A review and perspective on optical phased array for automotive LiDAR
CP Hsu, B Li, B Solano-Rivas, AR Gohil… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
This paper aims to review the state of the art of Light Detection and Ranging (LiDAR)
sensors for automotive applications, and particularly for automated vehicles, focusing on …
sensors for automotive applications, and particularly for automated vehicles, focusing on …
Toward human-vehicle collaboration: Review and perspectives on human-centered collaborative automated driving
The last decade witnessed a great development of automated driving vehicles (ADVs) and
vehicle intelligence. The significant increment of machine intelligence poses a new …
vehicle intelligence. The significant increment of machine intelligence poses a new …
SPINN: synergistic progressive inference of neural networks over device and cloud
Despite the soaring use of convolutional neural networks (CNNs) in mobile applications,
uniformly sustaining high-performance inference on mobile has been elusive due to the …
uniformly sustaining high-performance inference on mobile has been elusive due to the …
Trends and emerging technologies for the development of electric vehicles
T Mo, Y Li, K Lau, CK Poon, Y Wu, Y Luo - Energies, 2022 - mdpi.com
In response to severe environmental and energy crises, the world is increasingly focusing
on electric vehicles (EVs) and related emerging technologies. Emerging technologies for …
on electric vehicles (EVs) and related emerging technologies. Emerging technologies for …
A xgboost-based lane change prediction on time series data using feature engineering for autopilot vehicles
Road accidents wreck lives. Could technology stop them from happening? Driving better
road safety with technology and artificial intelligence are the key elements considered by …
road safety with technology and artificial intelligence are the key elements considered by …
Driving-induced neurological biomarkers in an advanced driver-assistance system
Physiological signals are immediate and sensitive to neurological changes resulting from
the mental workload induced by various driving environments and are considered a …
the mental workload induced by various driving environments and are considered a …
A survey on silicon photonics for deep learning
Deep learning has led to unprecedented successes in solving some very difficult problems
in domains such as computer vision, natural language processing, and general pattern …
in domains such as computer vision, natural language processing, and general pattern …
Object detection in autonomous vehicles: Status and open challenges
Object detection is a computer vision task that has become an integral part of many
consumer applications today such as surveillance and security systems, mobile text …
consumer applications today such as surveillance and security systems, mobile text …
DeepCrash: A deep learning-based internet of vehicles system for head-on and single-vehicle accident detection with emergency notification
WJ Chang, LB Chen, KY Su - IEEE Access, 2019 - ieeexplore.ieee.org
Most individuals involved in traffic accidents receive assistance from drivers, passengers, or
other people. However, when a traffic accident occurs in a sparsely populated area or the …
other people. However, when a traffic accident occurs in a sparsely populated area or the …
Roadmap for cybersecurity in autonomous vehicles
Autonomous vehicles are on the horizon and will be transforming transportation safety and
comfort. These vehicles will be connected to various external systems and utilize advanced …
comfort. These vehicles will be connected to various external systems and utilize advanced …