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With increasing vehicle ownership and utilization in urban areas, parking robot systems have become a promising tool to cope with both the parking difficulties and hazards in parking lots. With assistance of the parking robot systems, vehicles are not human-operated in parking lots but fetched by a parking robot to the target places. This study starts by depicting the parking robot allocations and movements consisting of empty-loaded and loaded trips as well as picking-up and setting-down operations. Then, with multi-stage processes aiming to minimize the empty-loaded and loaded travel time, respectively, a two-stage allocation model was proposed to assign parking robots to vehicles and allocate the vehicles with target places. Furthermore, a cellular automaton (CA) simulation was introduced and extended with additional priority rules to solve potential travel conflicts occurring in parking lots. Basing on a campus parking lot in Shanghai, China, the flowchart of the CA simulation was proposed to implement and validate the proposed allocation model. The results demonstrate that, compared with the one-stage allocation model, the proposed allocation model has the potential to decrease queue length and waiting time both at parking lot entrances and parking spaces, which may assist in design and operation of future parking lots.

Background The aim of this study was to evaluate the application of pulse contour cardiac output (PiCCO) in patients with traumatic shock.Methods Seventy-eight patients with traumatic shock were included and grouped. The control group (CG, n = 39) underwent fluid resuscitation through transthoracic echocardiography (TTE) monitoring, and the research group (RG, n = 39) received PiCCO-guided fluid resuscitation.Results The mechanical ventilation time, duration of vasoactive drug use, and duration of stay in the intensive care unit were lower in the RG compared to the CG (P < .05). At 72 h after fluid resuscitation, the mean arterial pressure and central venous pressure in the RG were higher than those in the CG (P < .05). The stroke volume variation and distensibility index of the inferior vena cava were lower at 72 h after fluid resuscitation, but the levels of extravascular lung water, global end-diastolic volume index, and intrathoracic blood volume index were higher in the RG (P < .05). The levels of endothelial 1, nitrogen monoxide, tumor necrosis factor-α, procalcitonin, C-reactive protein, and partial pressure of carbon dioxide at 72 h after fluid resuscitation in the RG were lower than those in the CG (P < .05).Conclusion PiCCO-guided liquid resuscitation may help to accurately evaluate the volumetric parameters, alleviate symptoms of ischemia and hypoxia, regulate hemodynamics and blood gas analysis, reduce inflammatory reactions, improve endothelial functions, and effectively guide the usage of vascular active drugs.

Parking spaces are often in short supply in urban areas. To balance the supply and demand and alleviate the overconsumption of public spaces, parking variable message signs (parking VMSs) are commonly used to release information on space availability to drivers en route. The aim of this study was to find the optimal positions for parking VMSs. To achieve the objective, we first define the major decision point (MDP) as the intersection where the newly generated path deviates from the previous one. When informed that the target parking lot is fully occupied, the driver would divert to an alternative one. The route to the alternative parking lot is indicated as the newly generated path, while the one leading to the original parking lot is denoted as the previous one. Quantitatively, MDPs with the highest frequency of occurrence are selected as the candidate positions. Then, an agent-based simulation is proposed to identify the MDPs induced by changes of space availability and the selection of routes. The results indicate that the proposed location algorithm slightly outperforms the scheme with the completed parking information in terms of average travel time and average travel distance. The algorithm can be further integrated into a simulation package, which may assist in the design and operation of an urban parking guidance and information system.

In order to optimize the location of public parking facilities based on the optimal total social cost, location selection and scale settings are considered as the main contents. By analyzing the cost factors and the restrictions, a location model of public parking facilities is formulated with the objective to minimize the total social cost. Under the assumption that the requirement distribution of the public parking is agreed to the Gravity Model, the optimization algorithm of the schemes selection is proposed to fully search the solution space. Finally, a numerical example is carried out to illustrate the proposed model and the algorithm.