Abstract
Based on the price-quantity adjustment behaviour principle of the non-Walrasian equilibrium theory, this paper adopted a new QUE (quantity adjustment user equilibrium) criterion to formulate the route comfort choice behaviour. The purpose of the present paper is to establish a proportional-switch adjustment model which aims to reflect the route adjustment behaviour interaction between the traditional UE (user equilibrium) travellers and the QUE travellers and converge to a mixed equilibrium state. It is assumed that a group of road network travellers follow the UE criteria by choosing the travel route with the purpose of minimizing their route travel time (travel cost). In addition, the other group of travellers follow the QUE criteria by selecting the route with the largest residual capacity to achieve a more comfortable travel experience. The travel route adjustment behaviour of the two group travellers generates the dynamic traffic flow evolution towards the mixed equilibrium, and the route adjusting flow is proportional to the difference of traveller decision-making variable among the alternative routes. Simple illustrative examples are used to evaluate the performance of the proposed model, and the uniqueness and stability of the solution are demonstrated by applying the variational inequality and Lyapunov stability theorem.
Highlights
DTA model has been a focus research area for a long time with a growing influence on the traffic control and guidance promoted by the development of ITS emerging, leading to a greater interest in understanding the travel choice decision behaviour and the adjustment behavioural mechanisms [1,2,3,4]
Route choice behaviour is the basis of the traffic flow, and researchers have carried out a number of studies for dynamic traffic flow evolution problems to deepen the understanding of travellers’ route choice behaviour decision-making mechanism [5,6,7,8]. e dynamic models are classified into five categories in the early researches: the simplex gravity flow dynamics, proportionalswitch adjustment process, network tatonnement process, projected dynamical system, and evolutionary traffic flow dynamics. e difference between the five types of methods lies in the convergence speed of the established evolutionary model and the stability in equilibrium state [9,10,11,12]
Guo et al [13] established a link-based discrete dynamic system model and depicted the rational adjustment process of network traffic flow from disequilibrium to an equilibrium state, which formulated more general behaviour compared with the five categories of dynamical system models
Summary
DTA (dynamic traffic assignment) model has been a focus research area for a long time with a growing influence on the traffic control and guidance promoted by the development of ITS (intelligence transportation system) emerging, leading to a greater interest in understanding the travel choice decision behaviour and the adjustment behavioural mechanisms [1,2,3,4]. Addition, this study expands the decision influencing factors of travellers’ route choice, which reflects travellers’ individual characteristics more flexible, and significantly deepens the understanding of network traffic flow and improves the level of urban traffic management
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