Dynamic Data Driven Application Simulation of Surface Transportation Systems

Fujimoto, Richard M.; Guensler, Randall; Hunter, Michael; Kim, Hyeon-Kook; Lee, J.; Leonard, John D.; Palekar, Mahesh; Schwan, Karsten; Seshasayee, Balasubramanian

doi:10.1007/11758532_57

Cited by 19 publications

(8 citation statements)

References 2 publications

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“…The data-driven based dynamic simulation approaches have been studied using real-time traffic data to estimate roadway traffic volumes across various time intervals [22]. A dynamic data-driven approach is applied to the surface transportation system [23]. Benefiting from increasing data volumes and computing power, the data-driven approach has been widely applied on transportation systems.…”

Section: Data-driven Approachesmentioning

confidence: 99%

Data-Driven Prediction System of Dynamic People-Flow in Large Urban Network Using Cellular Probe Data

Chen

Wan

Ding

et al. 2019

Journal of Advanced Transportation

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Cellular probe data, which is collected by cellular network operators, has emerged as a critical data source for human-trace inference in large-scale urban areas. However, because cellular probe data of individual mobile phone users is temporally and spatially sparse (unlike GPS data), few studies predicted people-flow using cellular probe data in real-time. In addition, it is hard to validate the prediction method at a large scale. This paper proposed a data-driven method for dynamic people-flow prediction, which contains four models. The first model is a cellular probe data preprocessing module, which removes the inaccurate and duplicated records of cellular data. The second module is a grid-based data transformation and data integration module, which is proposed to integrate multiple data sources, including transportation network data, point-of-interest data, and people movement inferred from real-time cellular probe data. The third module is a trip-chain based human-daily-trajectory generation module, which provides the base dataset for data-driven model validation. The fourth module is for dynamic people-flow prediction, which is developed based on an online inferring machine-learning model (random forest). The feasibility of dynamic people-flow prediction using real-time cellular probe data is investigated. The experimental result shows that the proposed people-flow prediction system could provide prediction precision of 76.8% and 70% for outbound and inbound people, respectively. This is much higher than the single-feature model, which provides prediction precision around 50%.

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Section: Data-driven Approachesmentioning

confidence: 99%

Data-Driven Prediction System of Dynamic People-Flow in Large Urban Network Using Cellular Probe Data

Chen

Wan

Ding

et al. 2019

Journal of Advanced Transportation

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“…This also involves computationally expensive simulation-based optimization, requiring the execution of many what-if simulations in a high-performance computing environment. This is distinctively different from existing work on simulation-based intelligent transportation systems (Fujimoto et al 2006), for example, which aims at performing a distributed traffic simulation. Furthermore, our simulation will represent the traffic of an entire city with a very high resolution.…”

Section: Summary and Future Workmentioning

confidence: 86%

Symbiotic simulation for future electro-mobility transportation systems

Aydt¹,

Lees

Knoll

2012

Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC)

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Electro-mobility is widely regarded as the future of transportation systems. The shift from fossil fuel-based engines to electro-mobility will pose new challenges to the operations of future transportation systems. Our vision of a smart transportation system for the future entails a collaborative communication and simulation infrastructure that can help to mitigate common traffic-related problems as well as problems that are specific to electric vehicles. At the core of this smart transportation system would be a symbiotic simulation system which incorporates information provided by the various traffic participants into city-scale traffic simulations. We describe the symbiotic simulation system and highlight the research challenges that need to be addressed in order to realize such a system. This includes a server-based city-scale simulation which would forecast general traffic patterns and conditions in the near-future. The outcome of these simulations can be used by server-based smart routing services and/or in-car navigation systems.

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“…The complexities associated with managing transportation systems will predominantly reside in the interaction between sensing systems, data acquisition systems, demand models, communications, and traffic simulations [4]. Because of more sensors having installed on the roadway and its continuity to proliferate, traffic-related data has grown exponentially.…”

Section: Traffic Managementmentioning

confidence: 99%

Service-oriented dynamic data driven application systems to potential field method vehicle navigation

Lin

Chao

2011

Proceedings of the 2011 ACM Symposium on Applied Computing

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With advance in distributed system technology, data has become ubiquitous and its dynamics has increased. Therefore, in this paper we proposed a new framework to integrate dynamic data driven application systems (DDDAS) with service-oriented architecture (SOA) and web services technology to tackle dynamic data issue in a real-time environment. An efficient and effective service-oriented dynamic data-driven framework algorithm is designed to support a prediction strategy for vehicle navigation. The simulation results show that our algorithm outperforms the Dijkstra algorithm by improving 24.43% in average vehicle traveling time.

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Dynamic Data Driven Application Simulation of Surface Transportation Systems

Cited by 19 publications

References 2 publications

Data-Driven Prediction System of Dynamic People-Flow in Large Urban Network Using Cellular Probe Data

Data-Driven Prediction System of Dynamic People-Flow in Large Urban Network Using Cellular Probe Data

Symbiotic simulation for future electro-mobility transportation systems

Service-oriented dynamic data driven application systems to potential field method vehicle navigation

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