Barriers and risks of Mobility-as-a-Service (MaaS) adoption in cities: A systematic review of the literature
There is a growing demand, across the globe, for smart mobility solutions to reduce negative
social, environmental and economic externalities of private automobile travel. Mobility-as-a …
social, environmental and economic externalities of private automobile travel. Mobility-as-a …
Analysis and control of autonomous mobility-on-demand systems
Challenged by urbanization and increasing travel needs, existing transportation systems
need new mobility paradigms. In this article, we present the emerging concept of …
need new mobility paradigms. In this article, we present the emerging concept of …
Privacy-preserving traffic flow prediction: A federated learning approach
Existing traffic flow forecasting approaches by deep learning models achieve excellent
success based on a large volume of data sets gathered by governments and organizations …
success based on a large volume of data sets gathered by governments and organizations …
Cyber-attacks in the next-generation cars, mitigation techniques, anticipated readiness and future directions
Abstract Modern-day Connected and Autonomous Vehicles (CAVs) with more than 100
million code lines, running up-to a hundred Electronic Control Units (ECUs) will create and …
million code lines, running up-to a hundred Electronic Control Units (ECUs) will create and …
[HTML][HTML] Barriers to the adoption of the mobility-as-a-service concept: The case of Istanbul, a large emerging metropolis
Y Kayikci, O Kabadurmus - Transport policy, 2022 - Elsevier
Megatrends such as urbanization, digitalization, and decarbonization have created the
necessity for new and creative approaches to the urban transportation system. As a solution …
necessity for new and creative approaches to the urban transportation system. As a solution …
Privacy-preserving cross-area traffic forecasting in ITS: A transferable spatial-temporal graph neural network approach
Y Qi, J Wu, AK Bashir, X Lin, W Yang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Traffic forecasting is essential in improving and maintaining safety and orderliness in
intelligent transportation systems (ITS). As a deep learning approach, graph neural networks …
intelligent transportation systems (ITS). As a deep learning approach, graph neural networks …
[图书][B] Informed Urban transport systems: Classic and emerging mobility methods toward smart cities
J Chow - 2018 - books.google.com
Informed Urban Transport Systems examines how information gathered from new
technologies can be used for optimal planning and operation in urban settings …
technologies can be used for optimal planning and operation in urban settings …
[HTML][HTML] The first two decades of smart city research from a risk perspective
Although they offer major advantages, smart cities present unprecedented risks and
challenges. There are abundant discrete studies on risks related to smart cities; however …
challenges. There are abundant discrete studies on risks related to smart cities; however …
Fedgru: Privacy-preserving traffic flow prediction via federated learning
Existing traffic flow forecasting technologies achieve great success based on deep learning
models on a large number of datasets gathered by organizations. However, there are two …
models on a large number of datasets gathered by organizations. However, there are two …
A differential privacy-based privacy-preserving data publishing algorithm for transit smart card data
Y Li, D Yang, X Hu - Transportation Research Part C: Emerging …, 2020 - Elsevier
This manuscript is focused on transit smart card data and finds that the release of such
trajectory information after simple anonymization creates high concern about breaching …
trajectory information after simple anonymization creates high concern about breaching …