scholarly journals Erratum: Ahmad, S.; Malik, S.; Park, D.-H.; Kim, D. Design of Lightweight Driver-Assistance System for Safe Driving in Electric Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5380
Author(s):  
Shabir Ahmad ◽  
Sehrish Malik ◽  
Dong-Hwan Park ◽  
DoHyeun Kim
Keyword(s):  
Electric Vehicles ◽  
Driver Assistance System ◽  
Assistance System ◽  
Driver Assistance ◽  
Safe Driving

The authors wish to make the following erratum to this paper [...]

scholarly journals Design of Lightweight Driver-Assistance System for Safe Driving in Electric Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4761 ◽  
Author(s):  
Shabir Ahmad ◽  
Sehrish Malik ◽  
Dong-Hwan Park ◽  
DoHyeun Kim
Keyword(s):  
Electric Vehicles ◽  
Driver Assistance System ◽  
Cost Driver ◽  
Assistance System ◽  
Battery Life ◽  
Human Beings ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Safe Driving ◽  
Assistance Systems

Electric-vehicle technology is an emerging area offering several benefits such as economy due to low running costs. Electric vehicles can also help to significantly reduce CO 2 emission, which is a vital factor for environmental pollution. Modern vehicles are equipped with driver-assistance systems that facilitate drivers by offloading some of the tasks a driver does while driving. Human beings are prone to errors. Therefore, accidents and fatalities can happen if the driver fails to perform a particular task within the deadline. In electric vehicles, the focus has always been to optimize the power and battery life, and thus, any additional hardware can affect their battery life significantly. In this paper, the design of driver-assistance systems has been introduced to automate and assist in some of the vital tasks, such as a braking system, in an optimized manner. We revamp the idea of the traditional driver-assistance system and propose a generic lightweight system based on the leading factors and their impact on accidents. We model tasks for these factors and simulate a low-cost driver-assistance system in a real-time context, where these scenarios are investigated and tasks schedulability is formally proved before deploying them in electric vehicles. The proposed driver-assistance system offers many advantages. It decreases the risk of accidents and monitors the safety of driving. If, at some point, the risk index is above a certain threshold, an automated control algorithm is triggered to reduce it by activating different actuators. At the same time, it is lightweight and does not require any dedicated hardware, which in turn has a significant advantage in terms of battery life. Results show that the proposed system not only is accurate but also has a very negligible effect on energy consumption and battery life.

Road Parameter-Based Driver Assistance System for Safe Driving

2019 ◽  
Vol 2 (4) ◽  
pp. 253-262
Author(s):  
Sai Charan Addanki ◽  
Keyword(s):  
Driver Assistance System ◽  
Assistance System ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Safe Driving ◽  
The Road ◽  
Lane Tracking ◽  
Road Type ◽  
Key Aspects ◽  
Type Classification

One of the key aspects of Advanced Driver Assistance Systems (ADAS) is ensuring the safety of the driver by maintaining a safe drivable speed. Overspeeding is one of the critical factors for accidents and vehicle rollovers, especially at road turns. This article aims to propose a driver assistance system for safe driving on Indian roads. In this regard, a camera-based classification of the road type combined with the road curvature estimation helps the driver to maintain a safe drivable speed primarily at road curves. Three Deep Convolutional Neural Network (CNN) models viz. Inception-v3, ResNet-50, and VGG-16 are being used for the task of road type classification. In this regard, the models are validated using a self-created dataset of Indian roads and an optimal performance of 83.2% correct classification is observed. For the calculation of road curvature, a lane tracking algorithm is used to estimate the curve radius of a structured road. The road type classification and the estimated road curvature values are given as inputs to a simulation-based model, CARSIM (vehicle road simulator to estimate the drivable speed). The recommended speed is then compared and analyzed with the actual speeds obtained from subjective tests.

scholarly journals Advanced Driver Assistance System

2020 ◽  
Vol 8 (6) ◽  
pp. 3481-3487
Keyword(s):  
Automobile Industry ◽  
Human Error ◽  
Driver Assistance System ◽  
Warning System ◽  
Modern Technology ◽  
Assistance System ◽  
Advanced Driver Assistance System ◽  
Driver Assistance ◽  
Multiple Sources ◽  
Safe Driving

The prime motive of the automobile industry is to improve safety in driving machines and avoid accidents. Traffic rules and regulations drafted by the law aren’t followed by many citizens. This is another reason for an accident. Accidents sometimes are unintentional. Some serious acts like drunk and drive, ignoring the signboards, and over speeding might result in severe causalities. To prevent situations like these we seek the Advanced Driver Assistance System (ADAS). ADAS has the potential to increase safety and provide comfort driving. Driving situations are electronically controlled and decisions are simplified for the driver. Old people may also receive plenty of benefits from this technology. ADAS is designed with a humanmachine interface which tends to improve road safety marginally. Accidents caused by human error can also be minimized. ADAS helps the driver to automate, adapt and enhance the vehicle system for safe driving. Passive safety technologies like wearing seatbelts and airbags cannot prevent road fatalities. Modern technology like ADAS is different from traditional and passive technology and minimizes the fatalities consistently. ADAS also alert the driver of potential problems and helps in maintaining the stability of the vehicle under critical circumstances. Safety features are implemented to take control of the vehicle during collisions. ADAS relies on inputs from multiple sources like the brake assistant, pressure control system, lane departure warning system, road sign identification, etc. Additional features can also be customized based on the needs of the driver. In this paper methods to prevent over speeding, vehicle collisions, and driver alertness systems are discussed. RFID readers are used for sensing the speed limit in the signboards. The speed of the vehicle is managed based on the reading obtained from the tags. Sensors like ultrasonic, alcohol detector, gas sensor, temperature sensor are used to measure other parameters to enhance the safety measure while driving.

Intelligent Advanced Driver Assistance System for Electric Vehicles

2011 ◽  
Author(s):  
Konstantinos Demestichas ◽  
Evgenia Adamopoulou ◽  
Michalis Masikos ◽  
Wolfgang Kipp ◽  
Thomas Benz
Keyword(s):  
Electric Vehicles ◽  
Driver Assistance System ◽  
Assistance System ◽  
Advanced Driver Assistance System ◽  
Driver Assistance

Advanced Driver Assistance System Supporting Routing and Navigation for Fully Electric Vehicles

2012 ◽  
pp. 197-206 ◽  
Author(s):  
Konstantinos Demestichas ◽  
Evgenia Adamopoulou ◽  
Michalis Masikos ◽  
Thomas Benz ◽  
Wolfgang Kipp ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Driver Assistance System ◽  
Assistance System ◽  
Advanced Driver Assistance System ◽  
Driver Assistance
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