A cross-disciplinary comparison of multimodal data fusion approaches and applications: Accelerating learning through trans-disciplinary information sharing
Multimodal data fusion (MMDF) is the process of combining disparate data streams (of
different dimensionality, resolution, type, etc.) to generate information in a form that is more …
different dimensionality, resolution, type, etc.) to generate information in a form that is more …
An automatic traffic density estimation using Single Shot Detection (SSD) and MobileNet-SSD
Traffic density estimation is a very important component of an automated traffic monitoring
system. Traffic density estimation can be used in a number of traffic applications–from …
system. Traffic density estimation can be used in a number of traffic applications–from …
A less-disturbed ecological driving strategy for connected and automated vehicles
This paper proposes a less-disturbed ecological driving strategy for connected and
automated vehicles (CAVs). The proposed strategy integrates the offline planning and the …
automated vehicles (CAVs). The proposed strategy integrates the offline planning and the …
Data fusion-based traffic density estimation and prediction
A Anand, G Ramadurai… - Journal of Intelligent …, 2014 - Taylor & Francis
Traffic congestion has become a major challenge in recent years in many countries of the
world. One way to alleviate congestion is to manage the traffic efficiently by applying …
world. One way to alleviate congestion is to manage the traffic efficiently by applying …
Developing a neural–Kalman filtering approach for estimating traffic stream density using probe vehicle data
This paper presents a novel model for estimating the number of vehicles along signalized
approaches. The proposed estimation algorithm utilizes the adaptive Kalman filter (AKF) to …
approaches. The proposed estimation algorithm utilizes the adaptive Kalman filter (AKF) to …
Mixed traffic flow state detection: A connected vehicles-assisted roadside radar and video data fusion scheme
An increasing number of connected vehicles (CVs) driving together with regular vehicles
(RVs) on the road is an inevitable stage of future traffic development. As accurate traffic flow …
(RVs) on the road is an inevitable stage of future traffic development. As accurate traffic flow …
Multimodal big data fusion for traffic congestion prediction
T Adetiloye, A Awasthi - Multimodal Analytics for Next-Generation Big Data …, 2019 - Springer
Traffic congestion is a widely occurring phenomenon characterized by slower vehicle
speeds, increased vehicular queuing and, sometimes, a complete paralysis of the traffic …
speeds, increased vehicular queuing and, sometimes, a complete paralysis of the traffic …
Multi-modal design of an intelligent transportation system
M Chaturvedi, S Srivastava - IEEE Transactions on Intelligent …, 2016 - ieeexplore.ieee.org
This paper proposes a novel intelligent transportation system (ITS) using the cellular
network, GPS probes, and limited ITS infrastructure for edge-level speed estimation under …
network, GPS probes, and limited ITS infrastructure for edge-level speed estimation under …
Real-time estimation of vehicle counts on signalized intersection approaches using probe vehicle data
MA Aljamal, HM Abdelghaffar… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This paper presents a novel method for estimating the number of vehicles traveling along
signalized approaches using probe vehicle data only. The proposed method uses the …
signalized approaches using probe vehicle data only. The proposed method uses the …
Estimation of traffic stream density using connected vehicle data: Linear and nonlinear filtering approaches
The paper presents a nonlinear filtering approach to estimate the traffic stream density on
signalized approaches based solely on connected vehicle (CV) data. Specifically, a particle …
signalized approaches based solely on connected vehicle (CV) data. Specifically, a particle …