[HTML][HTML] A federated mixed logit model for personal mobility service in autonomous transportation systems
Looking ahead to the future-stage autonomous transportation system (ATS), personal
mobility service (PMS) aims to provide the recommended travel options based on both …
mobility service (PMS) aims to provide the recommended travel options based on both …
[HTML][HTML] Exploring the Potentials of Open-Source Big Data and Machine Learning in Shared Mobility Fleet Utilization Prediction
The urban transportation landscape has been rapidly growing and dynamically changing in
recent years, supported by the advancement of information and communication …
recent years, supported by the advancement of information and communication …
Federated learning framework to decentralize mobility forecasting in smart cities
R Valente, C Senna, P Rito… - NOMS 2023-2023 IEEE …, 2023 - ieeexplore.ieee.org
The Federated Learning (FL) paradigm aims to provide performance advantages over
centralized models, such as lower latency and communication overhead when doing most of …
centralized models, such as lower latency and communication overhead when doing most of …
Preserving uncertainty in demand prediction for autonomous mobility services
Unlike traditional bus fleets, autonomous mobility services are naturally amenable to
dynamic, demand-responsive adaptation of itinerary. Accurate prediction of demand for such …
dynamic, demand-responsive adaptation of itinerary. Accurate prediction of demand for such …
Gaussian process-based decentralized data fusion and active sensing for mobility-on-demand system
Mobility-on-demand (MoD) systems have recently emerged as a promising paradigm of one-
way vehicle sharing for sustainable personal urban mobility in densely populated cities. In …
way vehicle sharing for sustainable personal urban mobility in densely populated cities. In …
[HTML][HTML] A collaborative privacy-preserving approach for passenger demand forecasting of autonomous taxis empowered by federated learning in smart cities
A Munawar, M Piantanakulchai - Scientific Reports, 2024 - nature.com
Abstract The concept of Autonomous Taxis (ATs) has witnessed a remarkable surge in
popularity in recent years, paving the way toward future smart cities. However, accurately …
popularity in recent years, paving the way toward future smart cities. However, accurately …
SMART mobility via prediction, optimization and personalization
In this chapter, we present a methodological approach for Smart Mobility that integrates
three key features: prediction, optimization, and personalization. They are integrated in such …
three key features: prediction, optimization, and personalization. They are integrated in such …
Investigating user perception on autonomous vehicle (AV) based mobility-on-demand (MOD) services in Singapore using the logit kernel approach
The rapid development of autonomous vehicles (AV) in recent years has drawn the attention
of numerous countries in terms of its feasibility for use and deployment as individually …
of numerous countries in terms of its feasibility for use and deployment as individually …
[HTML][HTML] Predicting car availability in free floating car sharing systems: Leveraging machine learning in challenging contexts
Free-Floating Car Sharing (FFCS) services are currently available in tens of cities and
countries spread all over the worlds. Depending on citizens' habits, service policies, and …
countries spread all over the worlds. Depending on citizens' habits, service policies, and …
A Federated Learning-Based Framework for Ride-Sourcing Traffic Demand Prediction
Accurate short-term ride-sourcing demand prediction is vital for transportation operations,
planning, and policy-making. With the models developed from data based on individual ride …
planning, and policy-making. With the models developed from data based on individual ride …