Rain-fog environments have an adverse effect on the security and reliability of transportation networks. Microscopic carfollowing models, a prevalent tool, are employed to quantify this negative influence. However, there exists no clear consensus in the literature regarding the appropriate calibration of these models in rain-fog environments. This study gathered traffic flow data in real-world conditions of normal, light rain, heavy fog, and rain-fog environments, and then calibrated the parameters of the GHR, FVD, and IDM models through the utilization of genetic algorithms. Lastly, the calibrated models were then validated through cross-validation. The results indicate that the calibrated GHR, FVD, and IDM models are capable of describing the variability of car-following behavior during adverse weather conditions. The validation analysis revealed that the IDM model had a validation error between 0.39 and 0.45 and more accurately replicated drivers' car-following behavior under rain-fog conditions compared to the GHR and FVD models. This study highlights the necessity of integrating rain-fog factors into existing microsimulation modeling practices, which can serve as a foundation for traffic organization and management in rain-fog environments.
Speed limit sign is an important measure to control driver’s driving speed and improve road traffic safety. It will have a series of impacts on the driver’s behavior, but the mechanism of its impact on the driver’s speed choice behavior is still unclear. In this study, three road scenes under different speed limit sign environments were constructed through UCwin/Road software, 20 drivers were recruited publicly, and a driving simulation test was carried out. Using mathematical statistics to summarize and analyze the data, taking the driving speed and acceleration of the drivers as the analysis indicators, the speed behaviors of the drivers when passing the speed limit sign were analyzed, and the influence rule of the speed limit sign on the driver’s speed selection was obtained. The results show that drivers tend to drive at high speed; the 100km/h and 80km/h speed limit signs have an impact on the speed choice of some drivers, but this impact is extremely limited, and drivers will still drive over the speed limit.
Five different RAPs were selected to perform gyratory compaction test at different testing temperatures (60 ℃ and 110 ℃) and compaction speeds (0.5 mm/s, 1.5 mm/s, 2.5 mm/s and 3.5 mm/s). The mechanical parameters (stress and strain) were recorded through AFG2 PINEPAVETM which was incorporated into the gyratory compactor. Results show that the stress and strain increase gradually with the compaction of RAPs. Different RAPs exhibit diverse stress and strain values under different temperatures and speeds of gyratory compaction. However, the changing rate of strain is almost the same with regard to different RAPs. The properties of RAP can be indirectly reflected based on these mechanical parameters, which is helpful for the evaluation of RAP performance and design of regenerated asphalt mixture.
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