In order to investigate collective effects of interactions between pedestrians and attractions, this study extends the social force model. Such interactions lead pedestrians to form stable clusters around attractions, or even to rush into attractions if the interaction becomes stronger. It is also found that for high pedestrian density and intermediate interaction strength, some pedestrians rush into attractions while others move to neighboring attractions. These collective patterns of pedestrian movements or phases and transitions between them are systematically presented in a phase diagram. The results suggest that safe and efficient use of pedestrian areas can be achieved by moderating the pedestrian density and the strength of attractive interaction, for example, in order to avoid situations involving extreme desire for limited resources.

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Walking is a fundamental activity of our daily life not only for moving to other places but also for interacting with surrounding environment. While walking on the streets, pedestrians can be aware of attractions like shopping windows. They can be influenced by the attractions and some of them might shift their attention towards the attractions, namely switching behavior. As a first step to incorporate the switching behavior, this study investigates collective effects of switching behavior for an attraction by developing a behavioral model. Numerical simulations exhibit different patterns of pedestrian behavior depending on the strength of the social influence and the average length of stay. When the social influence is strong along with a long length of stay, a saturated phase can be defined at which all the pedestrians have visited the attraction. If the social influence is not strong enough, an unsaturated phase appears where one can observe that some pedestrians head for the attraction while others walk in their desired direction. These collective patterns of pedestrian behavior are summarized in a phase diagram by comparing the number of pedestrians who visited the attraction to the number of passersby near the attraction. Measuring the marginal benefits with respect to the strength of the social influence and the average length of stay enables us to identify under what conditions enhancing these variables would be more effective. The findings from this study can be understood in the context of the pedestrian facility management, for instance, for retail stores.

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Purpose Road lighting illuminates road surface and surrounding areas of objects on a road, while car headlights illuminate vertical objects on a road. The goal of the study was to investigate the interaction between road lighting and car headlights at target detection distance. Method Target detection distances under different road lighting intensities and car headlights were studied with and without glare from an oncoming car. Dimmable high-pressure sodium lamps with three lighting levels 49, 71 and 100% (3557, 5179 and 7252 lm) were used. Test drivers had to detect a small uniform standard target standing vertically on the straight road. Results In the absence of glare (low beam car headlights), road lighting intensity levels of 100 and 49% provided comparable detection distances, while at 71% of road lighting intensity visibility was the lowest. The target was seen in negative or positive contrast in 100% of road lighting. In 71% of road lighting, the target was detected in positive contrast. While, in 49% of road lighting target was seen in negative contrast. There was a significant difference in detection distances under different road lighting intensities when there was no glare from the oncoming car. The significance main effect was between 49 and 71% of road lighting intensities. In addition, no significant differences in the effect of road lighting intensities could be found under glare from the oncoming car. In the presence of glare from the oncoming car, targets were always in negative contrast. Both road lighting and car headlights are associated with detection distances. Conclusion The results of these experiments can give new insight to the development of intelligent road lighting considering the combined effect of road lighting and car headlights. The results provide useful insight to dim the lighting in order to save energy without impairing the detection of objects.