scholarly journals Development and testing of braking and acceleration features for vehicle advanced driver assistance system

2022 ◽  
Vol 12 (2) ◽  
pp. 2047
Author(s):  
Johann Carlo Marasigan ◽  
Gian Paolo Mayuga ◽  
Elmer Magsino
Keyword(s):  
Traffic Congestion ◽  
Fuzzy Logic Controller ◽  
Driver Assistance System ◽  
Control Unit ◽  
Assistance System ◽  
Advanced Driver Assistance System ◽  
Driver Assistance ◽  
Safe Distance ◽  
Distance Information ◽  
Urban Planning And Development

<span lang="EN-US">Traffic congestion is a constant problem for cities worldwide. The human driving inefficiency and poor urban planning and development contribute to traffic buildup and travel discomfort. An example of human inefficiency is the phantom traffic jam, which is caused by unnecessary braking, causing traffic to slow down, and eventually coming to a stop. In this study, a brake and acceleration feature (BAF) for the advanced driver assistance system (ADAS) is proposed to mitigate the effects of the phantom traffic phenomenon. In its initial stage, the BAF provides a heads-up display that gives information on how much braking and acceleration input is needed to maintain smooth driving conditions, i.e., without sudden acceleration or deceleration, while observing a safe distance from the vehicle in front. BAF employs a fuzzy logic controller that takes distance information from a light detection and ranging (LIDAR) sensor and the vehicle’s instantaneous speed from the engine control unit (ECU). It then calculates the corresponding percentage value of needed acceleration and braking in order to maintain travel objectives of smooth and safe-distance travel. Empirical results show that the system suggests acceleration and braking values slightly higher than the driver’s actual inputs and can achieve 90% accuracy overall.</span>

scholarly journals Advanced Driver-Assistance System (ADAS) for Intelligent Transportation Based on the Recognition of Traffic Cones

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Liyong Wang ◽  
Peng Sun ◽  
Min Xie ◽  
Shaobo Ma ◽  
Boxiong Li ◽  
...  
Keyword(s):  
Path Planning ◽  
Machine Vision ◽  
Driver Assistance System ◽  
Vision System ◽  
Intelligent Transportation ◽  
Assistance System ◽  
Advanced Driver Assistance System ◽  
Depth Information ◽  
Driver Assistance ◽  
Temporary Road

Great changes have taken place in automation and machine vision technology in recent years. Meanwhile, the demands for driving safety, efficiency, and intelligence have also increased significantly. More and more attention has been paid to the research on advanced driver-assistance system (ADAS) as one of the most important functions in intelligent transportation. Compared with traditional transportation, ADAS is superior in ensuring passenger safety, optimizing path planning, and improving driving control, especially in an autopilot mode. However, level 3 and above of the autopilot are still unavailable due to the complexity of traffic situations, for example, detection of a temporary road created by traffic cones. In this paper, an analysis of traffic-cone detection is conducted to assist with path planning under special traffic conditions. A special machine vision system with two monochrome cameras and two color cameras was used to recognize the color and position of the traffic cones. The result indicates that this novel method could recognize the red, blue, and yellow traffic cones with 85%, 100%, and 100% success rate, respectively, while maintaining 90% accuracy in traffic-cone distance sensing. Additionally, a successful autopilot road experiment was conducted, proving that combining color and depth information for recognition of temporary road conditions is a promising development for intelligent transportation of the future.

scholarly journals Vehicle-in-the-Loop in Global Coordinates for Advanced Driver Assistance System

2020 ◽  
Vol 10 (8) ◽  
pp. 2645 ◽  
Author(s):  
Changwoo Park ◽  
Seunghwan Chung ◽  
Hyeongcheol Lee
Keyword(s):  
Real World ◽  
Driver Assistance System ◽  
Test Method ◽  
Assistance System ◽  
Advanced Driver Assistance System ◽  
Driver Assistance ◽  
Maintenance Time ◽  
Synchronization Module ◽  
Vehicle Controllers ◽  
Test Scenarios

Most vehicle controllers are developed and verified with V-model. There are several traditional methods in the automotive industry called “X-in-the-Loop (XIL)”. However, the validation of advanced driver assistance system (ADAS) controllers is more complicated and needs more environmental resources because the controller interacts with the external environment of the vehicle. Vehicle-in-the-Loop (VIL) is a recently being developed approach for simulating ADAS vehicles that ensures the safety of critical test scenarios in real-world testing using virtual environments. This new test method needs both properties of traditional computer simulations and real-world vehicle tests. This paper presents a Vehicle-in-the-Loop topology for execution in global Coordinates system. Also, it has a modular structure with four parts: synchronization module, virtual environment, sensor emulator and visualizer, so each part can be developed and modified separately in combination with other parts. This structure of VIL is expected to save maintenance time and cost. This paper shows its acceptability by testing ADAS on both a real and the VIL system.

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