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 Auditory interfaces in automated driving: an international survey

2015 ◽  
Author(s):  
Pavlo Bazilinskyy ◽  
Joost C. F. De Winter
Keyword(s):  
Warning System ◽  
Driver Assistance ◽  
Automated Driving ◽  
Driver Assistance Systems ◽  
Sound System ◽  
Collision Warning ◽  
English Speaking ◽  
Assistance Systems ◽  
Forward Collision Warning ◽  
Auditory Interfaces

This study investigated peoples’ opinion on auditory interfaces in contemporary cars and their willingness to be exposed to auditory feedback in automated driving. We used an Internet-based survey to collect 1,205 responses from 91 countries. The participants stated their attitudes towards two existing auditory driver assistance systems, a parking assistant (PA) and forward collision warning system (FCWS), as well as towards a futuristic augmented sound system (FS) proposed for fully automated driving. The respondents were positive towards the PA and FCWS, and rated their willingness to have these systems as 3.87 and 3.77, respectively (1 = disagree strongly, 5 = agree strongly). The respondents tolerated the FS. The results showed that a female voice is the most preferred feedback mode for the support of takeover requests in highly automated driving, regardless of whether the respondents’ country is English speaking or not. The present results could be useful for designers of automated vehicles and other stakeholders.

scholarly journals Auditory interfaces in automated driving: an international survey

2015 ◽  
Author(s):  
Pavlo Bazilinskyy ◽  
Joost C. F. De Winter
Keyword(s):  
Warning System ◽  
Driver Assistance ◽  
Automated Driving ◽  
Driver Assistance Systems ◽  
Sound System ◽  
Collision Warning ◽  
English Speaking ◽  
Assistance Systems ◽  
Forward Collision Warning ◽  
Auditory Interfaces

This study investigated peoples’ opinion on auditory interfaces in contemporary cars and their willingness to be exposed to auditory feedback in automated driving. We used an Internet-based survey to collect 1,205 responses from 91 countries. The participants stated their attitudes towards two existing auditory driver assistance systems, a parking assistant (PA) and forward collision warning system (FCWS), as well as towards a futuristic augmented sound system (FS) proposed for fully automated driving. The respondents were positive towards the PA and FCWS, and rated their willingness to have these systems as 3.87 and 3.77, respectively (1 = disagree strongly, 5 = agree strongly). The respondents tolerated the FS. The results showed that a female voice is the most preferred feedback mode for the support of takeover requests in highly automated driving, regardless of whether the respondents’ country is English speaking or not. The present results could be useful for designers of automated vehicles and other stakeholders.

scholarly journals Auditory interfaces in automated driving: an international survey

2015 ◽  
Author(s):  
Pavlo Bazilinskyy ◽  
Joost C. F. De Winter
Keyword(s):  
Warning System ◽  
Driver Assistance ◽  
Automated Driving ◽  
Driver Assistance Systems ◽  
Sound System ◽  
Collision Warning ◽  
English Speaking ◽  
Assistance Systems ◽  
Forward Collision Warning ◽  
Auditory Interfaces

This study investigated peoples’ opinion on auditory interfaces in contemporary cars and their willingness to be exposed to auditory feedback in automated driving. We used an Internet-based survey to collect 1,205 responses from 91 countries. The participants stated their attitudes towards two existing auditory driver assistance systems, a parking assistant (PA) and forward collision warning system (FCWS), as well as towards a futuristic augmented sound system (FS) proposed for fully automated driving. The respondents were positive towards the PA and FCWS, and rated their willingness to have these systems as 3.87 and 3.77, respectively (1 = disagree strongly, 5 = agree strongly). The respondents tolerated the FS. The results showed that a female voice is the most preferred feedback mode for the support of takeover requests in highly automated driving, regardless of whether the respondents’ country is English speaking or not. The present results could be useful for designers of automated vehicles and other stakeholders.

Study on the Framework of Intersection Pedestrian Collision Warning System Considering Pedestrian Characteristics

2019 ◽  
Vol 2673 (5) ◽  
pp. 747-758 ◽  
Author(s):  
Dongho Ka ◽  
Donghoun Lee ◽  
Sunghoon Kim ◽  
Hwasoo Yeo
Keyword(s):  
Warning System ◽  
Head Orientation ◽  
Comparison Study ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Detection Range ◽  
Vehicle Collisions ◽  
Collision Warning ◽  
Assistance Systems ◽  
Real Traffic

One of the most widely used advanced driver assistance systems (ADAS) for preventing pedestrian–vehicle collisions is the intersection collision warning system (ICWS). Most previous ICWSs have been implemented with in-vehicle distance sensors, such as radar and lidar. However, the existing ICWSs show some weaknesses in alerting drivers at intersections because of limited detection range and field-of-view. Furthermore, these ICWSs have difficulties in identifying the pedestrian’s crossing intention because the distance sensors cannot capture pedestrian characteristics such as age, gender, and head orientation. To alleviate these defects, this study proposes a novel framework for vision sensor-based ICWS under a cloud-based communication environment, which is called the intersection pedestrian collision warning system (IPCWS). The IPCWS gives a collision warning to drivers approaching an intersection by predicting the pedestrian’s crossing intention based on various machine learning models. With real traffic data extracted by image processing in the IPCWS, a comparison study is conducted to evaluate the performance of the IPCWS in relation to warning timing. The comparison study demonstrates that the IPCWS shows better performance than conventional ICWSs. This result suggests that the proposed system has a great potential for preventing pedestrian–vehicle collisions by capturing the pedestrian’s crossing intention.

Implementation 2D Lidar and Camera for detection object and distance based on RoS

2020 ◽  
Vol 4 (4) ◽  
pp. 231
Author(s):  
Agus Mulyanto ◽  
Rohmat Indra Borman ◽  
Purwono Prasetyawan ◽  
A Sumarudin
Keyword(s):  
Warning System ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Human Errors ◽  
Collision Warning ◽  
Robot Operating System ◽  
Vehicle Collision ◽  
Environment Perception ◽  
Assistance Systems ◽  
Camera Sensors

The advanced driver assistance systems (ADAS) are one of the issues to protecting people from vehicle collision. Collision warning system is a very important part of ADAS to protect people from the dangers of accidents caused by fatigue, drowsiness and other human errors. Multi-sensors has been widely used in ADAS for environment perception such as cameras, radar, and light detection and ranging (LiDAR). We propose the relative orientation and translation between the two sensors are things that must be considered in performing fusion. we discuss the real-time collision warning system using 2D LiDAR and Camera sensors for environment perception and estimate the distance (depth) and angle of obstacles. In this paper, we propose a fusion of two sensors that is camera and 2D LiDAR to get the distance and angle of an obstacle in front of the vehicle that implemented on Nvidia Jetson Nano using Robot Operating System (ROS). Hence, a calibration process between the camera and 2D LiDAR is required which will be presented in session III. After that, the integration and testing will be carried out using static and dynamic scenarios in the relevant environment. For fusion, we use the implementation of the conversion from degree to coordinate. Based on the experiment, we result obtained an average of 0.197 meters

New Lane Departure Warning System Based on Side-View Cameras

2015 ◽  
Vol 764-765 ◽  
pp. 1361-1365
Author(s):  
Cheng Yu Chiu ◽  
Chih Han Chang ◽  
Hsin Jung Lin ◽  
Tsong Liang Huang
Keyword(s):  
Warning System ◽  
Side View ◽  
Lane Departure Warning ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Warning Messages ◽  
Warning Message ◽  
Lane Departure ◽  
Assistance Systems ◽  
The Right

This paper addressed a new lane departure warning system (LDWS). We used the side-view cameras to promote Advanced Driver Assistance Systems (ADAS). A left side-view camera detected the right lane next to vehicle, and a right side-view camera detected the right lane. Two cameras processed in their algorithm and gave warning message, independently and separately. Our algorithm combined those warning messages to analyze environment situations. At the end, we used the LUXGEN MPV to test and showed results of verifications and tests.

scholarly journals Fast and Low-Cost Testing of Advanced Driver Assistance Systems using Small-Scale Vehicles

2019 ◽  
Vol 52 (5) ◽  
pp. 34-39 ◽  
Author(s):  
Astrid Rupp ◽  
Markus Tranninger ◽  
Raffael Wallner ◽  
Jasmina Zubača ◽  
Martin Steinberger ◽  
...  
Keyword(s):  
Low Cost ◽  
Small Scale ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Advanced Driver Assistance Systems ◽  
Assistance Systems

scholarly journals Empirical Analysis of Safe Distance Calculation by the Stereoscopic Capturing and Processing of Images Through the Tailigator System

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 5044
Author(s):  
Gerd Christian Krizek ◽  
Rene Hausleitner ◽  
Laura Böhme ◽  
Cristina Olaverri-Monreal
Keyword(s):  
Low Cost ◽  
Field Tests ◽  
Warning System ◽  
Collision Warning ◽  
The Road ◽  
Cost System ◽  
Straight Line ◽  
Real Value ◽  
On The Road ◽  
Forward Collision Warning

Driver disregard for the minimum safety distance increases the probability of rear-end collisions. In order to contribute to active safety on the road, we propose in this work a low-cost Forward Collision Warning system that captures and processes images. Using cameras located in the rear section of a leading vehicle, this system serves the purpose of discouraging tailgating behavior from the vehicle driving behind. We perform in this paper the pertinent field tests to assess system performance, focusing on the calculated distance from the processing of images and the error margins in a straight line, as well as in a curve. Based on the evaluation results, the current version of the Tailigator can be used at speeds up to 50 km per hour without any restrictions. The measurements showed similar characteristics both on the straight line and in the curve. At close distances, between 3 and 5 m, the values deviated from the real value. At average distances, around 10 to 15 m, the Tailigator achieved the best results. From distances higher than 20 m, the deviations increased steadily with the distance. We contribute to the state of the art with an innovative low-cost system to identify tailgating behavior and raise awareness, which works independently of the rear vehicle’s communication capabilities or equipment.

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