A pedestrian path-planning model in accordance with obstacle's danger with reinforcement learning

Most microscopic pedestrian navigation models use the concept of "forces" applied to the pedestrian agents to replicate the navigation environment. While the approach could provide believable results in regular situations, it does not always resemble natural pedestrian navigation behaviour in many typical settings. In our research, we proposed a novel approach using reinforcement learning for simulation of pedestrian agent path planning and collision avoidance problem. The primary focus of this approach is using human perception of the environment and danger awareness of interferences. The implementation of our model has shown that the path planned by the agent shares many similarities with a human pedestrian in several aspects such as following common walking conventions and human behaviours

Pedestrian Traffic: on the Quickest Path

When a large group of pedestrians moves around a corner, most pedestrians do not follow the shortest path, which is to stay as close as possible to the inner wall, but try to minimize the travel time. For this they accept to move on a longer path with some distance to the corner, to avoid large densities and by this succeed in maintaining a comparatively high speed. In many models of pedestrian dynamics the basic rule of motion is often either "move as far as possible toward the destination" or - reformulated - "of all coordinates accessible in this time step move to the one with the smallest distance to the destination". Atop of this rule modifications are placed to make the motion more realistic. These modifications usually focus on local behavior and neglect long-ranged effects. Compared to real pedestrians this leads to agents in a simulation valuing the shortest path a lot better than the quickest. So, in a situation as the movement of a large crowd around a corner, one needs an additional element in a model of pedestrian dynamics that makes the agents deviate from the rule of the shortest path. In this work it is shown, how this can be achieved by using a flood fill dynamic potential field method, where during the filling process the value of a field cell is not increased by 1, but by a larger value, if it is occupied by an agent. This idea may be an obvious one, however, the tricky part - and therefore in a strict sense the contribution of this work - is a) to minimize unrealistic artifacts, as naive flood fill metrics deviate considerably from the Euclidean metric and in this respect yield large errors, b) do this with limited computational effort, and c) keep agents' movement at very low densities unaltered

Modeling, Evaluation, and Scale on Artificial Pedestrians: A Literature Review

Modeling pedestrian dynamics and their implementation in a computer are challenging and important issues in the knowledge areas of transportation and computer simulation. The aim of this article is to provide a bibliographic outlook so that the reader may have quick access to the most relevant works related to this problem. We have used three main axes to organize the article's contents: pedestrian models, validation techniques, and multiscale approaches. The backbone of this work is the classification of existing pedestrian models; we have organized the works in the literature under five categories, according to the techniques used for implementing the operational level in each pedestrian model. Then the main existing validation methods, oriented to evaluate the behavioral quality of the simulation systems, are reviewed. Furthermore, we review the key issues that arise when facing multiscale pedestrian modeling, where we first focus on the behavioral scale (combinations of micro and macro pedestrian models) and second on the scale size (from individuals to crowds). The article begins by introducing the main characteristics of walking dynamics and its analysis tools and concludes with a discussion about the contributions that different knowledge fields can make in the near future to this exciting area

Queuing Rule of Thumb based on M/M/s Queuing Theory with Applications in Construction Management

The current trend of queuing theory development is toward more precision which requires higher mathematical manipulation. In this paper, we attempted to reverve the current trend toward simplification of queuing formulas such that it can be used in more practical purposes, especially in construction industry. Through numerical examples of two case studies on concreting and earth moving, how to model the construction activities as queuing systems is illustrated systematically. Through the numerical examples, it is shown that when the customer cost is much lower than the server cost, queuing system can be simplified only to incorporate the constraint equation. The queueing constraint equation is suggested to be used as queuing rule of thumb. The proposed rule of thumb is rather conservative in term of queuing performance compared to the standard stochastic queuing formula because it is assumed that all the customers arrive at once in the beginning of the service