Information use by humans during dynamic route choice in virtual crowd evacuations

We conducted a computer-based experiment with over 450 human participants and used a Bayesian model selection approach to explore dynamic exit route choice mechanisms of individuals in simulated crowd evacuations. In contrast to previous work, we explicitly explore the use of time-dependent and time-independent information in decision-making. Our findings suggest that participants tended to base their exit choices on time-dependent information, such as differences in queue lengths and queue speeds at exits rather than on time-independent information, such as differences in exit widths or exit route length. We found weak support for similar decision-making mechanisms under a stress-inducing experimental treatment. However, under this treatment participants were less able or willing to adjust their original exit choice in the course of the evacuation. Our experiment is not a direct test of behaviour in real evacuations, but it does highlight the role different types of information and stress play in real human decision-making in a virtual environment. Our findings may be useful in identifying topics for future study on real human crowd movements or for developing more realistic agent-based simulations

Dynamic speed limit control to resolve shock waves on freeways : Field test results of the SPECIALIST algorithm

We present the real-world test of the SPECIALIST algorithm in which dynamic speed limits were used to resolve shock waves on freeways. The real-world test was performed in the period September 2009–February 2010 on a 14 km long stretch on the Dutch A12 freeway. For the evaluation of the algorithm various performance measures were determined for each activation of the speed limits. The results show that the SPECIALIST algorithm can resolve shock waves in nearly 80% of the cases when the algorithm activated for shock waves. However, in approximately 50% of the activations the algorithm activated for jam types other than shock waves, in which case the effectivity was 40– 50%. Due to the tuning the stability of the traffic flow could be significantly improved, and the number of average activations per day was increased from 1.5 to 2.9 activations per day. The SPECIALIST algorithm was not only evaluated for traffic performance, but also for the correctness of the algorithm for real traffic in terms of expected qualitative behavior. Although the general operation of the algorithm is according to the theoretical expectations, some points for further improvements are identified during the test

Pedestrian, Crowd, and Evacuation Dynamics

This contribution describes efforts to model the behavior of individual pedestrians and their interactions in crowds, which generate certain kinds of self-organized patterns of motion. Moreover, this article focusses on the dynamics of crowds in panic or evacuation situations, methods to optimize building designs for egress, and factors potentially causing the breakdown of orderly motion.Comment: This is a review paper. For related work see http://www.soms.ethz.c

Optimizing evacuation instructions while anticipating traveler compliance behavior

Instructing evacuees on their departure time, destination and route can lead to more efficient traffic operations. Empirical findings on evacuation behavior support the view that in practice a share of travelers decides not to comply, while current evacuation plan optimization techniques are limited to assessing mandatory evacuation under the assumption of full compliance. In this contribution we show I) how traveler compliance behavior affects evacuation efficiency, and II) how evacuation efficiency can be improved in case of partial compliance when this traveler compliance is anticipated on. The optimization method and case study application presented here underline the relevance and importance of capturing traveler compliance behavior, as this has a large impact upon the evacuation efficiency

Social density processes regulate the functioning and performance of foraging human teams

Social density processes impact the activity and order of collective behaviours in a variety of biological systems. Much effort has been devoted to understanding how density of people affects collective human motion in the context of pedestrian flows. However, there is a distinct lack of empirical data investigating the effects of social density on human behaviour in cooperative contexts. Here, we examine the functioning and performance of human teams in a central-place foraging arena using high-resolution GPS data. We show that team functioning (level of coordination) is greatest at intermediate social densities, but contrary to our expectations, increased coordination at intermediate densities did not translate into improved collective foraging performance, and foraging accuracy was equivalent across our density treatments. We suggest that this is likely a consequence of foragers relying upon visual channels (local information) to achieve coordination but relying upon auditory channels (global information) to maximise foraging returns. These findings provide new insights for the development of more sophisticated models of human collective behaviour that consider different networks for communication (e.g. visual and vocal) that have the potential to operate simultaneously in cooperative contexts

Automated Quality Assessment of Space-Continuous Models for Pedestrian Dynamics

In this work we propose a methodology for assessment of pedestrian models continuous in space. With respect to the Kolmogorov-Smirnov distance between two data clouds, representing for instance simulated and the corresponding empirical data, we calculate an evaluation factor between zero and one. Based on the value of the herein developed factor, we make a statement about the goodness of the model under evaluation. Moreover this process can be repeated in an automatic way in order to maximize the above mentioned factor and hence determine the optimal set of model parameters.Comment: 8 pages, 3 figures, accepted at the Proceedings of Traffic and Granular Flow '1

New Pharmacological Agents to Aid Smoking Cessation and Tobacco Harm Reduction: What has been Investigated and What is in the Pipeline?

A wide range of support is available to help smokers to quit and aid attempts at harm reduction, including three first-line smoking cessation medications: nicotine replacement therapy, varenicline and bupropion. Despite the efficacy of these, there is a continual need to diversify the range of medications so that the needs of tobacco users are met. This paper compares the first-line smoking cessation medications to: 1) two variants of these existing products: new galenic formulations of varenicline and novel nicotine delivery devices; and 2) twenty-four alternative products: cytisine (novel outside of central and eastern Europe), nortriptyline, other tricyclic antidepressants, electronic cigarettes, clonidine (an anxiolytic), other anxiolytics (e.g. buspirone), selective 5-hydroxytryptamine (5-HT) reuptake inhibitors, supplements (e.g. St John’s wort), silver acetate, nicobrevin, modafinil, venlafaxine, monoamine oxidase inhibitors (MAOI), opioid antagonist, nicotinic acetylcholine receptors (nAChR) antagonists, glucose tablets, selective cannabinoid type 1 receptor antagonists, nicotine vaccines, drugs that affect gamma-aminobutyric acid (GABA) transmission, drugs that affect N-methyl-D-aspartate receptors (NMDA), dopamine agonists (e.g. levodopa), pioglitazone (Actos; OMS405), noradrenaline reuptake inhibitors, and the weight management drug lorcaserin. Six criteria are used: relative efficacy, relative safety, relative cost, relative use (overall impact of effective medication use), relative scope (ability to serve new groups of patients), and relative ease of use (ESCUSE). Many of these products are in the early stages of clinical trials, however, cytisine looks most promising in having established efficacy and safety and being of low cost. Electronic cigarettes have become very popular, appear to be efficacious and are safer than smoking, but issues of continued dependence and possible harms need to be considered

High-statistics modeling of complex pedestrian avoidance scenarios

Quantitatively modeling the trajectories and behavior of pedestrians walking in crowds is an outstanding fundamental challenge deeply connected with the physics of flowing active matter, from a scientific point of view, and having societal applications entailing individual safety and comfort, from an application perspective. In this contribution, we review a pedestrian dynamics modeling approach, previously proposed by the authors, aimed at reproducing some of the statistical features of pedestrian motion. Comparing with high-statistics pedestrian dynamics measurements collected in real-life conditions (from hundreds of thousands to millions of trajectories), we modeled quantitatively the statistical features of the undisturbed motion (i.e. in absence of interactions with other pedestrians) as well as the avoidance dynamics triggered by a pedestrian incoming in the opposite direction. This was accomplished through (coupled) Langevin equations with potentials including multiple preferred velocity states and preferred paths. In this chapter we review this model, discussing some of its limitations, in view of its extension toward a more complex case: the avoidance dynamics of a single pedestrian walking through a crowd that is moving in the opposite direction. We analyze some of the challenges connected to this case and present extensions to the model capable of reproducing some features of the motion

“Charge while driving” for electric vehicles: road traffic modeling and energy assessment

The aim of this research study is to present a method for analyzing the performance of the wireless inductive charge-while-driving (CWD) electric vehicles, from both traffic and energy points of view. To accurately quantify the electric power required from an energy supplier for the proper management of the charging system, a traffic simulation model is implemented. This model is based on a mesoscopic approach, and it is applied to a freight distribution scenario. Lane changing and positioning are managed according to a cooperative system among vehicles and supported by advanced driver assistance systems (ADAS). From the energy point of view, the analyses indicate that the traffic may have the following effects on the energy of the system: in a low traffic level scenario, the maximum power that should be supplied for the entire road is simulated at approximately 9 MW; and in a high level traffic scenario with lower average speeds, the maximum power required by the vehicles in the charging lane increases by more than 50