Roads that cars can read (original) (raw)
Related papers
Sensors
Among the reasons for traffic accidents, distractions are the most common. Although there are many traffic signs on the road that contribute to safety, variable message signs (VMSs) require special attention, which is transformed into distraction. ADAS (advanced driver assistance system) devices are advanced systems that perceive the environment and provide assistance to the driver for his comfort or safety. This project aims to develop a prototype of a VMS (variable message sign) reading system using machine learning techniques, which are still not used, especially in this aspect. The assistant consists of two parts: a first one that recognizes the signal on the street and another one that extracts its text and transforms it into speech. For the first one, a set of images were labeled in PASCAL VOC format by manual annotations, scraping and data augmentation. With this dataset, the VMS recognition model was trained, a RetinaNet based off of ResNet50 pretrained on the dataset COCO. ...
Lanes and Road Signs Recognition for Driver Assistance System
ijcsi.org
Driver assistance systems become one of the most important features of the modern vehicles to ensure driver safety and decrease vehicles accidents on roads. According to their type and functionality, they intervene in different levels of the control processes ...
Advanced Driver-Assistance System with Traffic Sign Recognition for Safe and Efficient Driving
International Journal on Recent and Innovation Trends in Computing and Communication
Advanced Driver-Assistance Systems (ADAS) coupled with traffic sign recognition could lead to safer driving environments. This study presents a sophisticated, yet robust and accurate traffic sign detection system using computer vision and ML, for ADAS. Unavailability of large local traffic sign datasets and the unbalances of traffic sign distribution are the key bottlenecks of this research. Hence, we choose to work with support vector machines (SVM) with a custom-built unbalance dataset, to build a lightweight model with excellent classification accuracy. The SVM model delivered optimum performance with the radial basis kernel, C=10, and gamma=0.0001. In the proposed method, same priority was given to processing time (testing time) and accuracy, as traffic sign identification is time critical. The final accuracy obtained was 87% (with confidence interval 84%-90%) with a processing time of 0.64s (with confidence interval of 0.57s-0.67s) for correct detection at testing, which emph...
IRJET, 2022
Intelligent connected cars (ICVs) are expected to improve transportation in the near future, making it safer, cleaner, and more comfortable for passengers. Even though many ICV prototypes have been created to demonstrate the notion of autonomous driving and the viability of perfecting business effectiveness, there is still a long way to go before high-position ICVs are produced in large quantities. The goal of this study is to provide an overview of key technologies needed for future ICVs from both the current state of the art and future perspectives. Reviewing every affiliated workshop and predicting their future perspectives is a taxing effort, especially for such a complicated and diverse field of research. Advanced driver-assistance systems (ADASs) have become a salient feature for safety in ultramodern vehicles. They're also a crucial underpinning technology in arising independent vehicles. State-of-the-art ADASs are primarily vision grounded, colorful type of features for partner. Automatic Emergency Braking (AEB) and other advanced- seeing technologies are also getting popular. In this composition, this composition is organized to overview the ICV key technologies or Features of ADAS. We bandy approaches used for vision- grounded recognition and detector emulsion in ADAS results. We also punctuate benefits for the coming generation of ADASs. This abecedarian work explains in detail systems for active safety and motorist backing, considering both their structure and their function. These include the well- known standard systems similar as Electronic Stability Control (ESC) or Adaptive voyage Control (ACC), Omni View( Bird eye View), Head- up display. But it includes also new systems for guarding collisions protection, for changing the lane, or for accessible parking. The paper aims at giving a complete picture fastening on the entire Features. First, it describes the factors, which are necessary for backing systems, similar as detectors, and control rudiments. also, it explains crucial features for the stoner-friendly design of mortal- machine interfaces between motorist and backing system
stream in order to lose as few frames as possible and minimize the chance of missing a readable traffic sign. In this paper we show a sign detection system for grayscale images based on a two-stage process: A rapid shape prefiltering, that relies on a new descriptor coined as Local Contour Patterns, rejects most of the image subwindows and preclassifies the rest as one of the three main sign types. Then, a sign-dependent AdaBoost-based cascade detector that makes use of a new set of simpler texture features, coined as Quantum Features, scans the pre-fetched subwindows to fine tune candidate traffic signs. The analysis of this detector over hundreds of video sequences which were captured with a car-mounted 752x480 grayscale camera and provided by the Galician Automotive Technology Center (CTAG) shows a very good behavior for multiclass traffic sign detection running at 14 frames/sec on a 2.8 GHz processor.
Automated Traffic Sign Detection for Modern Driver Assistance Systems
2010
SUMMARY Modern Driver Assistance Systems (DAS) are required to assist, guide, and control vehicles on highways and city streets based on GPS, INS and map matching. They play an important role in the navigation of modern vehicles. Although a GPS-navigation system can be updated in view of the modifications of the roads, it does not include exhaustive information about the
Road Markings and Signs in Road Safety
Encyclopedia
Due to the dynamic nature and complexity of road traffic, road safety is one of the most demanding social challenges. Therefore, contemporary road safety strategies incorporate a multidisciplinary and comprehensive approaches to address this problem and improve the safety of each individual element, i.e., the human, vehicle, and road. Traffic control devices are an important part of road infrastructure, among which road markings and road signs play a significant role. In general, road markings and signs represent basic means of communication between the road authorities and road users and, as such, provide road users with necessary information about the rules, warnings, obligations, and other information related to the upcoming situations and road alignment. The aim of this entry is to briefly present the main functions and characteristics of road markings and signs, and their role in road safety. In addition, practical issues and future trends and directions regarding road markings...
2020
In the era of automatic driving technology to maneuver on the far side of the validation stage and into absolute automatic driving, it’s vital to check the security of the automatic driving system [1]. In this paper a completely unique approach of investigating lanes is described. The projected dimension of lanes may be measured exactly by a way of lane detection algorithmic program to find the corresponding position and options of lane markings. Vision systems square measure wide employed in autonomous vehicle systems because of the wealthy info that camera sensors offer of the encircling atmosphere. The proposed system [3] comes with directions obtained throughout human progression of the automobile and uses these to come up with automated labels for learning linguistics primarily based on the path detection model. Alongside, a camera’s correct angle and therefore the path dimension may be non-inheritable by the influential activity. The planned method uses the prediction of a pat...