db_connect: Could not connect to paper db at "wotug@dragon.kent.ac.uk"<br>
db_connect: Could not connect to paper db at "wotug@dragon.kent.ac.uk"<br>

%T PEDFLOW \- A System for Modelling Pedestrian Movement using occam
db_connect: Could not connect to paper db at "wotug@dragon.kent.ac.uk"<br>
%A  Jon Kerridge,  N. McNair
db_connect: Could not connect to paper db at "wotug@dragon.kent.ac.uk"<br>
%E  Barry M. Cook
%B Proceedings of WoTUG\-22: Architectures, Languages and Techniques for Concurrent Systems
%X Road traffic modelling and simulation is currently well
   provided with a variety of packages dealing with the minute
   detail of road layouts from single isolated junction models
   to complete network simulations. There has also been much
   work in developing assignment models to optimise traffic
   signal sequences. The same is not true in the pedestrian
   modelling arena. With the exception of models dealing with
   railway and airport concourses and models of pedestrian
   movements around sports stadia there is very little support
   for the planner or designer of the pedestrian urban
   environment. The system discussed in this paper provides
   some insights as to the reasons for this and describes a
   highly parallel microscopic model called PEDFLOW (PEDestrian
   FLOW) which attempts to remedy the situation. The model
   operates on a grid size that is equivalent to the space
   occupied by a person at rest. The major difference between
   vehicular and pedestrian movement is that the former really
   has only one degree of freedom, forwards, whereas a
   pedestrian has unlimited two\-dimensional degrees of
   freedom. Vehicular travel is governed by a large number of
   laws and regulations that make it much easier to model.
   Within the pedestrian urban environment there are very few
   laws and regulations and those that do apply are related to
   interactions with vehicles. The design of PEDFLOW is
   discussed and it is shown how the complex behavioural rules
   governing pedestrian movement are captured. The parallel
   architecture underlying the model is described and it shows
   how the maximum possible parallelism is achieved among all
   the moving pedestrians at any one time. The performance of
   the model is then presented and uses to which the model is
   being put are then briefly presented.