Use of Foamed Cement Banking for Reducing Expressways Embankment Settlement

Expressways are often built on soft ground, the foundation of which is not processed adequately during the construction period. Consequently, the traffic safety and embankment stability will be seriously affected due to uneven settlement. The technology of holing the embankment and replacing foamed cement banking (FCB) could control the settlement of an embankment without road closure, thus reduce the impact of construction on normal operation of highways. In this paper, the principle of FCB is described. Additionally, a sedimentation ratio calculation method, through the analysis of the settlement load ratio, is proposed for calculating the roadbed replacement thickness. This paper takes the example of the test section EK0 + 323 on Shen-Jia-Hu expressway in Zhejiang Province and combines with site settlement monitoring data to confirm the effectiveness of the calculation method proposed.

Towards Autonomous Bridge Inspection: Sensor Mounting Using Aerial Manipulators

Periodic bridge inspections are required every several years to determine the state of a bridge. Most commonly, the inspection is performed using specialized trucks allowing human inspectors to review the conditions underneath the bridge, which requires a road closure. The aim of this paper was to use aerial manipulators to mount sensors on the bridge to collect the necessary data, thus eliminating the need for the road closure. To do so, a two-step approach is proposed: an unmanned aerial vehicle (UAV) equipped with a pressurized canister sprays the first glue component onto the target area; afterward, the aerial manipulator detects the precise location of the sprayed area, and mounts the required sensor coated with the second glue component. The visual detection is based on an Red Green Blue - Depth (RGB-D) sensor and provides the target position and orientation. A trajectory is then planned based on the detected contact point, and it is executed through the adaptive impedance control capable of achieving and maintaining a desired force reference. Such an approach allows for the two glue components to form a solid bond. The described pipeline is validated in a simulation environment while the visual detection is tested in an experimental environment.

DYNAMIC ROUTING FOR NAVIGATION IN CHANGING UNKNOWN MAPS USING DEEP REINFORCEMENT LEARNING

In this work, we propose an approach for an autonomous agent that learns to navigate in an unknown map in a real-world environment. Recognizing that the real-world environment is changing overtime such as road-closure happening due to construction work, a key contribution of our paper is adopt the dynamic adaptation characteristic of the reinforcement learning approach and develop a dynamic routing ability for our agent. Our method is based on the Q-learning algorithm and modifies it into a double-critic Qlearning model (DCQN) that only uses visual input without other aids such as GPS. Our treatment of the problem enables the agent to learn the navigation policy while interacting with the environment. We demonstrate that the agent can learn navigating to the destination kilometers away from the starting point in a real world scenario and has the ability to respond to environment changes while learning to adjust the routing plan dynamically by adjusting the old knowledge. The supplementary video can be accessed at the following link: https://www.youtube.com/watch?v=tknsxVuNwkg.

Real-time Rockfall Detection System with Automatic Road Closure and Reopening using Doppler Radar Technology at the Ruinon Landslide, Italy

<p>Transportation corridors in mountain regions are often situated at the bottom of narrow valleys. Changing slope stability conditions can put these routes at critical risk. Slope stabilization works (e.g., rock scaling, blasting) or structural protection measures (e.g., rock sheds, reinforced embankments, tunnels) are not always feasible or may not be cost-effective due to low average daily traffic or the expected event size. Route SP29 is the main connection road to Santa Catarina, a popular tourist resort in the Frodolfo River Valley, Lombardy, Italy. The Ruinon landslide is a major slope instability involving approximately 30 million m<sup>3</sup> of rock and debris and causes repeated rockfalls that can reach as far as the road. </p><p>We present a Doppler radar system for real-time rockfall detection and immediate road closure in case of an event. The rockfall radar permanently monitors the landslide area from the opposite side of the slope with a range of more than 1 km to the upper scarp. Radar technology works reliably regardless of visibility, i.e. in rain, fog or snowfall as well as at night. After an initial calibration period in summer 2020, we activated automatic road closure and reopening in case of a rockfall event; upon detection of rockfall in a defined region of interest, the radar system automatically switches the traffic lights to red. If the rock fall event reaches a defined zone near the road or the road itself, it remains closed and requires manual reset after site inspection with webcams at the radar site and the traffic lights. If the rockfall event remains above the road, then the radar system automatically releases the road again after 90 seconds. Automatic notifications about the status are sent to authorized user via email and SMS. In addition to the deployment of the alarm system using Doppler radar, the embankment along the endangered road section was reinforced and raised. These combined measures of protection structures and alarm system aim at maximising the opening hours of the street while providing the highest possible level of protection. Between July (installation) and December 2020, 60 rockfall events caused a road closure, with the road being automatically reopened by the system in approximately 85% of cases.</p>

River ice phenology and thickness from satellite altimetry. Potential for ice bridge road operation

River ice is an important component of land cryosphere. Satellite monitoring of river ice is rapidly developing scientific area with an important outcome for many climate, environmental and socio-economic applications. Radar altimetry, now widely used for monitoring of river water regime, demonstrates a good potential for observation of river ice phenology and for an estimation of river ice thickness. Jason-2 and -3 Ku-band backscatter measurements are sensitive enough for detection of first appearance of the ice and of beginning of thermal ice degradation on the Lower Ob River (Western Siberia). Uncertainties of the altimetric ice events timing are less than 10 days for 88–90 % of cases. River ice thickness retrieved from altimetric measurements via empirical relations with in situ observations, has an accuracy (expressed as RMSE) varying from 0.07 to 0.18 m. We demonstrated that using satellite altimetry the dates of ice road opening at Salekhard city can be predicted quite accurately with 4 days delay. Uncertainties for the prediction of dates of the ice road closure are of 3 days with the delay varying from 4 days (for late melting start) to 22 days (for yearly melting start).

FAT tool: A decision support tool for disaster risk reduction in the Alpine Space

<p>The last decades have seen a higher attention payed to natural hazards due to the increasing losses and economic damages caused by them. Researchers, practitioners and local administrations studied the best way to mitigate and prevent them, using both structural and non-structural  defense techniques. Even though there are now several possible solutions to be used, it is not always easy for decision makers to choose the best option from both a technical and an economical point of view.</p><p>With the FAT tool we aimed at providing a useful mean for practitioners to help them choose between various protection options. The FAT tool is an online platform where the user, inserting a limited number of input data (e.g. slope profile, slope width, forest cover), is provided with an easily understandable output, that being a comparison of the costs and the benefits generated by different protection solutions.</p><p>The tool is built on an empirical, profile-based hazard model and deals with avalanches, rockfall and shallow landslides. The outputs of the hazard models are used to dimension and calculate the costs and benefits of several protection options and the damages avoided by those. The possible solutions considered are: ecosystem based solutions (e.g. protection forest), technical measures (e.g. snow fences, catching dams, rockfall nets), avoidance measures (e.g. road closure, building evacuation) and a combination of these. The most innovative part of the tool is the importance given to the role of the forest, and generally to the Eco-DRR solutions, on the hazard track, where a forest protection effect indicator is calculated to assess the effectiveness of a stand in mitigating the risk on the chosen profile. The outputs of the FAT tool, consisting in the index and the economic values of different alternative protection measures, can help the user identify the areas where the forests have the highest mitigation effect and choose where to allocate forest management resources.</p>