Kolisoja, P, Herronen, T & Hiekkalahti, A. (2012). Summary of pajala mine road impact analysis – ROADEX implementation. The ROADEX Implementing Accessibility Project, 27 pp.
Salama H K, Chatti K, and Lyles R W. (2006). Effect of Heavy Multiple Axle Trucks on Flexible Pavement Damage Using In-Service Pavement Performance Data. Journal of Transportation Engineering. Volume 132, Issue 10 <https://doi.org/10.1061/(ASCE)0733-947X(2006)132:10(763)>
Tajudin, A N and Priyatna, R. (2019). Effect of Axle and Tyre Configurations on Flexible Pavement Response. IOP Conf. Ser.: Mater. Sci. Eng. 508 012004 <https://iopscience.iop.org/article/10.1088/1757-899X/508/1/012004/pdf>
Washington State Department of Transportation. (1995). WSDOT Pavement Guide – Volume2 <https://www.scribd.com/document/156759214/Wsdot-Pavement-Guide-volume2#>