Multi-agent decision-support system for an urban transportation network

Fayech, B.; Maouche, S.; Hammadi, Slim; Borne, Pierre

doi:10.1109/wac.2002.1049416

Cited by 10 publications

(9 citation statements)

References 4 publications

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“…6 Hierarchical architectures use some kind of organizational structure where a hierarchy of authority exists. 2,7,[12][13][14][15] Agents at lower levels send information to agents at upper levels, which make decisions to coordinate and synchronize activities and decisions of lower-level agents. 2,7,[12][13][14][15] Agents at lower levels send information to agents at upper levels, which make decisions to coordinate and synchronize activities and decisions of lower-level agents.…”

Section: Distributed Control Of Disturbed Public Bus Transportation Smentioning

confidence: 99%

“…5 Such architectures were suggested in related works. Fayech et al 14,15 developed an architecture that relies on bus and stop agents to monitor vehicle and station data and status, incident and zonepert agents to detect and analyze disturbances, and a top hierarchy zonereg agent to determine control decisions. For example, Belmonte et al 13 suggested a hierarchical architecture that includes three types of agents, ie, Data agents collect data, and Action Implementation agents execute control decisions made by Line Management agents.…”

Section: Distributed Control Of Disturbed Public Bus Transportation Smentioning

confidence: 99%

“…10,15,21 Only a few authors 8,11 have explicitly taken into account complementary information about disturbances that would explain their causes, describe their symptoms, or clarify their context of occurrence. Authors usually consider only the earliness and delays of buses with respect to scheduled timetable.…”

Section: Disturbance Managementmentioning

confidence: 99%

“…5 Such architectures were suggested in related works. 2,7,[12][13][14][15] Agents at lower levels send information to agents at upper levels, which make decisions to coordinate and synchronize activities and decisions of lower-level agents. For example, Belmonte et al 13 suggested a hierarchical architecture that includes three types of agents, ie, Data agents collect data, and Action Implementation agents execute control decisions made by Line Management agents.…”

Section: Distributed Control Of Disturbed Public Bus Transportation Smentioning

confidence: 99%

“…Authors usually consider only the earliness and delays of buses with respect to scheduled timetable. 10,15,21 Only a few authors 8,11 have explicitly taken into account complementary information about disturbances that would explain their causes, describe their symptoms, or clarify their context of occurrence. This article extends the work of Darmoul and Elkosantini 11 by including both time-and passenger-based symptoms, in addition to context, symptoms, and consequences, which is rarely done in literature.…”

Section: Disturbance Managementmentioning

confidence: 99%

See 4 more Smart Citations

An immune multiagent system to monitor and control public bus transportation systems

Mnif

Darmoul

Elkosantini

et al. 2018

Computational Intelligence

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In public bus transportation systems, several types of disturbances, such as accidents and congestion, may affect preestablished timetables and visiting hours at stations. Disturbances result in detrimental consequences, degraded performance, and poor quality of service in terms of extended delays and waiting times, punctuality, frequency, and efficiency of shuttles. Despite numerous research on the monitoring and control of public transportation systems by means of buses, distributed monitoring and control architectures that confer intelligence and decision-making autonomy to buses to react to disturbances are still missing. This article addresses this gap by designing and developing a distributed architecture to monitor and control public transportation buses using multiagent systems. The design relies on biological immunity as a methodological framework that guides the development of knowledge models and decision-making mechanisms. Knowledge models structure knowledge about disturbances and control decisions, whereas decision-making mechanisms implement control and reaction strategies. Through experimental validation based on simulation, we show that the suggested immune multiagent distributed control architecture is not only able to maintain performance (average delay/earliness, average total time in simulated network) at acceptable levels but also to improve quality of service in terms of number of served passengers and stations by at least 15% in case of disturbances. KEYWORDS artificial immune system, biological immune system, immune memory, multiagent system, negative selection theory, public transport control system

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Section: Distributed Control Of Disturbed Public Bus Transportation Smentioning

confidence: 99%

Section: Distributed Control Of Disturbed Public Bus Transportation Smentioning

confidence: 99%

Section: Disturbance Managementmentioning

confidence: 99%

Section: Distributed Control Of Disturbed Public Bus Transportation Smentioning

confidence: 99%

Section: Disturbance Managementmentioning

confidence: 99%

See 3 more Smart Citations

An immune multiagent system to monitor and control public bus transportation systems

Mnif

Darmoul

Elkosantini

et al. 2018

Computational Intelligence

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Traffic control in transportation systems

Dridi

Mesghouni

Borne

2005

Journal of Manufacturing Technology Management

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Purpose -This paper deals with real-time control of urban traffic with an emphasis on public transportation systems. The main objective is the regulation of traffic after the occurrence of disturbances. In a few words, the problem is to find a feasible schedule for some vehicles of some lines subject to certain constraints in order to design a decision support system (DSS) that detects, analyses and resolves disturbances. Design/methodology/approach -This work is achieved in cooperation with a public transport company called SEMURVAL. It consists of developing a DSS for the future transportation network of Valenciennes (city in the north of France). As a consequence, regulators of traffic have to treat a new lot of information and it becomes necessary to assist them in order to keep up with demands and to come up to passengers' expectations and hopes. Findings -From the case study finds that the solution proposed assures that arrival times of vehicles are more regular. Originality/value -The solution proposed presents a good combination of scheduling decisions permitting the good regulation of traffic.

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Partial network reconfiguration through a dynamic vehicle scheduling approach

Fayech

Hammadi

Maouche³

IEEE International Conference on Systems, Man and Cybernetics

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Multi-agent decision-support system for an urban transportation network

Cited by 10 publications

References 4 publications

An immune multiagent system to monitor and control public bus transportation systems

An immune multiagent system to monitor and control public bus transportation systems

Traffic control in transportation systems

Partial network reconfiguration through a dynamic vehicle scheduling approach

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