A heuristic model of bounded route choice in urban areas

Abstract

a b s t r a c tThere is substantial evidence to indicate that route choice in urban areas is complex cognitive process, conducted under uncertainty and formed on partial perspectives. Yet, conventional route choice models continue make simplistic assumptions around the nature of human cognitive ability, memory and preference. In this paper, a novel framework for route choice in urban areas is introduced, aiming to more accurately reflect the uncertain, bounded nature of route choice decision making. Two main advances are introduced. The first involves the definition of a hierarchical model of space representing the relationship between urban features and human cognition, combining findings from both the extensive previous literature on spatial cognition and a large route choice dataset. The second advance involves the development of heuristic rules for route choice decisions, building upon the hierarchical model of urban space. The heuristics describe the process by which quick, 'good enough' decisions are made when individuals are faced with uncertainty. This element of the model is once more constructed and parameterised according to findings from prior research and the trends identified within a large routing dataset. The paper outlines the implementation of the framework within a real-world context, validating the results against observed behaviours. Conclusions are offered as to the extension and improvement of this approach, outlining its potential as an alternative to other route choice modelling frameworks.

Perception of urban subdivisions in pedestrian movement simulation

“…We developed an ABM of pedestrian movement in urban spaces and devised four different scenarios to incrementally assess the effect of adding region and barrier information to their corresponding route choice models: a) currently prevailing least cumulative angular change minimisation, b) regions, c) barriers, and d) regions and barriers. The region-based approach entails two planning levels where the subdivision of the urban environment is used to depict a coarse initial plan that guides more granular intra-regional decisions [22,32]. The barrier-based approach contemplates 'course-adjustments' [120] by encouraging navigation along and through rivers and parks, whilst avoiding walking along major roads and railways.…”

“…However, the effect of regions in route choice behaviour in ABM has been modelled only for simulating the behaviour of taxi drivers in London. Building on Wiener and Mallot's framework [22], Manley and colleagues [32] advanced a route choice mechanism that embodies different planning levels by representing an initial rough global plan, subsequently refined at higher granularity levels. However, no simulation model of pedestrians movement or traffic flows has accounted for the role played by barriers in shaping route formulation processes.…”

“…In this scenario, agents make use of the so-extracted regions and employ a route choice model presented by Manley and colleagues [32] and adapted for pedestrian movement [33]. Agents subdivide the urban environment in portions cognitively easy to handle, and employ them to organise knowledge about other elements (i.e.…”

“…• The exit and entry nodes are in the direction of the destination; the angle (α) formed by the current location and a candidate exit node is supposed to be α > angle(currentLocation, des-tinationNode) − 70˚and α < angle(currentLocation, destinationNode) + 70˚. Although Manley [32] employed a ±90˚constrain, we used a narrower space, determined subjectively. We claim that pedestrians may not be as willing as car drivers to take long detours.…”

“…This research direction has inevitably influenced the design of Agent-Based Models (ABMs)-a computational paradigm that allows analysing how variation in the mechanisms behind individual behaviour may generate different global patterns [30,31]-for pedestrian movement simulation. Besides few cases [32,33], landmarks', regions' and barriers' functions have not been incorporated in ABM approaches, despite the great opportunity offered by these models to portray genuine interactions between pedestrian agents and the urban environment [34]. Emphasis on street cost-related properties, as the main determinant of agents' behaviour [35][36][37], has led pedestrian ABMs to neither fully account for the complex interplay between the physical and mental layers in route choice processes [38], nor for the hierarchical organisation of the environmental knowledge [39,40].…”