Development of Self-Sensing Asphalt Pavements: Review and Perspectives.

The digitalization of the road transport sector necessitates the exploration of new sensing technologies that are cost-effective, high-performing, and durable. Traditional sensing systems suffer from limitations, including incompatibility with asphalt mixtures and low durability. To address these challenges, the development of self-sensing asphalt pavements has emerged as a promising solution. These pavements are composed of stimuli-responsive materials capable of exhibiting changes in their electrical properties in response to external stimuli such as strain, damage, temperature, and humidity. Self-sensing asphalt pavements have numerous applications, including in relation to structural health monitoring (SHM), traffic monitoring, Digital Twins (DT), and Vehicle-to-Infrastructure Communication (V2I) tools. This paper serves as a foundation for the advancement of self-sensing asphalt pavements by providing a comprehensive review of the underlying principles, the composition of asphalt-based self-sensing materials, laboratory assessment techniques, and the full-scale implementation of this innovative technology.

Safety analysis of motorcyclists' overtaking maneuvers.

This paper aims to investigate the overtaking behavior of motorcyclists in a suburban environment. The goal is to model overtaking duration, identify the factors influencing it, and determine the likelihood of a rider overtaking a vehicle while maintaining critical lateral clearance. Riding data were collected using a passenger car equipped with cameras and a GPS device, which recorded videos of motorcyclists performing maneuvers to overtake it. This setup allowed for capturing natural motorcyclist behavior and avoided the potential limitations of instrumented motorcycle studies, such as bias due to participants being aware of their involvement in the experiment. A total of 119 overtaking maneuvers were recorded. A methodology combining digital image processing algorithms and GPS analysis was employed to characterize the recorded maneuvers. Survival and logistic analyses were then conducted to model the duration of overtaking and lateral clearance, respectively. The hazard-based duration model indicated that the duration of a motorcyclist's overtaking maneuver is influenced by the final longitudinal distance between the motorcycle and the passed vehicle at the end of the maneuver. Other factors include the speed difference between the motorcycle and the front vehicle at the same instant, and the initial Time-To-Collision (TTC) between the motorcycle and the front vehicle at the beginning of the overtaking. The logistic regression analysis revealed that the probability of overtaking a vehicle with a lateral clearance below the critical threshold increases when the rider does not invade the opposite lane during the overtaking maneuver when a vehicle in the opposite lane induces the motorcyclist to return to the right lane, and as the duration of the overtaking maneuver increases. This research provides valuable contributions to understanding motorcyclist behavior during overtaking maneuvers, aiding in the development of more realistic microsimulation models that account for actual rider behavior. Additionally, the study contributes to the development of Advanced Rider Assistance Systems aimed at guiding motorcyclists to make safer overtaking decisions and reduce significant risk exposure from complex overtaking maneuvers.

A hazard-based model of the motorcyclists' overtaking duration.

The overtaking maneuver performed by motorcyclists is one of the primary causes of motorcycle accidents. However, few studies in the literature deal with this topic and there are no studies modeling the total overtaking duration, i.e. the time during which extreme hazards are manifest. The present paper aims to analyze the motorcyclists' behavior during overtaking and to model the total overtaking duration. A field experiment, using instrumented motorcycles, was performed to collect data and a survival analysis was carried out to model the total overtaking duration. Twenty young motorcyclists drove their own motorcycles, which were instrumented with a camera and a global positioning system device (GPS), onto a two-lane suburban road in Rome. A total of 101 overtaking maneuvers were recorded. A methodology, based on video and GPS analyses, was developed to obtain data describing the motorcyclists' behavior. The obtained results showed that the mean values of the main parameters of the overtaking maneuver (total overtaking duration - 6.6 s - and distance - 109.7 m - lateral distance from the passed vehicle - 1.50 m) were consistent with the few data available in the revised literature. The total overtaking duration was modelled using a hazard-based duration model. The parametric accelerated failure time duration model with a log-logistic distribution, which was the best-fitted distribution, identified the covariates which affected, in a statistically significant way, the total overtaking duration. The obtained model revealed that the overtaking duration depends on several covariates. The greater average impact was found for the initial distance and speed difference, while the initial lateral distance and final distance produced a minor impact. When performing a multiple overtaking, the duration of the maneuver tended to increase by 31 %. This research can be considered as a pilot study and a starting point for future advances on motorcyclists' behavior during overtaking maneuver and for modeling the total overtaking duration. In addition, the findings of this study could contribute to the development of advanced rider assistance systems for the overtaking maneuver based on current driving conditions.