A review of Intelligent Transportation Systems from a communications technology perspective

Maimaris, Athanasios; Papageorgiou, George

doi:10.1109/itsc.2016.7795531

Cited by 44 publications

(16 citation statements)

References 38 publications

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“…The sustainable development of smart cities requires reliable and efficient transportation systems [ 10 ]. Internet of Things (IoT) can be applied with the existing infrastructure and service networks for the design of transportation systems, such as software-defined networks and communication technologies [ 11 , 12 , 13 ]. IoT-based intelligent transportation systems (IoT-ITSs) can be classified into four main fields: Advanced traveler information system (ATIS), advanced public transportation system (APTS), advanced traffic management system (ATMS) and emergency management system (EMS) [ 13 ].…”

Section: Related Workmentioning

confidence: 99%

Towards Attention-Based Convolutional Long Short-Term Memory for Travel Time Prediction of Bus Journeys

Shen

2020

Sensors

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Travel time prediction is critical for advanced traveler information systems (ATISs), which provides valuable information for enhancing the efficiency and effectiveness of the urban transportation systems. However, in the area of bus trips, existing studies have focused on directly using the structured data to predict travel time for a single bus trip. For state-of-the-art public transportation information systems, a bus journey generally has multiple bus trips. Additionally, due to the lack of study on data fusion, it is even inadequate for the development of underlying intelligent transportation systems. In this paper, we propose a novel framework for a hybrid data-driven travel time prediction model for bus journeys based on open data. We explore a convolutional long short-term memory (ConvLSTM) model with a self-attention mechanism that accurately predicts the running time of each segment of the trips and the waiting time at each station. The model is more robust to capture long-range dependence in time series data as well.

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Section: Related Workmentioning

confidence: 99%

Towards Attention-Based Convolutional Long Short-Term Memory for Travel Time Prediction of Bus Journeys

Shen

2020

Sensors

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“…Even though Intelligent Transportation Systems (ITS) is widely used for enhancing vehicular traffic, little has been done for promoting pedestrian flows. The authors, having wide experience with ITS applications [8]- [13], see the enormous potential that exists for what they call Intelligent Pedestrian Mobility Systems (IPMS) [14].…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluating Attitudes on the Quality of Service of Pedestrian Networks

Papageorgiou¹,

Maimaris²,

Efstathiadou³

et al. 2017

WIT Transactions on the Built Environment

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The aim of our research is to study opinions of people upon the pedestrian conditions in urban spaces. The goal is to evaluate, based on the perception of citizens, the existence of certain walkability factors that contribute to the quality of service of the pedestrian environment. Walkability factors are related to mobility, connectivity, comfort, safety and convenience. As a result, a pedestrian satisfaction index could be derived, which might reveal the citizens' quality of life and the need for developing comfortable, healthy and safe pedestrian networks. Results show the willingness of people to walk more, but also the obstacles that prevent them from doing so. Our study is important for the better understanding of walkability issues in urban spaces, especially for developing technology solutions and strategies for local governments in the quest of realizing the vision of the smart city.

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“…The intelligent transport systems (ITS) are the implementation of technologies on transport domain aiming to improve safety, efficiencies, mobility, and productivities [1]. With the development of mobile communication technologies, novel applications in ITS have been provided, including transportation information services, electronic payment methods, location and navigation, on‐board emergency management and etc.…”

Section: Introductionmentioning

confidence: 99%