With different origins and perspectives, urban sprawl has been recognized as a threat to the quality of life in both developed and emerging countries. However, although in developed countries, the effects of such sprawl have been assessed in terms of extra fuel consumption and traffic congestion, in emerging economies, such effects have not been quantified and analyzed in detail. It was the purpose of this research to estimate the effects of urban sprawl on the transportation costs and fuel consumption in a rapidly growing metropolitan area in Mexico. This was performed through a strategy consisting of applying known analytical methodologies to data that were obtained by direct home surveys. Although the results reveal that such an urban sprawling process represents increases in transportation costs and fuel consumption on the order of 65 and 20%, respectively, it was found that other externalities should be considered in future studies, particularly with respect to the extra costs associated with...

Materials play a fundamental role in any branch of civil engineering. From ancient times to the present day, society has required enormous amounts of construction materials, which implies an excessive exploitation of the natural environment. The present research work consisted in the design and development of asphalt mixes with a partial substitution of the natural aggregate (NA) by means of recycled concrete aggregate (RCA). The mix was designed with the Marshall methodology, considering the next percentages of substitution and addition by mass: 90% NA and 10% RCA; 80% NA and 20% RCA; 70% NA and 30% RCA. The mixtures were elaborated and analysed under the international standards and the Mexican regulation of the Communications and Transport Ministry, to determine the best option regarding their performance. The materials were characterized according to the current regulations and later employed in the mixes design. A total of 38 specimens were elaborated for each mixture, determining the optimum asphalt content; after that, mechanical tests were performed to analyse and determine the best results. In the aftermath of the examination of all mixtures, we concluded that the 70%AN/30%RCA is the best alternative option according to its performance and numeric results, complying with the cited regulations, and allowing a lower content of asphalt during the process.

The design of flexible road pavements is a complex process as a result of the multiple variables that influence and interact in the models that allow the design of each layer. In recent years, a particular interest has been raised to ensure that climate is considered in pavement design due to temperature and precipitation that influence the deterioration of pavements, impacting their service life. This paper presents a critical review of flexible pavement design methods, from the first ones based on experience, such as empirical methods, to the most recent ones on mechanical–empirical methodologies, where, based on different principles, they determine the thicknesses of the layers that integrate the structure of a pavement to identify how these methods have included climate variables within their methodology. Through this review, it was identified that temperature is incorporated in the dynamic modulus of the asphalt mix, and precipitation and moisture are incorporated through the resilient modulus in the granular layers (base, subbase, and foundation soil or subgrade courses). As a result, it was identified that the most holistic way of integrating climate is through the Enhanced Integrated Climatic Model (EICM) from the Mechanistic–Empirical Pavement Design Guide (MEPDG). In many cases, climate is incorporated through parameters whose behavior is associated with temperature and precipitation but does not use the data of these climate variables directly from the project site. The practical incorporation of climate into design methods allows an increase in the certainty of results, ensuring additional climate-resilient pavement structures and increasing their durability and sustainability during their service life.

The prediction of the resilient modulus of foundation soil or subgrade for road pavements has been a subject of significant interest in recent years. This study presents a summary of the factors that influence resilient modulus performance, including climate and climate change, and how this property is fundamental for pavement design. To incorporate climate and climate change in the resilient modulus of the pavement subgrade, a practical tool was developed based on the Climate Information System for Road Design (SICliC) and the Enhanced Integrated Climate Model (EICM) of Mechanistic-Empirical Pavement Design Guide (MEPDG), where the Thornthwaite Moisture Index (TMI) can be estimated based on historical monthly precipitation and mean temperature data and using climate change scenarios for Mexico. The proposal determines the prediction of the behavior of variables that influence the subgrade resilient modulus for unbound granular materials (UGMs) which are associated with climate, such as moisture content, soil suction and degree of saturation, by means of which an environmental factor for unbound materials can be estimated. This factor adjusts the “Resilient modulus at optimum” to an “Resilient modulus at equilibrium” for the project site. Incorporating the climate and climate change of the project site into pavement design, particularly into the resilient modulus of the subgrade, will increase the durability and resilience of pavements.

The freight transport industry in Mexico has grown significantly since the establishment of trade agreements in North America, which has brought significant environmental consequences to the main transport corridors. This paper proposes a methodology for the estimation of emissions for freight vehicles on road transportation corridors. The variables included in this analysis allow adequate characterization of the conditions of the vehicle fleet, the geometry and the quality of the road, the environment, and the average annual daily traffic (AADT) of heavy vehicles. The results were structured to show two indicators, the amount of CO₂ emissions per kilometer and the amount of emissions per tonne transported. These results will allow establishing a baseline of CO₂ emissions through which we can implement actions in the road transport sector to reduce greenhouse gases (GHG) to mitigate climate change and develop parameter values for use in Cost Benefit Analysis. The indicators can also be applied to geospatial modeling of emissions in road transport corridors and forecast its growth.

Urban road intersections are among the most critical locations for road safety because they involve complex interactions among multiple road users, particularly during turning maneuvers, where conflicts between pedestrians and vehicles frequently occur. This study adopts an observational approach to develop four statistical models for identifying the factors that significantly influence pedestrian–vehicle interactions during both right- and left-turn maneuvers. The study contributes to the existing literature by explicitly incorporating left-turn maneuvers and proposing a practical simplification of social force variables into directly observable indicators. These simplified indicators proved to be statistically significant and effectively captured the dynamics of pedestrian–vehicle interactions, enabling safety analyses in environments where advanced sensing technologies or automated traffic-monitoring systems are unavailable. The proposed simplification of the social force methodology incorporates variables such as pedestrian direction change, pedestrian conflict, crossing behavior, crossing speed, trajectory within the intersection, and the pedestrian paths. Vehicle-related surrogate safety measures, including crossing time and vehicle speed, were also incorporated into the analysis. Specifically, near-crash events were defined using the post-encroachment time (PET) indicator, linking conflict-based safety measures with behavioral and geometric explanatory variables. Predictive performance was further evaluated through receiver operating characteristic (ROC) analysis. The final specification (Model 4) demonstrated excellent predictive accuracy, achieving an area under the curve (AUC) of 0.992. Traffic conditions, geometric characteristics, and the simplified social force variables emerged as the strongest predictors of near-crash occurrence. The most influential predictors included pedestrian direction change, zebra-crossing time, curve length, crossing length, and the absolute difference between design and available sight distance.