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Advanced Driving Assistance System (ADAS) can predict pedestrian's trajectory, in order to avoid traffic accidents and guarantee driving safety. A few current pedestrian trajectory prediction methods use a pedestrian's historical motion to predict the future trajectory, but the pedestrian's trajectory is also affected by the vehicle using the ADAS for prediction (target vehicle). Other studies predict the pedestrian's and vehicle's trajectories separately, and use the latter to adjust the former, but their interaction is a continuous process and should be considered during prediction rather than after. Therefore, we propose PVII, a pedestrian-vehicle interactive and iterative prediction framework for pedestrian's trajectory. It makes prediction for one iteration based on the results from previous iteration, which essentially models the vehicle-pedestrian interaction. In this iterative framework, to avoid accumulation of prediction errors along with the increased iterations, we design a bi-layer Bayesian en/decoder. For each iteration, it not only uses inaccurate results from previous iteration but also accurate historical data for prediction, and calculates Bayesian uncertainty values to evaluate the results. In addition, the pedestrian's trajectory is affected by both target vehicle and other vehicles around it (surrounding vehicle), so we include into the framework a pre-trained speed estimation module for surrounding vehicles (SE module). It estimates the speed based on pedestrian's motion and we collect data from pedestrian's view for training. In experiments, PVII can achieve the highest prediction accuracy compared to the current methods. [ABSTRACT FROM AUTHOR]

This paper presents two novel solution approaches for addressing large-scale multi-floor process plant layout problems. Based on the mixed integer linear programming (MILP) model, the first solution approach employs a multi-directional search strategy while the second improves solution efficiency by reducing model size through an iterative framework. Both approaches determine the spatial arrangement of the plant equipment considering equipment-floor allocation, non-overlapping constraints, tall equipment penetrating multiple floors, etc. The computational results indicate that the proposed approaches achieved potential cost savings for four illustrative examples when compared to the previous studies. Finally, engineering experience constraints were included to represent a more complex industrial situation, and their applicability was tested with the last example. [ABSTRACT FROM AUTHOR]

The interconnection and synchronization among different transport modes have been more and more attractive as the modern transportation system is moving towards Mobility-as-a-Service. In this study, we address the train scheduling problem for "commuter rail-metro" systems, where the trains from commuter rail lines can go directly into metro systems to provide seamless services for passengers. To optimize the schedule of trains for both commuter rail lines and metro lines, we propose a job shop scheduling model where precedence constraints from commuter-metro networks are taken into account and develop a mixed-integer programming (MIP) model with quadratic constraints. Our model considers the orders of different types of trains and the safety constraints, due to different types of signalling equipment in commuter and metro systems. Since these constraints involve a set of IF-THEN rules, we prove that these constraints can be equivalently reformulated as linear inequalities, without adding new variables. To solve the proposed model efficiently, we design an iterative solution framework, which generates a feasible solution using dynamic programming, next solves a MIP model, then calculates the train speed profiles, and if train speed profiles violate the safety constraints, re-optimizes the MIP model with modified alternative constraints. To verify the effectiveness of the proposed approaches, numerical experiments are performed on small and real-world instances based on the Beijing metro Line 1 and the Batong Line operational data. • Train scheduling and train speed management in commuter-metro networks. • A mixed-integer quadratic programming model based on the job shop scheduling. • We propose an iterative solution methodology for our integrated scheduling problem. • Results verify the effectiveness of our approaches and derive managerial insights. [ABSTRACT FROM AUTHOR]