An effort-based model for pedestrian route choice behaviour

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This research proposes a novel effort-based theoretical framework for the pedestrian route choice problem to discover principles that pedestrians use to select their routes. A pedestrian chooses their route by optimising certain criteria, such as distance, time, and effort. Several possible criteria that could be used to predict the route choices of a pedestrian are re-assessed. In most cases, the common criteria of a pedestrian route choice are route length and travel time. Effort is proposed as an additional criterion, which indicates metabolic energy expenditure. The basic principle and a methodology are proposed for route choice based on the least effort that a pedestrian may consume during travel between destinations. The followed deterministic approach assumes that the perceived utility of a route is deterministic and that pedestrians will only choose the route that features minimum average cost. A mathematical formulation for solving the pedestrian route choice problem utilising the concept of physical effort is introduced. We compare our effort-based model against time and distance based models and validate against the Brisbane dataset. We demonstrate that our method has higher performance efficiency than the models that exist in the state-of-the-art and thereby the model justifies optimal pedestrian behaviour when choosing a route in a congested environment. Our discussion concludes with an overview of how our approach could be used by rail service providers to optimise operations and improve customer experience. It is contended that the entire behaviour of an individual is subject to effort minimization. Hence, the pedestrian route choice problem is formulated as a constrained non-linear optimization problem whose objective function is the effort consumed while moving from current position to destination over the route. This doctoral research is a part of research project entitled “Integrated Passenger Behaviour, Train Operations Diagnostics, and Vehicle Condition Monitoring System”, which aims to consolidate foundation technology for the sensing and perception functions of a system that can monitor passenger behaviour and operational characteristics of passenger trains as they arrive at crowded stations using low-cost multi-sensor network. The Brisbane Central Rail Train Station is selected for a case study for validation of the developed model.
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