Design of multifunctional autonomous car using ultrasonic and infrared sensors

Iqbal, Ayesha; Ahmed, Syed Shaheryar; Tauqeer, Muhammad Danish; Sultan, Ali A.; Abbas, Syed Yasir

doi:10.1109/iswsn.2017.8250023

Cited by 16 publications

(8 citation statements)

References 8 publications

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“…However, most of the TMDCs have wide bandgaps varying from 1.4 to 2.1 eV, which limits the responsible light spectrum within the visible range, and thus, obstructs their wide applications. [15][16][17][18][19][20][21]. Thanks to the weak inter-layer van der Waals force, atomically thin 2D layered materials not only can be exfoliated easily from their bulk counterparts, but are also free of surface dangling bonds, which enables stacking any different types of 2D materials together to from heterojunctions with various band structures.…”

Section: Introductionmentioning

confidence: 99%

Visible to near-infrared photodetector based on SnSe₂/WSe₂ heterojunction with potential application in artificial visual neuron

Sun

et al. 2021

Nanotechnology

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Two-dimensional (2d) transition-metal dichalcogenides (TMDCs) are promising candidate materials for developing next generation nano optoelectronic devices, due to their strong interaction with light. In addition, the free of surface dangling bonds makes it possible to stacking any different types of 2D TMDCs together to form heterojunctions with desirable band structures for various applications. However, most of the 2D TMDCs are bipolar or strong unipolar n-type doped, while very few of them show weak p-type doping, which severely affects the performance of the formed heterojunctions. In this work, we fabricated a SnSe 2 /WSe 2 heterojunction of type II band alignment with a small bandgap of ∼0.1 eV, which is ideally for developing optoelectronic devices responsible to a broad light spectrum. N 2 O plasma treatment is applied to enhance the p-type doping of both WSe 2 and SnSe 2 , which results in the increased on-off ratio of n-type SnSe 2 by 50 times and the hole mobility of WSe 2 by 527 times. The WSe 2 /SnSe 2 heterostructure also achieves a decent performance as a p-n junction, which exhibits photo responsivity of 450 mA W −1 and 133 mA W −1 for 700 nm visible light and 1600 nm infrared light, respectively, without any gate or source-drain bias, showing great photovoltaic effect. Moreover, the heterojunction shows great promise as an artificial visual neuron, which can differentiate the dark, visible and infrared light illumination conditions by applying a series of electrical pulses through the back-gate electrode.

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Section: Introductionmentioning

confidence: 99%

Visible to near-infrared photodetector based on SnSe₂/WSe₂ heterojunction with potential application in artificial visual neuron

Sun

et al. 2021

Nanotechnology

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“…Autonomous vehicles use a wide range of sensors to "see" the environment around them, collect the information and feed this collected data to the control system so that decisions can be made and required action can be taken. Cameras help to view objects; LiDAR (Light Detection and Ranging) sensors use light in the form of a laser to measure the distance between the object and the vehicle; RADAR (Radio Detection and Ranging) sensors detect the objects, measures their speed and the direction of their movement [17][18][19][20]. Ultrasonic sensors are also used that help to measure short distances at low speeds.…”

Section: Sensorsmentioning

confidence: 99%

“…The accuracy of the sensing capability can be negatively impacted due to adverse weather conditions (fog, snow, or heavy rain), traffic signs with graffiti, heavy traffic, and low light. Cameras and sensors are not able to track lane markings if they are covered by water, ice, oil, or debris [15,[17][18][19][20]. Figure 3 shows the sensors, cameras, and other basic components of an autonomous car.…”

Section: Sensorsmentioning

confidence: 99%

Sharing the Road: Challenges and Strategies

Iqbal¹

2023

Autonomous Vehicles - Applications and Perspectives

Self Cite

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The idea of autonomous cars has been around for decades, but the recent advancements in automation, robotics and communication technology have given sharp rise to the prospect of self-driving/autonomous vehicles technology. With the recent acceleration in research and development in this field, the dream is now turning into reality and soon autonomous vehicles (AVs) and human-driven vehicles (HVs) will be sharing the road. This chapter presents a deeper insight into the possible challenges and hurdles that need to be addressed in order to make this co-existence possible. Considering all possible scenarios and circumstances is crucial to develop the right technology and infrastructure for future transportation systems.

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“…For example, Yılmaz and Tarıyan [2] installed infrared sensors, ultrasonic sensors, and other components on the smart car. Iqbal et al [3] added infrared and ultrasonic sensors into the car. Their car could detect lanes, overtake other vehicles, avoid obstacles, and identify traffic lights.…”

Section: Introductionmentioning

confidence: 99%

Multi-task Autonomous Driving Based on Improved Convolutional Neural Network and ST Loss in MTS and MOD Modes

Nie¹,

Jian²

2022

Curr. Appl. Sci. Technol.

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Multi-task autonomous driving is a research hotspot in autonomous driving. However, existing research has only achieved single-task or dual-task autonomous driving. Therefore, we propose two novel multi-task approaches: a multi-task shared model mode (MTS) and a multi-object dual-model mode (MOD). In addition, existing neural network architectures are underperforming in multi-task autonomous driving, so we propose a novel neural network architecture - MT-ResNet26. Moreover, to alleviate the problem of noise and class imbalance from data, we propose a new loss function - Stable Loss (ST Loss). Finally, our smart car can achieve multi-task road tracking, left-right turn sign recognition, automatic obstacle avoidance, stop, real-time acceleration and deceleration. In addition, we compare the existing multi-task autonomous driving model YS-VGG17_MSE, which shows our MT-ResNet26_ST is superior in loss value and actual performance. Meanwhile, we use our proposed approaches to train two classical neural networks—ResNet18_MSE* and DenseNet121_MSE*, so that they also achieve multi-task autonomous driving with our proposed approaches, showing the applicability of MTS and MOD. Furthermore, we compare MT-ResNet26_MSE with MT-ResNet26_ST, and the results show that the model using our novel ST Loss outperforms the model using the original loss function MSE. To sum up, it is shown that the performance of multi-task autonomous driving can be achieved and improved using our proposed neural network architecture and loss function. Furthermore, we propose optimized multi-task modes. OMTS and OMOD optimize and accelerate the models using semi-precision techniques based on the TensorRT. The results show that the optimized multi-task autonomous driving accuracy has been further improved.

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Design of multifunctional autonomous car using ultrasonic and infrared sensors

Cited by 16 publications

References 8 publications

Visible to near-infrared photodetector based on SnSe₂/WSe₂ heterojunction with potential application in artificial visual neuron

Visible to near-infrared photodetector based on SnSe₂/WSe₂ heterojunction with potential application in artificial visual neuron

Sharing the Road: Challenges and Strategies

Multi-task Autonomous Driving Based on Improved Convolutional Neural Network and ST Loss in MTS and MOD Modes

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Design of multifunctional autonomous car using ultrasonic and infrared sensors

Cited by 16 publications

References 8 publications

Visible to near-infrared photodetector based on SnSe2/WSe2 heterojunction with potential application in artificial visual neuron

Visible to near-infrared photodetector based on SnSe2/WSe2 heterojunction with potential application in artificial visual neuron

Sharing the Road: Challenges and Strategies

Multi-task Autonomous Driving Based on Improved Convolutional Neural Network and ST Loss in MTS and MOD Modes

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Product

Resources

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Visible to near-infrared photodetector based on SnSe₂/WSe₂ heterojunction with potential application in artificial visual neuron

Visible to near-infrared photodetector based on SnSe₂/WSe₂ heterojunction with potential application in artificial visual neuron