Search

This paper presents the design of collision avoidance in heavy vehicles by using ultrasonic sensors. This project is about vehicle collision avoidance system for vehicles such as cars and trucks, and in particular, this research work utilizes the ultrasonic sensor. Further, the proposed research work utilizes the application of electronic systems embedded in automobile, which is mainly used to save the lives of people and reduce injuries when the accident occurs, and mainly, it reduces or avoids the vehicle accident disaster. This project concentrates on developing a vehicle collision avoidance system model of the rear-end vehicles that contain an LCD display, which will recognize the length between two vehicles that are moving in the same lane, same direction, and when anyone is in danger, a microcontroller will alert the driver. Sensing of object ahead and distance measurement is done by using an ultrasonic sensor.

Every new development in sensors and ultrasonic technologies has always been a bonus for electronics traveling aids (ETAs). This sets way to the development of smart vehicles for disabled people. These smart vehicles are used by physically disabled people. This electronic intelligent wheelchair is designed to help disabled people to move independently to any place without a caretaker. It consists of a smartphone app-based operation along with obstacle avoidance, fall detection and narrow way locomotion. An android application is used to control the wheelchair. This smart chair can function in full automatic mode. It uses GPS-guided system and magnetic compass to determine location and stores the location to return back to the location automatically. The fall detection system tilts the seat when it moves around any inclined plane and alerts the nearby caretaker with an SMS when a fall is detected. It has an intelligent collision avoidance system to avoid any type of obstacles including potholes and can move around narrow pathways and doors without being hit or bumped against any obstacle.

During winter season, in foggy environment, accidents are evident on national highways and many people succumb to death due to these accidents especially in Northern and Eastern region of India. To avoid such accidents, the authors have proposed a Raspberry Pi-based image processing approach to save the life of human being. An ultrasonic sensor detects the obstacle/vehicle and measures the distance. Once the obstacle is within the range, the edge detection algorithm processes the fog image and produces enhanced quality images displayed to the vehicle driver. The advantage of the proposed approach is that with the information achieved from ultrasonic sensor, the driver may have to apply the sudden brake to avoid accidents with the front-side vehicles but the backside vehicle may collide with his/her vehicle. But the enhanced image spatial information is useful to the driver in taking the decision whether to apply the brake or overtake the obstacle form left/right side to avoid accidents from backside vehicles also. Further, the high processing capacity of Raspberry Pi produces results within fraction of seconds (real time) to give sufficient amount of time to the driver to take appropriate decision to save life.

An autonomous mobile robot or Unmanned Ground Vehicle (UGV) is a vehicle that operates remotely, without human on-board. UGVs are widely used for mission-based applications that are often hazardous or/and inconvenient for humankind regardless of its sizes. As to enable its autonomous capability, UGVs often equipped with artificial eyes e.g. sensors and on-board camera to assist navigation during mission. In this experiment, we utilized a sweeping technique using ultrasonic sensor (HC-SR04) as the ‘eye’ of the mobile robot to map the obstacle around it using distance measurement. Meanwhile, an Arduino based controller is used to execute the avoidance algorithm. The ultrasonic sensor is programmed to sweep at six different angles to cover about 150° field of views. Path planning algorithm in this project provides the decision to avoid the obstacle and create temporary new waypoints within split seconds using decision table. We observed that the algorithm that uses decimal method is easy to implement and provides faster decision as compared to the binary method.

This chapter describes the basic principles of constructing an integrated flight safety system on the basis of the satellite-based landing system (SLS) and the collision avoidance system (CAS) using GNSS technologies. The proposed technical solutions are partially described in [1, 2, 3].

People detection has always posed a challenge in the image processing domain, and a lot of research has been going on to solve the problems posed due to the large number of variants present in detecting a human. In this paper, we introduce a system that integrates various components to perform pedestrian detection, safe distance calculation and a risk assessment for pedestrians, with a warning if the pedestrian is potentially in danger. The proposed system is for middle income cars, where a web camera is connected to a Raspberry Pi 3. The processor performs the calculations based on live webcam feed and gives an alert to the driver via an Android Application. This project uses a custom LBP Cascade classifier written in OpenCV, for pedestrian detection. A comparison of results between this custom classifier with the standard Haar classifier is shown here. This system is tested on an Indian dataset collected by us and on the Penn-Fudan Database for Pedestrian Detection and Segmentation dataset for comparing the results.

The collision avoidance system is the present state-of-the-art hardware/software integration for preventing an impending collision. The developed algorithm functions in two stages. It first warns the driver and if the driver fails to respond in time, it applies the brakes automatically to avoid the collision or reduce its severity. This paper deals with the development of a suitable mathematical model for Collision Avoidance System. Analysis and Simulation of the mathematical model has been done in MATLAB®. Simulation studies with On–Off and Fuzzy Logic Controller are compared and usefulness of Fuzzy Inference System (FIS) has been established. With two fuzzy inputs namely (slip ratio and rate of change of slip ratio) and one output (fraction of Brake Pressure required), optimum braking force is achieved. An iterative method is used to optimize the FIS controller. A new definition of critical distance has also been developed for optimization of the assessment of critical distance.

In recent years, autonomous or unmanned ground vehicles (UGV) have become the prima focus of research in automotive industry and even in academic institutions. Advanced driver assistance systems technologies like lane keeping system (LKS), obstacle or collision avoidance system, lane departure warning system (LDW), automatic parking system have been thoroughly researched and are being practically implemented in most of the modern-day vehicles. According to recent report by Ministry of Road Transport and Highways (MoRTH), India, the number of accidents due to improper overtaking and jumping/changing lanes is a major concern, with manoeuvrability of the driver being the sole attribute. This paper focuses on control logic for safe navigation of vehicle before lane change manoeuvre is initiated in traffic environment. The simulations have been carried out to simulate the control logic and of subject vehicle merging into two vehicles (lead and lag) for a single lane change manoeuvre. The parameters such as position, speed and gap distance between the vehicles in the current and target lane are taken into consideration for controlling the vehicle manoeuvre to avoid collisions.

Objective: The train collision avoidance system (TCAS) is a synergic approach for intervention of train in danger zone using Internet of things. Methods: The proposed system surveillance the signal condition and observe the disobedience of the track signal. A sensor is placed beneath the track, which senses the pressure, temperature, altitude of the track. The presence of train is observed by heavy pressure, change in temperature, and altitude on the track. Eventually, the system notifies the intervention of train being in danger zone using Internet of things by ThingSpeak IoT platform. An alarm is given to the train side that blow through Beaglebone black using Wi-fi module and if locomotive pilot does not respond, then the train stops by controlling braking system. Findings: Track signal plays a paramount role in cognizance of train’s direction. The disobedience of signal results in collision, derailment, and conflict. It is mainly occurred due to human error or rigid climate conditions like fog, rain and affects thousands of lives. TCAS-IoT prevails the problem of overshooting the track signal and acknowledging the locomotive pilot about intervention of train in danger zone. Conclusion/Improvement: The proposed TCAS-IoT can avoid train collision and capable of taking action before collision or derailment of trains. It is a unique way to synthesize the intervention of train in danger zone and can save lot of precious lives.

Use of fuzzy controller offers the advantage of assimilating the human intelligence for nonlinear complex system like autonomous vehicle. In order to prevent rear end collision of vehicles travelling in the same direction, Forward collision avoidance system is introduced which uses automated throttle and brake adjustment. Occupant comfort and safety are used as performance measures for assessing the performance of the system. The performance of the system depends on the spacing policy which describes about the distance to be maintained between the vehicles (lead and host) travelling in the same lane and direction of travel with respect to the velocity of travel. This research work proposes a novel Human Behavioural Model to determine the spacing between the vehicles and a heuristic-based Fuzzy controller since it does not require a detailed mathematical model of the system. Test result shows that the controller with the proposed method has shown an improved performance over the other existing spacing policies.