Tactical Layer Research Articles

Modeling Pedestrian Detour Behavior By-Passing Conflict Areas

In the process of walking, most pedestrians prefer to choose the shortest path, which requires passing through the conflict area. However, in the case of high crowd density, 5–20% of the total population will choose to follow the pre-planned route before walking or during the initial period of the trip to bypass the conflict area. Aiming at reproducing this detour behavior phenomenon, an extended social force model (SFM) is proposed according to a three-layer pedestrian simulation framework. This model not only fully considers the choice of detour mode, but also contains the avoidance and game behavior at the conflict point. At the strategic layer, a detour mode selection model based on the Logit model is established considering the pedestrian starting time and detour angle, to distinguish between the two groups of pedestrians who follow the pre-planned route and those who repeatedly adjust the route during the trip. Then, the path decision based on visual perception density at the tactical layer and the Voronoi-based SFM at the operational layer are combined to guide the specific movement of the two types of pedestrian groups. A series of evaluation indexes such as the central density, the mean local density, and detour level is selected, and Kolmogorov–Smirnov (K-S) test and dynamic time warping (DTW) method are used to evaluate and compare the scores of each index of different models. The results show that the model can improve the existing pedestrian detour simulation model to a certain extent. In sum, the travel time score, the detour level, and the mean local density score respectively increase from 0.71 to 0.81, 0.46 to 0.81, and 0.39 to 0.48, which indicates a significant improvement in walking performance.

A Platoon-Based Hierarchical Merging Control for On-Ramp Vehicles Under Connected Environment

Connected autonomous vehicle technology is conductive to promoting the transition from traditional merging control (e.g., ramp metering) to automated merging control. This paper proposes a platoon-based hierarchical merging control algorithm for on-ramp vehicles to achieve automated merging control under connected traffic environment. The proposed algorithm optimizes merging maneuvers of on-ramp vehicles to smooth their merging trajectories without frequent decelerations or stops at the end of the ramp, and to minimize disruption to the mainline traffic in the merging zone. A tactical layer controller is designed to select pre-target merging gaps for on-ramp vehicles, in which the future motion (i.e., acceleration and deceleration) of mainline vehicles is considered through the grey prediction model. An operational layer controller is constructed based on model predictive control to adjust the speed of on-ramp vehicles in advance, and controls on-ramp vehicles to merge into the pre-target merging gaps under state constraints (i.e., safe headway, maximum speed and so on). Through numerical simulation, the effectiveness of the proposed algorithm is validated under different merging scenarios. It is shown that on-ramp vehicles smoothly merge into the mainline within the pre-target merging gap at the same speed as adjacent mainline vehicles. Compared with the baseline merging control algorithm, the proposed algorithm significantly reduces both fuel consumption and travel time of on-ramp vehicles, and improves passenger comfort.

Preliminary Experimental Results of Context-Aware Teams of Multiple Autonomous Agents Operating under Constrained Communications

This work presents and experimentally tests the framework used by our context-aware, distributed team of small Unmanned Aerial Systems (SUAS) capable of operating in real time, in an autonomous fashion, and under constrained communications. Our framework relies on a three-layered approach: (1) an operational layer, where fast temporal and narrow spatial decisions are made; (2) a tactical layer, where temporal and spatial decisions are made for a team of agents; and (3) a strategical layer, where slow temporal and wide spatial decisions are made for the team of agents. These three layers are coordinated by an ad hoc, software-defined communications network, which ensures sparse but timely delivery of messages amongst groups and teams of agents at each layer, even under constrained communications. Experimental results are presented for a team of 10 small unmanned aerial systems tasked with searching for and monitoring a person in an open area. At the operational layer, our use case presents an agent autonomously performing searching, detection, localization, classification, identification, tracking, and following of the person, while avoiding malicious collisions. At the tactical layer, our experimental use case presents the cooperative interaction of a group of multiple agents that enables the monitoring of the targeted person over wider spatial and temporal regions. At the strategic layer, our use case involves the detection of complex behaviors, i.e., the person being followed enters a car and runs away, or the person being followed exits the car and runs away, which require strategic responses to successfully accomplish the mission.

A Hierarchical Model-Based Optimization Control Approach for Cooperative Merging by Connected Automated Vehicles

Gap selection and dynamic speed profiles of interacting vehicles at on-ramps affect the safety and efficiency of highway merging sections. This paper puts forward a hierarchical control approach for Connected Automated Vehicles (CAVs) to achieve efficient and safe merging operations. A tactical layer controller employs a second-order car-following model with a cooperative merging mode to represent a cooperative merging process and generates an optimal vehicle merging sequence and time instants when on-ramp CAVs start to adapt their speeds and positions to prepare merging into the target gaps respectively. An operational layer controller is designed based on Model Predictive Control (MPC). It uses a third-order vehicle dynamics model and optimizes desired accelerations for CAVs and the time instants when the on-ramp CAVs initiate the lane-changing executions respectively. Both the tactical layer controller and operational layer controller derive their control commands by minimizing an objective function for different time horizons. The objective function penalizes deviations of CAVs’ inter-vehicle gaps to their desired values, relative speeds to their direct predecessors, and actual or desired accelerations, subject to constraints on velocities, actual or desired accelerations, and inter-vehicle gaps. The performance of the proposed hierarchical control framework and a benchmark on-ramp merging method using a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">first-in-first-out</i> rule to determine the merging sequence is demonstrated under 135 scenarios with different initial conditions, desired time gap settings, and numbers of on-ramp vehicles. The experimental results show the superiority of the hierarchical control approach.

Profits comparison between alliance mode and non-alliance mode of empty containers repositioning of liner companies

ABSTRACTAlliance and non-alliance modes are the typical decision-making problem of strategy layer. Upper layer decision will have direct impact on the lower two layers: tactical layer and operational layer. Empty container repositioning mechanism must be keep synchronous operation according to the upper two layers. To quantitative analyse the impact of two modes of strategy layer, we have built the optimization models of empty containers repositioning according to the actual business flow. Two simulation cases have been designed to solve the models. The experimental data show that under alliance it can reduce various costs dramatically and improve the profits contrast to the non-alliance. The results validate the proposed standpoint: alliance mode is feasible for different company sizes. All companies in consolidation can obtain win–win. Furthermore, the reduced various costs such as transportation cost also mean lower greenhouse gas emissions, which is importance to keep sustainable development for the earth.

Combining MPC and integer operators for capacity adjustment in job-shop systems with RMTs

With today's worldwide competition, manufacturing companies are faced with challenges to respond to volatile market demands quickly and flexibly while maintaining a cost-effective level of production. Capacity adjustment is one of the major approaches to cope with such uncertain fluctuations, balance capacity and load and improve the effectiveness of manufacturing control. Instead of flexible staffs, working time and outsourcing, in this paper, we consider a machinery-based capacity adjustment via Reconfigurable Machine Tools (RMTs) to compensate for unpredictable events. To include these tools effectively on the operational and tactical layer, we propose a complementing feedback approach using model predictive control (MPC) to identify the potential of RMTs for a better compliance with logistics objectives and a sustainable demand oriented capacity allocation. To this end, we formulate a reconfiguration rule for the determination of the triggered RMTs and propose three strategies for resolving the integer assignment of RMTs: floor operator, genetic algorithm as well as branch and bound. Utilising simulation, we demonstrate the effectiveness of the proposed method for a four-workstation job-shop system.

Cooperative Automated Maneuvering at the 2016 Grand Cooperative Driving Challenge

Cooperative adaptive cruise control and platooning are well-known applications in the field of cooperative automated driving. However, extension toward maneuvering is desired to accommodate common highway maneuvers, such as merging, and to enable urban applications. To this end, a layered control architecture is adopted. In this architecture, the tactical layer hosts the interaction protocols, describing the wireless information exchange to initiate the vehicle maneuvers, supported by a novel wireless message set, whereas the operational layer involves the vehicle controllers to realize the desired maneuvers. This hierarchical approach was the basis for the Grand Cooperative Driving Challenge (GCDC), which was held in May 2016 in The Netherlands. The GCDC provided the opportunity for participating teams to cooperatively execute a highway lane-reduction scenario and an urban intersection-crossing scenario. The GCDC was set up as a competition and, hence, also involving assessment of the teams’ individual performance in a cooperative setting. As a result, the hierarchical architecture proved to be a viable approach, whereas the GCDC appeared to be an effective instrument to advance the field of cooperative automated driving.

Israel's military public diplomacy evolution: Historical and conceptual dimensions

This study provides an historical overview of the IDF Spokesperson’s Unit (ISU) from the early years of the State of Israel until 2009. Analyzing five periods during which the ISU played a key role in Israel's public diplomacy, this research sheds light on the challenges the ISU faced in different periods and circumstances and examines how the ISU tried to modify its methods and actions in response to geopolitical changes and media development, albeit not always successfully. The study suggests better understanding the adaptation process by applying a three-layer framework for analysis: the tactical layer, the strategic layer and the perceptional layer. The findings of this work demonstrate that in adapting to new circumstances, the ISU focused mainly on the tactical response level, with the result that it did not undertake any review or debate over the need for deeper perceptional changes in ISU policies.

Enable Better and Timelier Decision-Making Using Real-Time Business Intelligence System

Today's businesses need support when making decisions. Business intelligence (BI) helps businesses to make decisions based on good pre-analysis and documented data, and enables information to be presented when and where the decisions need to be made. Real time business intelligence (RTBI) presents numbers in real time, providing the decision makers at the operational and tactical layers with data as fresh as it can

An Integrated Approach to Assess Manufacturing Greenness Level

This paper proposes an integrated approach for relative greenness level assessment in selected manufacturing industries at the system level. The approach builds on existing methodologies to develop a multi-layer tool box called “Greenometer” which focus on the strategic comparison for cross industries evaluation as well as tactical comparison for intra-industries. The assessment tool captures the fundamental evaluation parameters of green manufacturing namely; Environment, Energy, Resources and Economy. In addition, the Greenometer employs geometric mean method (GMM) for the strategic layer and data envelopment analysis (DEA) for the tactical layer and will be used for different selected manufacturing disciplines. The proposed tool will have a practical impact on assessing, developing and improving environmental plans and policies of the selected industries.

Developing a content maintenance and governance strategy

The Missing Piece of Content Management Information and content governance is frequently a missing piece of a content management plan. Think of building the new content management system (CMS) as building a new house.You design the layout of the house and requirements based on the needs of your family. Then you move into the house. In preparation for the move, you put all of your possessions in boxes and mark those boxes to indicate where they will be going in the new home. If you are moving into a larger home, you’ll likely take items that were in a single room and put them into multiple rooms.

Global change and regional integrity

Abstract Global changes involve multiple, strongly interactive systems and strong regional differentiation. Reality is extremely complex, and it is hard to model Global Change on a regional level, particularly for formerly communist areas of Central and Eastern Europe, where it is imperative that the analytic framework provide insight for restructing after collapse. The Applied Landscape Ecology (ALO) section of Umweltforschungszentrum Leipzig-Halle (UFZ), approached this methodological quandary with a hierarchical research framework which allows for interaction of conceptual (strategic), operational (dynamic), and tactical (detailed informational) layers. After a year of work, we find that our plan was conceptually naive in assuming that existing models could be adapted to address the critical problems in our region, and operationally naive in not allowing for people, procedures, organizational culture and politics.