## 1 Introduction  
### Background  
The City of Riyadh, Saudi Arabia, has seen very rapid development over the past two decades. The city area expanded from 75 km\({}^{2}\) to more than 1600 km\({}^{2}\). The General Directorate of Operation and Maintenance of Riyadh Municipality is the agency responsible for maintaining a street network exceeding in length 10,000 km [1]. It was not possible to maintain the roads of a city with this huge street network without a pavement maintenance management system (PMMS). PMMS is a program to maintain and preserve the pavements of the road network at acceptable level of safety, quality, and performance and minimize their lifecycle costs as a major component of a comprehensive pavement management system (PMS) [2]. The basic purpose of a PMMS is to achieve the best value possible for the available public funds and to provide safe, comfortable, and long-lasting transportation infrastructure [3]. An essential element of any PMMS is a reliable and accurate way to predict pavement performance. A typical way to predict the performance of the pavement is by developingpavement performance models, which can be used to determine the future maintenance needs and the required maintenance budget and to set maintenance priorities based on the available budget. Pavement performance models are imperative for a PMMS and perform a function similar to that of a car engine. Based on these models, the future pavement condition can be forecasted and can be used as an input to the maintenance policy to predict the required maintenance and rehabilitation (M&R) activities. Therefore, the PMMS assists top management in finding optimum strategies for providing and maintaining pavement in a serviceable condition [1]. A pavement performance curve describes the relationship between pavement conditions with pavement age or traffic level. The performance of the pavements was assessed to determine whether they were good or poor [4; 5]. Pavement conditions can be determined through performance indicators such as pavement distresses, riding quality, structural adequacy, and skid resistance. These performance indicators can be combined into one index, e.g., the pavement condition index (PCI) has been widely utilized to allocate pavement maintenance strategies [6]. As shown in Figure 1, PCI values are computed based on visual assessment and indicate the types of distress, magnitude, and quantity present on the pavement surface [5]. The PCI provides the evaluation of the pavement's state, with scores ranging from 0 (failed) to 100 (excellent), as illustrated in Figure 2.  
Maintenance activities are used to prevent pavement deterioration or reduce the rate at which the pavement deteriorates. The effect of M&R can be represented as the improvement in the pavement condition. This effect can be evaluated based on the change in the slope of the pavement condition curve or as the change in the level of pavement condition before and after performing a maintenance strategy. In some cases, the effect is measured by the frequency of the maintenance applied to extend the pavement's service life. The concept of pavement maintenance's effect on pavement condition is illustrated in Figure 3.  
One technique to evaluate the effects of different M&R strategies is by building performance models. The procedure of modeling the M&R effect starts by determining the factors that may influence the pavement condition. These factors may include the pavement construction details, maintenance age, traffic level, availability of drainage system, maintenance age, environmental factors, etc. Once all the possible factors that may influence pavement condition are determined, pavement sections can be grouped based on the type of maintenance they received. The maintenance models can then be developed to predict pavement conditions under each maintenance strategy. Figure 1: The procedure of the pavement condition index (PCI). Figure 2: Pavement condition index (PCI) rating.