SMART on-board multi-sensor obstacle detection system for improvement of rail transport safety

Author(s):  
Danijela Ristić-Durrant ◽  
Muhammad Abdul Haseeb ◽  
Milan Banić ◽  
Dušan Stamenković ◽  
Miloš Simonović ◽  
...  

This paper presents an on-board multi-sensor system which is able to detect obstacles and estimate their distances in railway scenes in different illumination conditions. The system was developed within the H2020 Shift2Rail project SMART (Smart Automation of Rail Transport) and aims at increasing the safety of rail transport by detecting obstacles on the rail tracks ahead of a moving train in order to reduce the number of collisions. The system hardware consists of cameras of different types integrated into a specially designed housing, mounted on the front of the train. Multiple vision sensors complement each other in order to handle different illumination and environmental conditions. The system software uses a novel machine learning-based method that is suited to a particular challenge of railway operations, the need for long-range obstacle detection and distance estimation. The development of this method used a long-range railway dataset, which was specifically generated for this project. Evaluation results of reliable obstacle detection in various environmental conditions using the SMART RGB camera in day light illumination conditions and using the SMART Night Vision sensor in poor (night) illumination conditions are presented. The results demonstrate both the potential of the on-board SMART obstacle detection system in the operational railway environment and the benefit of the use of different cameras to be more independent of light and environmental conditions.

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 474
Author(s):  
Elio Hajj Assaf ◽  
Cornelius von von Einem ◽  
Cesar Cadena ◽  
Roland Siegwart ◽  
Florian Tschopp

Increasing demand for rail transportation results transportation by rail, resulting in denser and more high-speed usage of the existing railway network, making makes new and more advanced vehicle safety systems necessary. Furthermore, high traveling speeds and the greatlarge weights of trains lead to long braking distances—all of which necessitates Long braking distances, due to high travelling speeds and the massive weight of trains, necessitate a Long-Range Obstacle Detection (LROD) system, capable of detecting humans and other objects more than 1000 m in advance. According to current research, only a few sensor modalities are capable of reaching this far and recording sufficiently accurate enoughdata to distinguish individual objects. The limitation of these sensors, such as a 1D-Light Detection and Ranging (LiDAR), is however a very narrow Field of View (FoV), making it necessary to use ahigh-precision means of orienting to target them at possible areas of interest. To close this research gap, this paper presents a novel approach to detecting railway obstacles by developinga high-precision pointing mechanism, for the use in a future novel railway obstacle detection system In this work such a high-precision pointing mechanism is developed, capable of targeting aiming a 1D-LiDAR at humans or objects at the required distance. This approach addresses To address the challenges of a low target pricelimited budget, restricted access to high-precision machinery and equipment as well as unique requirements of our target application., a novel pointing mechanism has been designed and developed. By combining established elements from 3D printers and Computer Numerical Control (CNC) machines with a double-hinged lever system, simple and cheaplow-cost components are capable of precisely orienting an arbitrary sensor platform. The system’s actual pointing accuracy has been evaluated using a controlled, in-door, long-range experiment. The device was able to demonstrate a precision of 6.179 mdeg, which is at the limit of the measurable precision of the designed experiment.


2021 ◽  
Vol 2107 (1) ◽  
pp. 012030
Author(s):  
F S Kamaruddin ◽  
N H Mahmood ◽  
M A Abdul Razak ◽  
N A Zakaria

Abstract Visually impaired people usually have a lot of difficulties involved in interacting with their environment. Physical movement is a major challenge for them, because it can be tricky to make a distinction about where they are and how they can move from one place to another. In this project, smart assistive shoes with Internet of Things (IoT) implementation is designed. These shoes are equipped with ultrasonic sensors and vibration motors that can warn users about obstacles. Next, the IoT system is implemented using Adafruit IO and If This, Then That (IFTTT) to transfer data between Google Assistant and buzzer for shoes position finder purposes. NodeMCU allows the buzzer on shoes to be controlled by the Internet using its WiFi module which is connected to the mobile phone hotspots. As a result, shoes with an obstacle detection system which can detect obstacles within 20 cm distance and shoes position finder using Google Assistant are designed. In conclusion, hopefully these shoes will become one of the alternatives to aid the independent movement of the visually impaired people in the future.


Author(s):  
Jawad N. Yasin ◽  
Sherif A. S. Mohamed ◽  
Mohammad-hashem Haghbayan ◽  
Jukka Heikkonen ◽  
Hannu Tenhunen ◽  
...  

The world has increased its demand for assistive technology (AT). There are a lot of researches and developments going on with respect to AT. Among the AT devices which are being developed, the need for a reliable and less expensive device which serves as an assistance for a visually challenged person is in serious demand all around the world. We, therefore, intend to provide a solution for this by constructing a device that has the capability to detect the obstacles within a given range for a visually challenged person and alerting the person about the obstacles. This involves various components like a camera for image detection, an ultrasonic distance sensor for distance estimation and a vibration motor which works on the principle of Haptic feedback and rotates with varied intensities depending on how far the obstacle is from the user. This paper presents a model which is a part of the footwear of the user and hence, no additional device is required to hold onto for assistance. The model involves the use of a microcontroller, a camera, to dynamically perceive the obstacles and a haptic feedback system to alert the person about the same. The camera dynamically acquires the real time video footage which is further processed by the microcontroller to detect the obstacles. Simultaneously, one more algorithm is being executed to estimate the distance with the help of an ultrasonic distance sensor. Depending on the distance, the frequency of the vibration motor, which acts as the output for notifying the user about the obstacle, is varied (haptic feedback). With this system, a visually challenged person will be able to avoid the obstacles successfully without the use of any additional device.


Sign in / Sign up

Export Citation Format

Share Document