A Constructive Intelligent Transportation System for Urban Traffic Network in Developing Countries via GPS Data from Multiple Transportation Modes

Pham, Duc-Thinh; Hoang, Bao An; Thanh, Son Nguyen; Nguyen, Ha Anh; Dương, Vũ

doi:10.1109/itsc.2015.281

Cited by 8 publications

(4 citation statements)

References 4 publications

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“…In [17], de Almeida et al propose a system that monitors and disseminates SN Computer Science traffic conditions using a decentralized infrastructure (DOCTraMS) with applied traffic data from São Paulo, Brazil. In [18], Pham et al propose a framework for collecting and processing traffic data from various types of sources; and adapting several algorithms in transportation research to regulate the traffic and inform users via a control center in Ho Chi Minh City, Vietnam. These systems are, however, limited in coverage and, more importantly, they are not matured enough in developing countries.…”

Section: Related Workmentioning

confidence: 99%

Mining Urban Traffic Condition from Crowd-Sourced Data

et al. 2020

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Traffic congestion is an inherent and hard issue to be tackled in huge urban areas, particularly in developing countries where transportation infrastructures have not been grown well to fulfill speedy developing request demands. This paper proposes novel solutions to these issues by devising mobile crowd-sourcing based approaches to traffic estimation. A framework for effective collecting, integrating and analyzing traffic-related data shared by mobile crowds has been devised. Besides, essential issues on predicting traffic conditions at streets where real-time data is missed are also resolved by applying data mining techniques to historical data. A prototype system has been developed to validate the proposed solutions. The experimental results show the feasibility and the effectiveness of the proposed methods revealing that they are ready to be applied in the practice.

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Section: Related Workmentioning

confidence: 99%

Mining Urban Traffic Condition from Crowd-Sourced Data

et al. 2020

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“…Cities including New York and San Francisco have analysed and applied data generated from GPS-enabled taxis (King & Saldarriaga, 2017;Miao et al, 2016). Pham, Hoang, Thanh, Nguyen, and Duong (2015) look specifically at gathering data from GPS-enabled modes in developing cities, like Ho Chi Minh City, that feature heavy 'non lane-based traffic'. The study evaluates the potential for collecting and processing data from GPS on taxis, cars, motorcycles, and buses, as well as individuals using a mobile phone application, and identifies challenges such as battery loss on collection devices (Pham et al, 2015).…”

Section: Global Positioning Systems (Gps)mentioning

confidence: 99%

“…Pham, Hoang, Thanh, Nguyen, and Duong (2015) look specifically at gathering data from GPS-enabled modes in developing cities, like Ho Chi Minh City, that feature heavy 'non lane-based traffic'. The study evaluates the potential for collecting and processing data from GPS on taxis, cars, motorcycles, and buses, as well as individuals using a mobile phone application, and identifies challenges such as battery loss on collection devices (Pham et al, 2015). van Zyl and Giannini (2013) discuss the use of GPS tracking of minibus taxis in South Africa and find that the ability to monitor route adherence patterns and other operations information can not only improve safety, but can enable transport authorities to improve planning capabilities, especially related to integration between minibus taxis and other modes (i.e.…”

Section: Global Positioning Systems (Gps)mentioning

confidence: 99%

Using data and technology to integrate mobility modes in low-income cities

Yanocha

Mason

Hagen³

2020

Transport Reviews

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The utilisation of data and technology in transportation has given rise to new forms of flexible, on-demand mobility and urban freight services. Such advances have also enabled the integration of multiple transportation modes and facilitated more predictable, environmentally-friendly, high-volume trips. While many of these technologies are now commonplace in higher income cities, they are less prevalent in lower income cities. This review identifies a) recent advances in technology and data that can facilitate multimodal urban travel, and b) the existing and potential application of these advances in low-and lower middleincome (LIC and LMIC) cities, particularly in Sub-Saharan Africa and Asia. This review examines peer-reviewed and grey literature and uses a multi-method approach with expert interviews. The review identifies open transportation data and data standards, global positioning systems, cashless fare payment, and blockchain as having high potential to facilitate integrated mobility in lower income contexts, and considers potential barriers to adopting and risks of utilising these technologies in LICs and LMICs. The review finds that, enabled by technology and data advances, LICs and LMICs could leapfrog the high car use and inefficient urban freight systems typical of higher income cities to more integrated, efficient, multimodal transport systems.

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“…Optimal routing analysis, as one of the important spatial analyses in geographic information science (GIS), has been widely applied in travel route planning (Chen, Lam, Sumalee, & Li, 2012;Rice, 2013), vehicle navigation (Uppoor, Manohara Pai, & Mouzna, 2009;Won, Kim, Baek, & Lee, 2009), and intelligent transportation systems (Szeto, 2014;Pham, Hoang, Thanh, Nguyen, & Duong, 2015). Given that virtual globes enable the combination of heterogeneous datasets, some research depends on virtual globes to realize optimal routing.…”

mentioning

confidence: 99%

A topographically preserved road‐network tile model and optimal routing method for virtual globes

Dong

Jin

Liu

2019

Transactions in GIS

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Virtual globes enable the combination of heterogeneous datasets for optimal routing analyses in transportation, environmental ecology, and construction engineering. In this study, considering the advantages of the hierarchical tiling structure and topography of virtual globes, we propose a tile‐based optimal routing method for large‐scale road networks in a virtual globe. This method designs a topographically preserved road‐network tile model by partitioning roads into tiles and constructs the road‐network pyramid from the bottom to the top. During construction, a TileArc is calculated and flagged as the shortest path in a tile. Based on the built road‐network pyramid carrying hierarchical TileArcs, a multi‐level and flexible shortest path query can be executed efficiently. The proposed method is implemented with large road networks with different road grades in a virtual globe. Experimental results verify its validity, efficiency, and exactness. Moreover, the length of the shortest path with surface distance is approximately 1.3 times longer than that with Euclidean distance.

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A Constructive Intelligent Transportation System for Urban Traffic Network in Developing Countries via GPS Data from Multiple Transportation Modes

Cited by 8 publications

References 4 publications

Mining Urban Traffic Condition from Crowd-Sourced Data

Mining Urban Traffic Condition from Crowd-Sourced Data

Using data and technology to integrate mobility modes in low-income cities

A topographically preserved road‐network tile model and optimal routing method for virtual globes

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