Single-Handed Driving System with Kinect

2013 ◽  
pp. 631-639 ◽  
Author(s):  
Jae Pyo Son ◽  
Arcot Sowmya
Keyword(s):  
Driving System

Smart Driving System for Improving Traffic Flow

2017 ◽  
Vol 7 (7) ◽  
pp. 236
Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Adaptive Cruise Control ◽  
Human Perception ◽  
Cruise Control ◽  
Driving System ◽  
V2v Communication ◽  
Traffic Conditions ◽  
Cooperative Adaptive Cruise Control

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

Research on driving system with wireless remote control in high speed rice transplanter

2013 ◽  
Vol 38 (4) ◽  
pp. 441-445 ◽  
Author(s):  
Chang-sheng XIE ◽  
Pin JIANG ◽  
Wen-wu HU ◽  
Ya-hui LUO ◽  
Yan-li TONG
Keyword(s):  
Remote Control ◽  
High Speed ◽  
Driving System

Autonomy and Responsibility in Hybrid Systems

2017 ◽  
Author(s):  
Wulf Loh ◽  
Janina Loh
Keyword(s):  
Hybrid Systems ◽  
Hybrid System ◽  
Moral Dilemma ◽  
Autonomous Driving ◽  
Shared Responsibility ◽  
Driving System ◽  
Autonomous Cars ◽  
Self Driving Cars ◽  
Trolley Cases ◽  
Autonomous Driving System

In this chapter, we give a brief overview of the traditional notion of responsibility and introduce a concept of distributed responsibility within a responsibility network of engineers, driver, and autonomous driving system. In order to evaluate this concept, we explore the notion of man–machine hybrid systems with regard to self-driving cars and conclude that the unit comprising the car and the operator/driver consists of such a hybrid system that can assume a shared responsibility different from the responsibility of other actors in the responsibility network. Discussing certain moral dilemma situations that are structured much like trolley cases, we deduce that as long as there is something like a driver in autonomous cars as part of the hybrid system, she will have to bear the responsibility for making the morally relevant decisions that are not covered by traffic rules.

Vision-Based Navigation of Autonomous Vehicles in Roadway Environments with Unexpected Hazards

2019 ◽  
Vol 2673 (12) ◽  
pp. 494-507 ◽  
Author(s):  
Mhafuzul Islam ◽  
Mashrur Chowdhury ◽  
Hongda Li ◽  
Hongxin Hu
Keyword(s):  
Object Detection ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Semantic Segmentation ◽  
Steering Wheel ◽  
Potential Hazard ◽  
Driving System ◽  
Hazardous Object ◽  
Vision Based Navigation ◽  
Navigational System

Vision-based navigation of autonomous vehicles primarily depends on the deep neural network (DNN) based systems in which the controller obtains input from sensors/detectors, such as cameras, and produces a vehicle control output, such as a steering wheel angle to navigate the vehicle safely in a roadway traffic environment. Typically, these DNN-based systems in the autonomous vehicle are trained through supervised learning; however, recent studies show that a trained DNN-based system can be compromised by perturbation or adverse inputs. Similarly, this perturbation can be introduced into the DNN-based systems of autonomous vehicles by unexpected roadway hazards, such as debris or roadblocks. In this study, we first introduce a hazardous roadway environment that can compromise the DNN-based navigational system of an autonomous vehicle, and produce an incorrect steering wheel angle, which could cause crashes resulting in fatality or injury. Then, we develop a DNN-based autonomous vehicle driving system using object detection and semantic segmentation to mitigate the adverse effect of this type of hazard, which helps the autonomous vehicle to navigate safely around such hazards. We find that our developed DNN-based autonomous vehicle driving system, including hazardous object detection and semantic segmentation, improves the navigational ability of an autonomous vehicle to avoid a potential hazard by 21% compared with the traditional DNN-based autonomous vehicle driving system.

scholarly journals Surface Quality Improvement by Using a Novel Driving System Design in Single-Side Planetary Abrasive Lapping

Materials ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1691 ◽  
Author(s):  
Zhenzhen Chen ◽  
Donghui Wen ◽  
Jianfei Lu ◽  
Jie Yang ◽  
Huan Qi
Keyword(s):  
System Design ◽  
Surface Quality ◽  
Material Removal ◽  
Rotation Speed ◽  
Target Surface ◽  
Speed Ratio ◽  
The Novel ◽  
Particle Trajectories ◽  
Driving System ◽  
Single Side

For the traditional single-side planetary abrasive lapping process particle trajectories passing over the target surface are found to be periodically superposed due to the rational rotation speed ratio of the lapping plate to workpiece that could affect the material removal uniformity and hence its surface quality. This paper reports on a novel driving system design with combination of the tapered roller and contact roller to realize the irrational rotation speed ratio of the lapping plate to workpiece in the single-side planetary abrasive lapping process for the improvement of surface quality. Both of the numerical and experimental investigations have been conducted to evaluate the abrasive lapping performance of the novel driving system. It has been found from the numerical simulation that particle trajectories would theoretically cover the whole target surface if the lapping time is long enough due to their non-periodic characteristics, which can guarantee the uniformity of material removal from the surface of workpiece with relatively high surface quality. The encouraging experimental results underline the potential of the novel driving system design in the application of the single-side planetary abrasive lapping for the improvement of the surface quality in terms of surface roughness and material removal uniformity.

Level-wise driving knowledge induction for embedded automatic train driving system

2021 ◽  
pp. 107754632110033
Author(s):  
Gang Xiao ◽  
Qinwen Yang ◽  
Fan Yang ◽  
Tao Liu ◽  
Tao Li ◽  
...  
Keyword(s):  
Embedded System ◽  
Fuzzy Rule ◽  
Operating Efficiency ◽  
Driving Experience ◽  
Driving System ◽  
Automatic Driving ◽  
Energy Consumption Reduction ◽  
Experience Levels ◽  
Consumption Reduction ◽  
Regression Learning

Automatic driving of trains can significantly reduce the energy cost and enhance the operating efficiency and safety. The automatic train driving system has to be an embedded system that can run onboard with low power, which necessitates an efficient inference model. In this article, a level-wise driving knowledge induction approach is proposed for embedded automatic train driving systems. The coincident driving patterns in the records of drivers with different experience levels suggest the suitability of a driving experience knowledge rule induction approach. We design a two-level learning approach to obtain both the driving experience pattern in fuzzy rule-based knowledge form and the detailed parameters of velocity and gear by regression learning methods. With 8.93% energy consumption reduction compared with average human drivers, the experiments indicate the effectiveness of our approach.

scholarly journals Motor shifting and torque distribution control of a multi-motor driving system in electric construction vehicles

2021 ◽  
Vol 13 (6) ◽  
pp. 168781402110284
Author(s):  
Weikang Kong ◽  
Jixin Wang ◽  
Dewen Kong ◽  
Yuanying Cong ◽  
Shuangshi Feng
Keyword(s):  
Power Systems ◽  
Control Method ◽  
Simulation Analysis ◽  
Rapid Development ◽  
Transmission Efficiency ◽  
Torque Distribution ◽  
Driving System ◽  
Construction Machinery ◽  
Improve Energy Efficiency ◽  
Parameter Matching

With the rapid development of the world economic construction and the shortage of energy, it has become a hot research issue to realize the electrification of the vehicle driving system and improve energy efficiency. Most of the electric construction machinery power systems are characterized by low speed and high load. The coordinated driving of multiple motors can increase the output torque and improve the transmission efficiency of the machine on the basis of a compact layout. A novel configuration of electric construction vehicles based on multi-motor and single-speed and its driving torque distribution control method is presented in this paper. The detailed mathematical model is established and the simulation analysis is carried out based on it. The results show that the proposed multi-motor driving system with the control strategy can improve the overall efficiency in the condition of ensuring the driving force when the parameter matching and motors choosing reasonably.

Modeling and suppression of unbalanced radial force for in-wheel motor driving system

2021 ◽  
pp. 107754632110260
Author(s):  
Zhaoxue Deng ◽  
Xu Li ◽  
Tianqin Liu ◽  
Shuen Zhao
Keyword(s):  
Electromagnetic Force ◽  
Switched Reluctance Motor ◽  
Radial Force ◽  
Force Amplitude ◽  
Switched Reluctance ◽  
Driving System ◽  
Coupling Relationship ◽  
Force Fluctuation ◽  
Reluctance Motor ◽  
Road Excitation

Considering the negative vertical dynamics effect of switched reluctance motor on an in-wheel motor driving system, this article presents a modeling and suppression method for unbalanced radial force of the in-wheel motor driving system. To tease out the coupling relationship within the in-wheel motor driving system, this investigation, respectively, explores the principle of unbalanced radial force and the coupling relationship between rotor eccentricity and road excitation based on the suspension response model with unbalanced radial force under road excitation. The switched reluctance motor nonlinear analytical model was fitted by the Fourier series, and its radial electromagnetic force was modeled and analyzed by the Maxwell stress tensor method. To mitigate the influence of radial electromagnetic force fluctuation and unbalanced radial force amplitude value under eccentricity condition on the in-wheel motor driving system, the elitist non-dominated sorting genetic algorithm was adopted to improve radial electromagnetic force fluctuation and unbalanced radial force amplitude value of the switched reluctance motor. The simulation results show that the proposed optimization method can suppress the radial electromagnetic force fluctuation and unbalanced radial force amplitude value, and the negative effect of vertical dynamics of the in-wheel motor driving system is conspicuously mitigated.

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