Wardrop Equilibrium Can Be Boundedly Rational: A New Behavioral Theory of Route Choice

As one of the most fundamental concepts in transportation science, Wardrop equilibrium (WE) has always had a relatively weak behavioral underpinning. To strengthen this foundation, one must reckon with bounded rationality in human decision-making processes, such as the lack of accurate information, limited computing power, and sub-optimal choices. This retreat from behavioral perfectionism in the literature, however, was typically accompanied by a conceptual modification of WE. Here we show that giving up perfect rationality need not force a departure from WE. On the contrary, WE can be reached with global stability in a routing game played by boundedly rational travelers. We achieve this result by developing a day-to-day (DTD) dynamical model that mimics how travelers gradually adjust their route valuations, hence choice probabilities, based on past experiences. Our model, called cumulative logit (CULO), resembles the classical DTD models but makes a crucial change: whereas the classical models assume routes are valued based on the cost averaged over historical data, ours values the routes based on the cost accumulated. To describe route choice behaviors, the CULO model only uses two parameters, one accounting for the rate at which the future route cost is discounted in the valuation relative to the past ones and the other describing the sensitivity of route choice probabilities to valuation differences. We prove that the CULO model always converges to WE, regardless of the initial point, as long as the behavioral parameters satisfy certain mild conditions. Our theory thus upholds WE's role as a benchmark in transportation systems analysis. It also resolves the theoretical challenge posed by Harsanyi's instability problem by explaining why equally good routes at WE are selected with different probabilities

A Study of Driver’s Route Choice Behavior Based on Evolutionary Game Theory

This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers’ route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver’s route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver’s route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent

Behaviour of Humans and Behaviour of Models in Dynamic Space

This paper addresses new trends in quantitative geography research. Modern social science research – including economic and social geography – has in the past decades shown an increasing interest in micro-oriented behaviour of actors. This is inter alia clearly reflected in spatial interaction models (SIMs), where discrete choice approaches have assumed a powerful position. This paper aims to provide in particular a concise review of micro-based research, with the aim to review the potential – but also the caveats – of micro-models to map out human behaviour. In particular, attention will be devoted to interactive learning principles that shape individual decisions. Lessons from cognitive sciences will be put forward and illustrated, amongst others on the basis of computational neural networks or spatial econometric approaches. The methodology of deductive reasoning under conditions of large data bases in studying human mobility will be questioned as well. In this context more extensive attention is given to ceteris paribus conditions and evolutionary thinkin

Life is an Adventure! An agent-based reconciliation of narrative and scientific worldviews\ud

The scientific worldview is based on laws, which are supposed to be certain, objective, and independent of time and context. The narrative worldview found in literature, myth and religion, is based on stories, which relate the events experienced by a subject in a particular context with an uncertain outcome. This paper argues that the concept of “agent”, supported by the theories of evolution, cybernetics and complex adaptive systems, allows us to reconcile scientific and narrative perspectives. An agent follows a course of action through its environment with the aim of maximizing its fitness. Navigation along that course combines the strategies of regulation, exploitation and exploration, but needs to cope with often-unforeseen diversions. These can be positive (affordances, opportunities), negative (disturbances, dangers) or neutral (surprises). The resulting sequence of encounters and actions can be conceptualized as an adventure. Thus, the agent appears to play the role of the hero in a tale of challenge and mystery that is very similar to the "monomyth", the basic storyline that underlies all myths and fairy tales according to Campbell [1949]. This narrative dynamics is driven forward in particular by the alternation between prospect (the ability to foresee diversions) and mystery (the possibility of achieving an as yet absent prospect), two aspects of the environment that are particularly attractive to agents. This dynamics generalizes the scientific notion of a deterministic trajectory by introducing a variable “horizon of knowability”: the agent is never fully certain of its further course, but can anticipate depending on its degree of prospect