The rapid development of neuro-inspired computing demands synaptic devices with ultrafast speed, low power consumption, and multiple non-volatile states, among other features. Here, a high-performance synaptic device is designed and established based on a Ag/PbZr0.52Ti0.48O3 (PZT, (111)-oriented)/Nb:SrTiO3 ferroelectric tunnel junction (FTJ). The advantages of (111)-oriented PZT (~1.2 nm) include its multiple ferroelectric switching dynamics, ultrafine ferroelectric domains, and small coercive voltage. The FTJ shows high-precision (256 states, 8 bits), reproducible (cycle-to-cycle variation, ~2.06%), linear (nonlinearity <1) and symmetric weight updates, with a good endurance of >109 cycles and an ultralow write energy consumption. In particular, manipulations among 150 states are realized under subnanosecond (~630 ps) pulse voltages ≤5 V, and the fastest resistance switching at 300 ps for the FTJs is achieved by voltages <13 V. Based on the experimental performance, the convolutional neural network simulation achieves a high online learning accuracy of ~94.7% for recognizing fashion product images, close to the calculated result of ~95.6% by floating-point-based convolutional neural network software. Interestingly, the FTJ-based neural network is very robust to input image noise, showing potential for practical applications. This work represents an important improvement in FTJs towards building neuro-inspired computing systems. 

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High-precision and linear weight updates by subnanosecond pulses in ferroelectric tunnel junction for neuro-inspired computing

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The purpose of this study is to investigate the unsafe conditions of pedestrian crossings at signalized intersections under the mixed traffic environment in Changsha, China. For this purpose, based...

Safety evaluation of pedestrian-vehicle interaction at signalized intersections in Changsha, China

A review on key challenges in intelligent vehicles: Safety and driver-oriented features

Design of novel energy-harvesting regenerative shock absorber using barrel cam follower mechanism to power the auxiliaries of a driverless electric bus

Environmental perception technology is the guarantee of the safety of driverless vehicles. At present, there are a lot of researches and reviews on environmental perception, aiming to realize unmanned driving while ensuring the safety of human life. However, the technology is facing new challenges in the new era. This review paper attempts to systematically summarize environment perception technology and discuss the new challenges currently faced. To this end, we first summarized the advantages, disadvantages and applicable occasions of several commonly used sensing methods to provide a clear selection guide. The new challenges faced by environmental perception technology are discussed from three aspects: technology, external environment and applications. Finally, the article also points out the future development trends and efforts of environmental perception technology.

Jie Bai

Papers

Sensing system of environmental perception technologies for driverless vehicle: A review of state of the art and challenges