Incorporating Dynamic Traffic Distribution into Pavement Maintenance Optimization Model

Network-level pavement maintenance and rehabilitation decision-making with the optimized annual budget

Maintenance and rehabilitation (M&R) is necessary to keep pavement networks in good condition. Due to the capital intensity, M&R funding is always insufficient. The annual budget, determining the available funding, is a critical criterion when planning M&R treatments. However, its values are often given, and the determination of the values is seldom discussed. To fill the gap, this paper focuses on both the determination of annual budgets and the budget allocations, and therefore enhances the network-level decision-making on M&R by developing a Multi-Objective Optimization (MOO) method. This method does not only optimize and trade off the annual budgets and their consequences, but also allocates the funding across the entire network through generating the optimized M&R decisions. According to a case study with 50 segments, the developed method successfully and effectively identified non-linear discrete relationship between the minimized annual budgets and the maximized M&R benefits subject to all the constraints, and generated the optimized annual budget allocation for each M&R decision. The achievements of this paper can be used to enhance the efficiency of M&R decisions and contribute to informed pavement management.

Modelling of Evenness of Runways as an Element of Sustainable Airport Maintenance

The elevation of airport runways is specified in the operations manuals and in globally accepted design guidelines. Airport runways are constantly exposed to various physical and weather factors. However, these factors can deteriorate the condition of the runway to the point where it becomes unusable. Monitoring and the continuous inspection of runway evenness is an important element of a sustainable airport maintenance system. An important element of a sustainable airport maintenance system is a runway evenness detection and modelling system. The investigation of the use of various available methods for modelling runway evenness was conducted based on measurements of the actual condition of the existing runway at Edvard Rusjan Airport in Maribor, Slovenia. During the measurements of the runway condition, our own measurement equipment was used, which ensures the geodetic accuracy of the measurements. The novelty of the article is a comparison between five different approaches to modelling runway evenness: approximation with regression plane, inverse distance weighted interpolation (IWD) with a weighting factor of 1, 2, and 10, and interpolation based on a triangulated irregular network (TIN)–linear and cubic. In the methodology section, the advantages and disadvantages of the mentioned methods were described. The selected models were evaluated by required processor time, by the file size resulting from the modelling, and by the values of the descriptive statistics of the model deviation at the average uniform slope. It was found that the modelling method using linear triangular irregular network interpolation provided the most useful results. The results of the conducted analysis can be easily used in any runway management models at airport thet allow for professionally based actions aimed at ensuring the safety and efficiency of runway operations, especially at smaller, regional airports.

The Innovative Model of Runway Sustainable Management on Smaller Regional Airports

Airport runways are exposed to large traffic loads and other external factors which cause their transformation. Monitoring the state of the unevenness and determining the runway defectiveness is a complex procedure which includes fast and qualitative measurements of the execution of flatness, their evaluation and the determination of the level of runway defectiveness. For this purpose, an improved process of determining airport runway defectiveness is proposed, based on geodetic survey and the management information system prototype, which enables evaluating the results of the executed survey and suggesting the runway maintenance measures. A similar analysis of the considered data on the example of a smaller, regional airport in Maribor, Slovenia, was performed with the help of our own algorithm, which, on various platforms, enables the tabular and graphical display of surface irregularities. The algorithm prototype allows the automated monitoring and evaluating of the unevenness or runway states, determining their defectiveness and advising adequate action. With the help of the suggested method and developed information system prototypes, it is possible to confirm the demand for professionally adequate and on-time planning of necessary maintenance works, with which it is surely possible to prevent an eventual unexpected closing of the runway and related costs. The suggested method is also usable in evaluating the state of other traffic infrastructure.

Modeling the Optimal Maintenance Scheduling Strategy for Bridge Networks

An optimal maintenance scheduling strategy for bridge networks can generate an efficient allocation of resources with budget limits and mitigate the perturbations caused by maintenance activities to the traffic flows. This research formulates the optimal maintenance scheduling problem as a bi-level programming model. The upper-level model is a multi-objective nonlinear programming model, which minimizes the total traffic delays during the maintenance period and maximizes the number of bridges to be maintained subject to the budget limit and the number of crews. In the lower-level, the users’ route choice following the upper-level decision is simulated using a modified user equilibrium model. Then, the proposed bi-level model is transformed into an equivalent single-level model that is solved by the simulated annealing algorithm. Finally, the model and algorithm are tested using a highway bridge network. The results show that the proposed method has an advantage in saving maintenance costs, reducing traffic delays, minimizing makespan compared with two empirical maintenance strategies. The sensitivity analysis reveals that traffic demand, number of crews, availability of budget, and decision maker’s preference all have significant effects on the optimal maintenance scheduling scheme for bridges including time sequence and job sequence.

Optimal Evacuation Strategy for Parking Lots Considering the Dynamic Background Traffic Flows

An optimal evacuation strategy for parking lots can shorten evacuation times and reduce casualties and economic loss. However, the impact of dynamic background traffic flows in a road network on the evacuation plan is rarely taken into account in existing approaches. This research develops an optimal evacuation model with total evacuation time minimization by dividing the evacuation process in a parking lot into two periods. In the first period, a queuing theory is used to estimate the queuing time, and in the second period, a traffic flow equilibrium model and an intersection delay model are employed to simulate vehicles’ route choice. To deal with these models, a modified ant colony algorithm is developed. The results of a numerical example prove that the proposed method has an advantage in improving evacuation efficiency. The results also show that background traffic flows affect not only vehicles’ average queuing time in parking lots but also optimal evacuation route choice. Additionally, a sensitivity analysis indicates that the minimum threshold of headway time that allows vehicles out of a parking lot to merge into the background traffic flows on the roads connecting the exits has a great impact on average queuing time, average travel time, and total evacuation time.