A comprehensive study of speed prediction in transportation system: From vehicle to traffic
In the intelligent transportation system (ITS), speed prediction plays a significant role in
supporting vehicle routing and traffic guidance. Recently, a considerable amount of research …
supporting vehicle routing and traffic guidance. Recently, a considerable amount of research …
A review of model predictive controls applied to advanced driver-assistance systems
Advanced Driver-Assistance Systems (ADASs) are currently gaining particular attention in
the automotive field, as enablers for vehicle energy consumption, safety, and comfort …
the automotive field, as enablers for vehicle energy consumption, safety, and comfort …
Prediction of vehicle driving conditions with incorporation of stochastic forecasting and machine learning and a case study in energy management of plug-in hybrid …
Prediction of short-term future driving conditions can contribute to energy management of
plug-in hybrid electric vehicles and subsequent improvement of their fuel economy. In this …
plug-in hybrid electric vehicles and subsequent improvement of their fuel economy. In this …
Development and evaluation of velocity predictive optimal energy management strategies in intelligent and connected hybrid electric vehicles
In this study, a thorough and definitive evaluation of Predictive Optimal Energy Management
Strategy (POEMS) applications in connected vehicles using 10 to 20 s predicted velocity is …
Strategy (POEMS) applications in connected vehicles using 10 to 20 s predicted velocity is …
Designing a steady-state experimental dataset for predicting transient NOx emissions of diesel engines via deep learning
Deep learning has been used to predict engine phenomena that are otherwise difficult to
predict using conventional modeling approaches. Previous studies using deep learning for …
predict using conventional modeling approaches. Previous studies using deep learning for …
Mobility energy productivity evaluation of prediction-based vehicle powertrain control combined with optimal traffic management
Transportation vehicle and network system efficiency can be defined in two ways: 1)
reduction of travel times across all the vehicles in the system, and 2) reduction in total …
reduction of travel times across all the vehicles in the system, and 2) reduction in total …
Trip-based prediction of hybrid electric vehicles velocity using artificial neural networks
N Abi Akl, J El Khoury… - 2021 IEEE 3rd International …, 2021 - ieeexplore.ieee.org
In this paper, a high-performance Long Short-Term Memory (LSTM) neural network vehicle
velocity predictor considering the case of countries with no vehicle to infrastructure or …
velocity predictor considering the case of countries with no vehicle to infrastructure or …
High-fidelity modeling of light-duty vehicle emission and fuel economy using deep neural networks
The transportation sector contributes significantly to emissions and air pollution globally.
Emission models of modern vehicles are important tools to estimate the impact of …
Emission models of modern vehicles are important tools to estimate the impact of …
An overview of energies problems in robotic systems
Considering the current world trends, the most challenging issue industry is facing revolves
around how to reduce the power consumption of electronic systems. Since the invention of …
around how to reduce the power consumption of electronic systems. Since the invention of …
Multipath traveling purchaser problem with time-dependent market structure using quantum-inspired variable length genetic algorithm
In developing countries, rural and semi-urban markets remain open for a particular period of
time in a day, and items' availabilities and prices vary within the opening hours of a market …
time in a day, and items' availabilities and prices vary within the opening hours of a market …