Utterance Generation Based on Driving Evaluation for Driving Assistance Robot

2016 ◽  
Vol 20 (5) ◽  
pp. 836-844 ◽  
Author(s):  
Yoshikazu Okajima ◽  
◽  
Hiroyuki Masuta ◽  
Masatoshi Okumura ◽  
Tatsuo Motoyoshi ◽  
...  
Keyword(s):  
Evaluation System ◽  
Fuzzy Inference ◽  
Estimation Method ◽  
Assistance System ◽  
Human Beings ◽  
Robot Interaction ◽  
Timing Estimation ◽  
Driving Assistance ◽  
Utterance Generation ◽  
Driving Assistance System

This manuscript describes a robot interaction for the driving assistance system of an Ultra-Compact Electric Vehicle (UCEV). Fun-to-drive and safety are important for improving the commercial value of UCEV. To improve fun-to-drive and safety, the improvement of the driving skills is important. However, the driving assistance system of an ordinary vehicle only considers the objective driving evaluation. Therefore, we propose an interactive driving assistance system that considers the relation between the subjective as well as the objective driving evaluation. Furthermore, we install a communicating robot within a UCEV to interact with human beings in real time. As a first step, we propose a driving evaluation system by applying a simplified fuzzy inference, and an interaction timing estimation method by applying a spiking neural network. Through an off-line simulation experiment, we verify the effectiveness of our proposal that is able to generate a robot utterances content as well as estimate reasonable timing.

Modelling of Safe Driving Assistance System for Automotive and Prediction of Accident Rates

2019 ◽  
Vol 10 (1) ◽  
pp. 61-77
Author(s):  
Debraj Bhattacharjee ◽  
Prabha Bhola ◽  
Pranab K. Dan
Keyword(s):  
Fuzzy Inference ◽  
Warning System ◽  
Assistance System ◽  
Inference System ◽  
Safe Driving ◽  
Driving Assistance ◽  
System Module ◽  
Accident Rates ◽  
The Right ◽  
Driving Assistance System

This research article attempts to analytically determine the factors, significant for safety, in connection with driving of automotives as well as to develop a conceptual model of the driving assistance system, using the knowledge about such factors. Millions of casualties due to road accidents, happen worldwide every year and the annual average of lives lost in India alone is about hundred and fifty thousand. The causes of such accidents are attributed to road characteristic and condition, driving faults, driving conditions or traffic environmental factors and defects or functional failure in vehicle mechanism. Studies have focused primarily on these factors without associating the ‘weather' which has been reported as in a work but as an isolated factor without including the above three. This work includes all the four stated factors in modelling the driver assistance system for automatic speed control with warning system module. Further, to predict accident rates in a particular region a model using adaptive neuro fuzzy inference system (ANFIS) is proposed in this work, which may be used by the vehicle manufactures to select the right product variant to minimise accidents.

Bus driving assistance system for town area by using ATmega328P microcontroller

2017 ◽  
Author(s):  
Mohamad Fauzi Zakaria ◽  
Tan Jiah Soon ◽  
Munzilah Md Rohani
Keyword(s):  
Assistance System ◽  
Driving Assistance ◽  
Driving Assistance System ◽  
Town Area

scholarly journals Built-in-self-test system for FPGA-based vehicle video-detection and distance measurement

2021 ◽  
Author(s):  
Md Forhad Ebn Anwar
Keyword(s):  
High Speed ◽  
Vision System ◽  
Test System ◽  
Distance Measurement ◽  
Assistance System ◽  
Project Work ◽  
Practical Calculation ◽  
Automatic Driving ◽  
Driving Assistance ◽  
Driving Assistance System

Collision of vehicles in highways are very frequent. Because of high speed (more than 100 km/hour), the momentum of collision is too high that leads sever casualty. Automatic Driving Assistance system can assist the vehicle operators to take decision based on realistic practical calculation on safety measures. It is always better to have third eye working parallel with human to avoid road accident. There are several technologies used to develop perfect driving assistance system to achieve higher accuracy in detection, identification and distance measurement of obstacles where vision based system is one of them. Mono-vision system provides cheap and fast solution rather stereo vision. This project work conducted with objective to comprehend computational complexity in implementation of mono-vison camera based object detection where system will generate warning if the detected object has a motion towards target. Processing and analyzing of captured video image is the focused mechanism of implementation and used internal image generator module to mimic actual video camera. Appeared size of the shape of object considered for the decision making. The simulated image pattern can change it’s dimension to represent vehicle movement in one direction (Back and forth). In this work the on-chip car image generation sub-system was proposed designed and partially implemented on the base of the FPGA where Xilinx Zynq-7010 (ZYNQ XC7Z010-1CLG400C) FPGA development board used. Keyword: Computer Vision, mono vision, image processing on FPGA, Automatic Driving Assistance, Vehicle Detection.

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