Pedestrian fuzzy risk exposure indicator

Abstract: We all find ourselves in the situation of a pedestrian at least for a short period of time. The loss of millions of lives and injury of others, is not enough sufficient for urban architects, decisions makers and designers to radically reconsider the design of the urban network, and not only improve the use of pathways and priorities rules, but to improve the walking environment for pedestrians while considering walking as an essential and necessary part of the overall transportation system. Without protection, pedestrians are particularly vulnerable network road users. The reduction or elimination of risks to pedestrians is an important and achievable goal. In this paper we present an indicator of pedestrians’ accidents risk which can evaluate the accident rate on a chosen network road.

[1]  Christophe F. Wakim,et al.  A Markovian model of pedestrian behavior , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[2]  Harsh J. Amin,et al.  Modelling the Crossing Behavior of Pedestrian at Uncontrolled Intersection in Case of Mixed Traffic Using Adaptive Neuro Fuzzy Inference System , 2015 .

[3]  Jesus Savage,et al.  Local Autonomous Robot Navigation Using Potential Fields , 2008 .

[4]  Hirozumi Yamaguchi,et al.  Urban pedestrian mobility for mobile wireless network simulation , 2009, Ad Hoc Networks.

[5]  Tal Oron-Gilad,et al.  Are child-pedestrians able to identify hazardous traffic situations? Measuring their abilities in a virtual reality environment , 2015 .

[6]  Michael Hanss,et al.  Applied Fuzzy Arithmetic , 2005 .

[7]  Attila Bilgic,et al.  Pedestrian Mobility Modelling for the Simulation of Heterogeneous Wireless Infrastructures , 2010, 2010 IEEE International Conference on Communications.

[8]  Ning Ding,et al.  Simulation of pedestrian flow based on cellular automata: A case of pedestrian crossing street at section in China , 2013 .

[9]  Vicente Milanés Montero,et al.  Autonomous Pedestrian Collision Avoidance Using a Fuzzy Steering Controller , 2011, IEEE Transactions on Intelligent Transportation Systems.

[10]  Dipika Gupta.  SIMULATION OF PEDESTRIAN AT INTERSECTION IN URBAN CONGESTED AREA , 2014 .

[11]  A. Boulmakoul,et al.  Fuzzy Ant Colony Paradigm for Virtual Pedestrian Simulation , 2011 .

[12]  Johan Olstam,et al.  Analytical Traffic Models for Roundabouts with Pedestrian Crossings , 2011 .

[13]  Eleonora Papadimitriou.  Theory and models of pedestrian crossing behaviour along urban trips , 2012 .

[14]  George Yannis,et al.  Measuring accident risk exposure for pedestrians in different micro-environments. , 2007, Accident; analysis and prevention.