Age-driven Crossing Behavior and Walkability: Empirical Studies towards Simulations

The necessity to guarantee the comfort and safety of the elderly pedestrians while walking and crossing in urban environments can be supported by the use of advanced computer-based simulations. Nowadays, simulation of vehicular and pedestrian traffic is a consolidated application domain, but integrated models considering the interactions between these two entities still lack empirical evidences to produce validated simulations. In this paper we introduce the results of two empirical studies aimed at assessing the walkability degree perceived by the elderly inhabitants of a specific area of the city of Milan, considering the impact of drivers’ compliance and level of service. Then, the paper proposes an approach to the modeling of pedestrians and vehicles interactions in the area of a zebra crossing, either signalized or not. The model is subject of further improvement and validation with the outcomes of the empirical studies.

[1]  Iris Ruther Winogrond,et al.  A Comparison of Interpersonal Distancing Behavior in Young and Elderly Adults , 1981, International journal of aging & human development.

[2]  Giuseppe Vizzari,et al.  An Integrated Model for the Simulation of Pedestrian Crossings , 2014, ACRI.

[3]  J. Mindell,et al.  Most older pedestrians are unable to cross the road in time: a cross-sectional study. , 2012, Age and ageing.

[4]  Dirk Helbing,et al.  General Lane-Changing Model MOBIL for Car-Following Models , 2007 .

[5]  Helbing,et al.  Social force model for pedestrian dynamics. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[6]  Michael Schreckenberg,et al.  A cellular automaton model for freeway traffic , 1992 .

[7]  鹿田 成則,et al.  講座 HIGHWAY CAPACITY MANUAL 2000(3)2車線道路と多車線道路 , 2002 .

[8]  Kai Nagel,et al.  Still Flowing: Approaches to Traffic Flow and Traffic Jam Modeling , 2003, Oper. Res..

[9]  M. Hamed Analysis of pedestrians’ behavior at pedestrian crossings , 2001 .

[10]  Margaret J. Weber,et al.  Influence of Sensory Abilities on the Interpersonal Distance of the Elderly , 2003 .

[11]  Emilio Frazzoli,et al.  Revisiting Street Intersections Using Slot-Based Systems , 2016, PloS one.

[12]  J. Burgess The social biology of human populations: Spontaneous group formation conforms to evolutionary predictions of adaptive aggregation patterns , 1989 .

[13]  Victoria Gitelman,et al.  An evaluation of crosswalk warning systems: effects on pedestrian and vehicle behaviour , 2002 .

[14]  Dirk Helbing,et al.  Analytical investigation of oscillations in intersecting flows of pedestrian and vehicle traffic. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[15]  Ulrich Weidmann,et al.  Transporttechnik der Fussgänger , 1992 .

[16]  Hideki Nakamura,et al.  A Modified Social Force Model for Pedestrian Behavior Simulation at Signalized Crosswalks , 2014 .

[17]  P. G. Gipps,et al.  A behavioural car-following model for computer simulation , 1981 .

[18]  P. Wagner,et al.  Metastable states in a microscopic model of traffic flow , 1997 .

[19]  Arnaud Banos,et al.  Simulating Pedestrian-Vehicle Interaction in an Urban Network Using Cellular Automata and Multi-Agent Models , 2007 .

[20]  A. Schadschneider,et al.  Simulation of pedestrian dynamics using a two dimensional cellular automaton , 2001 .

[21]  W Reilly,et al.  HIGHWAY CAPACITY MANUAL 2000 , 1997 .

[22]  Stefania Bandini,et al.  Towards Modelling Pedestrian-Vehicle Interactions: Empirical Study on Urban Unsignalized Intersection , 2016, ArXiv.

[23]  Heather J. Ruskin,et al.  Modelling Traffic Flow At Multi-Lane Urban Roundabouts , 2006 .