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Erschienen in:
Congestion Management in Motorways and Urban Networks Through a Bargaining-Game-Based Coordination Mechanism Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

A Psycho-Social Agent-Based Model of Driver Behavior Dynamics

verfasst von : Theodore Tsekeris, Ioannis Katerelos

Erschienen in: Game Theoretic Analysis of Congestion, Safety and Security

Verlag: Springer International Publishing

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Abstract

This paper suggests a psycho-social agent-based model, referred to as Holistic-Emergent Social Interaction-Oriented Dynamics (HESIOD) model, to simulate the drivers’ behavior dynamics under various types of interaction among vehicles. The HESIOD model allows representing the heterogeneity and dynamical processes involved in such control dimensions as risk assessment and time responsiveness of driving behavior (controlled dimension). It is shown that highly differentiated states may arise, such as fixed point, periodicity and transient chaos. The dynamical state is found to be mostly affected by the degree to which the control dimensions of neighboring vehicle drivers depart from each other, and the topology of interaction among drivers. In contrast with the aggregate statistical-probabilistic models, this agent-based model can offer valuable insights into the role of both cognitive processes and interactions of drivers on their actual driving behavior. The findings may have useful implications for improving the level of service, safety and security in roads.

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Vorheriges Kapitel Solving a Dynamic User-Optimal Route Guidance Problem Based on Joint Strategy Fictitious Play
Nächstes Kapitel Game-Theoretic Context and Interpretation of Kerner’s Three-Phase Traffic Theory
Fußnoten
1
Particularly, headlight flashing can be very irritating, at this point! A very antagonistic view of my fellow co-driver. This kind of behavior is strongly associated with cultural parameters, mainly in reference to the driving style usually met in southern European countries.
 
2
The Bound of Confidence (BC) expresses the bound within which each agent takes other agents’ opinions (driving behaviors) into account [10]. For instance, if I get surpassed by a car having the triple of my speed and I am already driving to the speed limit (into the city), then this behavior (driving at such a high speed) can be outside my bound of confidence; so, I am not at all influenced (this behavior is far too riskier than I can bear) and therefore, it does not influence me: I will pass the challenge.. As one can easily understand, if a driver has a very wide bound of confidence, then s/he is susceptible to be influenced by almost any driving behavior no matter how risky it is.
 
3
K can also be of zero value. This means that a driver with K = 0, insists in retaining his/hers speed no matter what the other drivers in proximity are doing.
 
4
A cognitive procedure named Focus On Max Change (FOMC, [12]). Although this procedure may seem arbitrary, since it is not backed up by concrete data, the mechanism tends to imitate satisfyingly real behaviors when one is oriented more to assess dynamically a given situation than to apprehend it statically. In the real world, the FOMC can be easily depicted: if someone is receiving two stimuli, the one which differs maximally from his/her own position (state) will attract his/her attention in priority. Nevertheless, the above mentioned mechanism is subjected to ongoing research and testing; so, a better refinement can be expected in future projects.
 
5
These simulations use homogenous agents: they all share a common K and Ψ.
 
6
Since an indicative example of three vehicles (very small number of active agents) is employed here, the notion of cellular automata topology can be translated ad hoc to a directed graph (3 node-incomplete graph) compared to an undirected graph (3 node–complete graph).
 
7
In a rather theoretical view, in real life, this case can look like a race between supercars in Daytona or, even more vividly, the race of “24 h of Isle of Man”: the drivers maintain extreme speeds while very close to one another.
 
8
Such as “spontaneous races”, “drifting”, “spinning”, “chicken-game” etc.
 
9
Police controls/blocks, “car chasing”, etc. During the recent years, the common procedure adopted by police officers confronting suspects of unlawful actions when they try to get away via driving through the road network, is to stay behind and wait either for the suspect to run out of fuel or for the suspect to enter a controlled environment minimizing possible collateral damage. Evidently, a certain tactic of “pushing” the suspect to a kind of “road race/car chase” (and, therefore “negotiating” with him/her either his/her driving skills or his/her vehicle’s potential regarding acceleration and handling), could challenge the suspect and augment dramatically the probability of harming him/herself or others.
 
10
This holds without taking into account possible enervation of other drivers and, consecutively, the adoption of an aggressive (and dangerous if escalades) stance against the trespasser (him/her)!
 
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Metadaten
Titel
A Psycho-Social Agent-Based Model of Driver Behavior Dynamics
verfasst von
Theodore Tsekeris
Ioannis Katerelos
Copyright-Jahr
2015
Buch
Game Theoretic Analysis of Congestion, Safety and Security

Print ISBN: 978-3-319-11673-0

Electronic ISBN: 978-3-319-11674-7

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-11674-7_4

Neuer Inhalt

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