DynaMIT2.0: architecture design and preliminary results on real-time data fusion for traffic prediction and crisis management

Yang Lu; Francisco Camara Pereira; Ravi Seshadri; Aidan O'Sullivan; Constantinos Antoniou; Moshe Ben-Akiva

doi:10.1109/ITSC.2015.363

DynaMIT2.0: architecture design and preliminary results on real-time data fusion for traffic prediction and crisis management

Yang Lu, Francisco Camara Pereira, Ravi Seshadri, Aidan O'Sullivan, Constantinos Antoniou, Moshe Ben-Akiva

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

The ability to monitor and predict in real-time the state of the transportation network is a valuable tool for both transportation administrators and travellers. While many solutions exist for this task, they are generally much more successful in recurrent scenarios than in non-recurrent ones. Paradoxically, it is in the latter case that such tools can make the difference. Therefore, the dynamic traffic assignment and simulation based prediction system such as DynaMIT (1) demonstrates high effectiveness in the context of sudden network disturbance or demand pattern changes. This paper presents the design, development and implementation of new components and modules of DynaMIT 2.0 which is an extension of its predecessor with recent enhancements on online calibration, context mining, scenario analyser and strategy simulation capability. Also, some preliminary results are presented using Singapore expressway to show the actual benefit of the system.

Original language	English
Title of host publication	Proceedings of the 2015 IEEE 18th International Conference on Intelligent Transportation Systems (ITSC)
Number of pages	6
Publisher	IEEE
Publication date	2015
Pages	2250-2255
ISBN (Print)	978-1-4673-6595-6
DOIs	https://doi.org/10.1109/ITSC.2015.363
Publication status	Published - 2015
Event	18th International IEEE Conference on Intelligent Transportation Systems: The Wild Frontier in Intelligent Transportation - Las Palmas, Gran Canaria, Spain Duration: 15 Sept 2015 → 18 Sept 2015 Conference number: 18 https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=30712

Conference

Conference	18th International IEEE Conference on Intelligent Transportation Systems
Number	18
Country/Territory	Spain
City	Las Palmas, Gran Canaria
Period	15/09/2015 → 18/09/2015
Internet address	https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=30712

Keywords

data handling
data mining
emergency management
road traffic
sensor fusion
traffic information systems
Transportation
architecture design
Calibration
Computational modeling
context mining
crisis management
Data models
demand pattern changes
dynamic traffic assignment
dynamic traffic simulation
DynaMIT2.0
Prediction algorithms
Predictive models
real-time data fusion
Real-time systems
scenario analyser
Sensors
Singapore expressway
strategy simulation capability
sudden network disturbance
traffic prediction
transportation administration
transportation network state monitoring
transportation network state prediction
travellers

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10.1109/ITSC.2015.363

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Lu, Y., Pereira, F. C., Seshadri, R., O'Sullivan, A., Antoniou, C., & Ben-Akiva, M. (2015). DynaMIT2.0: architecture design and preliminary results on real-time data fusion for traffic prediction and crisis management. In Proceedings of the 2015 IEEE 18th International Conference on Intelligent Transportation Systems (ITSC) (pp. 2250-2255). IEEE. https://doi.org/10.1109/ITSC.2015.363

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abstract = "The ability to monitor and predict in real-time the state of the transportation network is a valuable tool for both transportation administrators and travellers. While many solutions exist for this task, they are generally much more successful in recurrent scenarios than in non-recurrent ones. Paradoxically, it is in the latter case that such tools can make the difference. Therefore, the dynamic traffic assignment and simulation based prediction system such as DynaMIT (1) demonstrates high effectiveness in the context of sudden network disturbance or demand pattern changes. This paper presents the design, development and implementation of new components and modules of DynaMIT 2.0 which is an extension of its predecessor with recent enhancements on online calibration, context mining, scenario analyser and strategy simulation capability. Also, some preliminary results are presented using Singapore expressway to show the actual benefit of the system.",

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author = "Yang Lu and Pereira, {Francisco Camara} and Ravi Seshadri and Aidan O'Sullivan and Constantinos Antoniou and Moshe Ben-Akiva",

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doi = "10.1109/ITSC.2015.363",

language = "English",

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booktitle = "Proceedings of the 2015 IEEE 18th International Conference on Intelligent Transportation Systems (ITSC)",

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note = "18th International IEEE Conference on Intelligent Transportation Systems : The Wild Frontier in Intelligent Transportation, ITSC 2015 ; Conference date: 15-09-2015 Through 18-09-2015",

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Lu, Y, Pereira, FC, Seshadri, R, O'Sullivan, A, Antoniou, C & Ben-Akiva, M 2015, DynaMIT2.0: architecture design and preliminary results on real-time data fusion for traffic prediction and crisis management. in Proceedings of the 2015 IEEE 18th International Conference on Intelligent Transportation Systems (ITSC). IEEE, pp. 2250-2255, 18th International IEEE Conference on Intelligent Transportation Systems, Las Palmas, Gran Canaria, Spain, 15/09/2015. https://doi.org/10.1109/ITSC.2015.363

DynaMIT2.0: architecture design and preliminary results on real-time data fusion for traffic prediction and crisis management. / Lu, Yang; Pereira, Francisco Camara; Seshadri, Ravi et al.
Proceedings of the 2015 IEEE 18th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2015. p. 2250-2255.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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ER -

DynaMIT2.0: architecture design and preliminary results on real-time data fusion for traffic prediction and crisis management

Abstract

Conference

Keywords

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