Fatal crush conditions occur in crowds with tragic frequency. Event organizers and architects are often criticised for failing to consider the causes and implications of crush conditions, but the reality is that the prediction of such conditions o ers signi cant challenges. This thesis investigates the use of crush metrics in simulation environments, which can be used to help quantify the danger of crush conditions forming during real life evacuations. An investigation is carried out in the use of computer models for the purpose of simulating building evacuation. From this review we identify the most suitable methodologies for modelling crowd behaviour, and we detail the speci c areas of functionality which must be in place before modellers can incorporate crush analysis into an evacuation simulation. We nd that full treatment of physical force within crowd simulations is precise but computationally expensive; the more common method, human interpretation of simulation output, is computationally \cheap" but subjective and timeconsuming. A technique which admits a low computational cost alternative to the explicit modelling of physical force, yet still o ers a quantitative metric for the level of force present during an in silico evacuation is proposed. This technique and the precise manner in which we apply it to the problem of crush detection is shown and we present the results of initial experiments. To further test the ability of our technique to identify dangerous evacuation conditions, we recreate a well-known historical evacuation. Results of these experiments show that we do o er an e ective and e cient route towards the low cost automatic detection of crush, and an alternative approach to traditional methods.

The aim of this thesis is to extend the social identity model of crowd behaviour (Reicher, 1984, 1987, 1996) by exploring the experience of collective participation, with an emphasis upon quality of within-crowd social relations (‘relatedness') and collective emotionality. A multi-method research strategy is employed to study these topics at a variety of crowd events. Studies 1 and 2 use ethnography and retrospective interviews at a student protest and public screenings of football matches to generate hypotheses for subsequent testing. Study 3 then tests these hypotheses by means of questionnaire data collected during Study 2. Using an experimental ‘visualisation' paradigm, Study 4 demonstrates the role of shared identity (and not simply self-categorization) in generating relatedness. Studies 5 and 6 present evidence that groups of high relatedness participants experience identity-relevant stimuli as more emotionally intense than low relatedness groups. Study 7 concludes the empirical work by using questionnaire data collected at political protests to test a model of collective experience based upon the findings of the previous studies. The thesis argues that a perception of shared identity with co-present others can positively transform social relations towards relatedness (connectedness, validation and recognition). Relatedness may then be experienced emotionally, and facilitate the realisation of group goals which may also have emotional consequences. Strength of social identity is also noted as an antecedent to group-based emotion. In this way the analysis offers three ways in which social identity may lead to emotionality of collective experience, contradicting ‘classic' crowd psychology in which crowd emotion was rooted in a loss of identity. Preliminary evidence is also presented suggesting that the experience of collective participation may have a role to play in determining future social identification and participation in co-action.