scholarly journals Technical Feasibility of Advanced Driver Assistance Systems (ADAS) for Road Traffic Safety

2005 ◽  
Vol 28 (3) ◽  
pp. 167-187 ◽  
Author(s):  
Meng Lu ◽  
Kees Wevers ◽  
Rob Van Der Heijden
F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 1122
Author(s):  
Siti Fatimah Abdul Razak ◽  
Sumendra Yogarayan ◽  
Afizan Azman ◽  
Mohd Fikri Azli Abdullah ◽  
Anang Hudaya Muhamad Amin ◽  
...  

Background: Automobile manufacturers need to have an insight and understand how consumers, specifically drivers, respond to the advanced driver assistance systems (ADAS) technology in their manufactured vehicles. This study reveals drivers’ perceptions of Malaysia’s advanced driver assistance systems, which is currently lacking in the literature. So far, other studies have focused on countries that are unlike Malaysia’s multi-culture environment. Methods: A survey was designed and distributed using convenience sampling to obtain responses from licensed drivers. Questions included demographic and driving questions, the perceptions of benefits and obstacles relevant to ADAS use, vehicle decision-making, and technology use. Data were collected from 818 respondents who were licensed drivers in Malaysia. Results were then analysed using statistical approaches. Results: The findings indicated that 76.8% of drivers have a positive attitude towards ADAS technology, particularly safety applications when they are available. Regardless of the accuracy of these systems, acceptance of the technology may shift upon viewing or hearing messages of possible problems with ADAS. Conclusions: It can be concluded that the safety advantages of ADAS technology are less valued by drivers who do not have experience of road traffic accidents. Furthermore, acceptance of the technology could be undermined by assuming that the safety applications could be compromised.


2015 ◽  
Vol 25 (14) ◽  
pp. 1540038 ◽  
Author(s):  
Guizhen Yu ◽  
Bin Zhou ◽  
Yunpeng Wang ◽  
Xinkai Wun ◽  
Pengcheng Wang

Due to more severe challenges of traffic safety problems, the Advanced Driver Assistance Systems (ADAS) has received widespread attention. Measuring the distance to a preceding vehicle is important for ADAS. However, the existing algorithm focuses more on straight road sections than on curve measurements. In this paper, we present a novel measuring algorithm for the distance to a preceding vehicle on a curve road using on-board monocular camera. Firstly, the characteristics of driving on the curve road is analyzed and the recognition of the preceding vehicle road area is proposed. Then, the vehicle detection and distance measuring algorithms are investigated. We have verified these algorithms on real road driving. The experimental results show that this method proposed in the paper can detect the preceding vehicle on curve roads and accurately calculate the longitudinal distance and horizontal distance to the preceding vehicle.


2018 ◽  
Vol 2018 ◽  
pp. 1-32 ◽  
Author(s):  
Kay Massow ◽  
Ilja Radusch

Advanced Driver Assistance Systems (ADAS) were strong innovation drivers in recent years, towards the enhancement of traffic safety and efficiency. Today’s ADAS adopt an autonomous approach with all instrumentation and intelligence on board of one vehicle. However, to further enhance their benefit, ADAS need to cooperate in the future, using communication technologies. The resulting combination of vehicle automation and cooperation, for instance, enables solving hazardous situations by a coordinated safety intervention on multiple vehicles at the same point in time. Since the complexity of such cooperative ADAS grows with each vehicle involved, very large parameter spaces need to be regarded during their development, which necessitate novel development approaches. In this paper, we present an environment for rapidly prototyping cooperative ADAS based on vehicle simulation. Its underlying approach is either to bring ideas for cooperative ADAS through the prototyping stage towards plausible candidates for further development or to discard them as quickly as possible. This is enabled by an iterative process of refining and assessment. We reconcile the aspects of automation and cooperation in simulation by a tradeoff between precision and scalability. Reducing precise mapping of vehicle dynamics below the limits of driving dynamics enables simulating multiple vehicles at the same time. In order to validate this precision, we also present a method to validate the vehicle dynamics in simulation against real world vehicles.


2017 ◽  
Vol 58 ◽  
pp. 238-244 ◽  
Author(s):  
Francesco Biondi ◽  
David L. Strayer ◽  
Riccardo Rossi ◽  
Massimiliano Gastaldi ◽  
Claudio Mulatti

Author(s):  
Sơn

Các hệ thống hỗ trợ lái xe tiên tiến (Advanced Driver Assistance Systems: ADAS) đóng một vai trò quan trọng trong hệ thống an toàn chủ động chỉ có camera và các phương tiện tự động thông minh. Đối với các ứng dụng này, các yêu cầu về hiệu suất phát hiện đáng tin cậy và thời gian thực là các yếu tố cấp thiết. Bài báo này đề xuất giải pháp tối ưu tốc độ phát hiện ô tô và giảm các cảnh báo lỗi cho các hệ thống phát hiện điểm mù. Theo đó, trước tiên chúng tôi đề xuất bộ phân tầng Cascade – AdaBoost cùng với tập dữ liệu mẫu và thuật toán đào tạo của chúng tôi. Ngoài ra, để cải thiện tốc độ phát hiện, một kĩ thuật lựa chọn vùng quan tâm (Region of Interest: ROI) cũng được sử dụng để tránh trích xuất các vùng có khả năng tạo ra các cảnh báo lỗi như là bầu trời hoặc các vùng không phù hợp với phối cảnh. Phương pháp đề xuất đã tăng tốc độ phát hiện lên ít nhất 1,9 lần và giảm cảnh báo lỗi 2,24 lần so với phương pháp truyền thống ở các ảnh có độ phân giải cao (720 x 480) với tỷ lệ phát hiện đạt 99,4% và tỷ lệ cảnh báo lỗi nhỏ là 4,08%. Phương pháp đề xuất này có thể được ứng dụng cho các xe tự hành thông minh thời gian thực.


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