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 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 [...]

Driver Assistance Systems with Communication to Traffic Lights - Configuration of Assistance Systems by Receiving and Transmission and Field Experiments -

2010 ◽  
Vol 22 (6) ◽  
pp. 737-744 ◽  
Author(s):  
Shin Kato ◽  
◽  
Naohisa Hashimoto ◽  
Takeki Ogitsu ◽  
Sadayuki Tsugawa ◽  
...  
Keyword(s):  
Field Experiments ◽  
Driver Assistance System ◽  
The State ◽  
Assistance System ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Traffic Lights ◽  
Assistance Systems

We propose some driver assistance systems with communication to traffic lights. It proposes the driver assistance system that uses information from the traffic lights with the state of the signal and time of the cycle. The demand traffic lights systems are also proposed. In addition, a consideration of the configuration and the construction of the experiment systems, and some field experiments for driver assistance are described.

scholarly journals A Portable Driver Assistance System Headset Using Augmented Reality

2018 ◽  
Vol 7 (3.6) ◽  
pp. 294
Author(s):  
Shantanu Misra ◽  
Vedika Parvez ◽  
Tarush Singh ◽  
E Chitra
Keyword(s):  
Augmented Reality ◽  
Driver Assistance System ◽  
Pedestrian Detection ◽  
Cost Effective ◽  
Weather Conditions ◽  
Assistance System ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Vehicle Collision ◽  
Life Threatening

Vehicle collision leading to life threatening accidents is a common problem which is incrementing noticeably. This necessitated the need for Driver Assistance Systems (DAS) which helps drivers sense nearby obstacles and drive safely. However, it’s inefficiency in unfavorable weather conditions, overcrowded roads, and low signal penetration rates in India posed many challenges during it’s implementation. In this paper, we present a portable Driver Assistance System that uses augmented reality for it’s working. The headset model comprises of five systems working in conjugation in order to assist the driver. The pedestrian detection module, along with the driver alert system serves to assist the driver in focusing his attention to obstacles in his line of sight. Whereas, the speech recognition, gesture recognition and GPS navigation modules together prevent the driver from getting distracted while driving. In the process of serving these two root causes of accidents, a cost effective, portable and holistic driver assistance system has been developed.  

scholarly journals A Forward-Collision Warning System for Electric Vehicles: Experimental Validation in Virtual and Real Environment

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4872
Author(s):  
Nicola Albarella ◽  
Francesco Masuccio ◽  
Luigi Novella ◽  
Manuela Tufo ◽  
Giovanni Fiengo
Keyword(s):  
Electric Vehicles ◽  
Low Cost ◽  
Warning System ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Driver Behaviour ◽  
Collision Warning ◽  
Fast Development ◽  
Assistance Systems ◽  
Forward Collision Warning

Driver behaviour and distraction have been identified as the main causes of rear end collisions. However a promptly issued warning can reduce the severity of crashes, if not prevent them completely. This paper proposes a Forward Collision Warning System (FCW) based on information coming from a low cost forward monocular camera for low end electric vehicles. The system resorts to a Convolutional Neural Network (CNN) and does not require the reconstruction of a complete 3D model of the surrounding environment. Moreover a closed-loop simulation platform is proposed, which enables the fast development and testing of the FCW and other Advanced Driver Assistance Systems (ADAS). The system is then deployed on embedded hardware and experimentally validated on a test track.

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.

scholarly journals Intelligent Torque Vectoring Approach for Electric Vehicles with Per-Wheel Motors

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Alberto Parra ◽  
Asier Zubizarreta ◽  
Joshué Pérez ◽  
Martín Dendaluce
Keyword(s):  
Electric Vehicles ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Torque Distribution ◽  
Neuro Fuzzy ◽  
Torque Vectoring ◽  
Assistance Systems ◽  
Tire Forces ◽  
Analytical Approaches ◽  
Yaw Moment

Transport electrification is currently a priority for authorities, manufacturers, and research centers around the world. The development of electric vehicles and the improvement of their functionalities are key elements in this strategy. As a result, there is a need for further research in emission reduction, efficiency improvement, or dynamic handling approaches. In order to achieve these objectives, the development of suitable Advanced Driver-Assistance Systems (ADAS) is required. Although traditional control techniques have been widely used for ADAS implementation, the complexity of electric multimotor powertrains makes intelligent control approaches appropriate for these cases. In this work, a novel intelligent Torque Vectoring (TV) system, composed of a neuro-fuzzy vertical tire forces estimator and a fuzzy yaw moment controller, is proposed, which allows enhancing the dynamic behaviour of electric multimotor vehicles. The proposed approach is compared with traditional strategies using the high fidelity vehicle dynamics simulator Dynacar. Results show that the proposed intelligent Torque Vectoring system is able to increase the efficiency of the vehicle by 10%, thanks to the optimal torque distribution and the use of a neuro-fuzzy vertical tire forces estimator which provides 3 times more accurate estimations than analytical approaches.

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