Browse Topic: Crash prevention

Items (92)
Integrating 3D point cloud and image fusion into flying car detection systems is essential for enhancing both safety and operational efficiency. Accurate environmental mapping and obstacle detection enable flying cars to optimize flight paths, mitigate collision risks, and perform effectively in diverse and challenging conditions. The AutoAlignV2 paradigm recently introduced a learnable schema that unifies these data formats for 3D object detection. However, the computational expense of the dynamic attention alignment mechanism poses a significant challenge. To address this, we propose a Lightweight Cross-modal Feature Dynamic Aggregation Module, which utilizes a model-driven feature alignment strategy. This module dynamically realigns heterogeneous features and selectively emphasizes salient aspects within both point cloud and image datasets, enhancing the differentiation between objects and the background and improving detection accuracy. Additionally, we introduce the Lightweight
Feng, XiaoyuZhang, RenhangChu, ZhengWei, LinaBian, ChenDuan, Linshuai
ABSTRACT Many rollover prevention algorithms rely on vehicle models which are difficult to develop and require extensive knowledge of the vehicle. The Zero-Moment Point (ZMP) combines a simple vehicle model with IMU-only sensor measurements. When used in conjunction with haptic feedback, ground vehicle rollover can be prevented. This paper investigates IMU grade requirements for an accurate rollover prediction. This paper also discusses a haptic feedback design that delivers operator alerts to prevent rollover. An experiment was conducted using a Gazebo simulation to assess the capabilities of the ZMP method to predict vehicle wheel lift-off and demonstrate the potential for haptic communication of the ZMP index to prevent rollover. Citation: K. Steadman, C. Stubbs, A. Baskaran, C. G. Rose, D. Bevly, “Teleoperated Ground Vehicle Rollover Prevention via Haptic Feedback of the Zero-Moment Point Index,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium
Steadman, KathleenStubbs, ChandlerBaskaran, AvinashRose, Chad G.Bevly, David
ABSTRACT As unmanned ground vehicle technology matures and autonomous platforms become more common, such platforms will invariably be in close proximity to one another both in formation and independently. With an increasingly crowded field, the risk of collisions between these platforms grows, and with it the need for path deconfliction. This paper presents two complementary technological developments to this end: a pipeline for affirmatively identifying and classifying dynamic objects, e.g., vehicles or pedestrians; and a pipeline for preventing collisions with such objects. The efficacy of these techniques is demonstrated in simulation, and validation on robotic platforms will be undertaken in the near future. Citation: Matthew Grogan, “Dynamic Object Collision Avoidance for Autonomous Multi-Vehicle Systems in the Robotic Technology Kernel”, In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 13-15, 2019
Grogan, Matthew
Background: Road accident severity estimation is a critical aspect of road safety analysis and traffic management. Accurate severity estimation contributes to the formulation of effective road safety policies. Knowledge of the potential consequences of certain behaviors or conditions can contribute to safer driving practices. Identifying patterns of high-severity accidents allows for targeted improvements in terms of overall road safety. Objective: This study focuses on analyzing road accidents by utilizing real data, i.e., US road accidents open database called “CRSS.” It employs advanced machine learning models such as boosting algorithms such as LGBM, XGBoost, and CatBoost to predict accident severity classification based on various parameters. The study also aims to contribute to road safety by providing predictive insights for stakeholders, functional safety engineering community, and policymakers using KABCO classification systems. The article includes sections covering
Babaev, IslamMozolin, IgorGarikapati, Divya
Automatic emergency braking (AEB) systems play a crucial role in enhancing vehicular safety. Current research predominantly focuses on the longitudinal dynamics of vehicles, utilizing various control algorithms to improve braking effectiveness. However, there has been limited exploration into utilizing wheel deflection as a method to further enhance emergency braking performance. This study aims to contribute by proposing an advanced enhancement of the AEB system through coordinated wheel deflection strategies. In an emergency situation, when the speed of AEB-equipped vehicle drops to the set threshold due to wheel braking, the innovative control system will activate. The vehicle’s coaxial wheels will then execute a counter-deflection maneuver to maximize friction between the tires and the road surface. As a result, this approach reduces braking distance, thereby enhancing vehicle safety. The effectiveness of the proposed control algorithm is validated through combined simulation using
Lai, FeiXiao, HaoHuang, Chaoqun
In the context of vehicular safety and performance, brake pads represent a critical component, ensuring controlled driving and accident prevention. These pads consist of friction materials that naturally degrade with usage, potentially leading to safety issues like delayed braking response and NVH disturbances. Unfortunately, assessing brake pad wear remains challenging for vehicle owners, as these components are typically inaccessible from the outside. Moreover, Indian OEMs have not yet integrated brake pad life estimation features. This research introduces a hybrid machine learning approach for predicting brake pad remaining useful life, comprising three modules: a weight module, utilizing mathematical formulations based on longitudinal vehicle dynamics to estimate vehicle weight necessary for calculating braking kinetic energy dissipation; and temperature and wear modules, employing deep neural networks for predictive modeling. Notably, the model’s training leverages rig-level data
Iqbal, ShoaibBhambri, Mihirlahase, Rahul
Finding edge hazardous scenarios which appear very infrequently in the dataset than common hazardous scenarios is essential for implementing scenario-based testing of autonomous driving systems(ADs). However, it is difficult to evaluate the rarity of dynamic scenarios with huge scenario space high-dimensional time series, making it difficult to search for edge hazardous scenarios quickly. To solve this problem, this paper proposes a Semi-supervised anomaly detection method combining MiniRocket and DAGMM(Semi-MiniRocket-GMM, SRG), which treats edge hazardous scenarios as anomalous samples of common hazardous scenarios. SRG uses a small number of samples of common hazardous scenarios to guide interpretable feature extraction and clustering of a large amount of high-dimensional unlabeled temporal data and finds rarer edge hazardous scenarios based on anomaly evaluation to improve the coverage of test scenarios. The method is validated in the open-source natural driving dataset HighD
Li, MengyuLi, FangGuo, ZihanWang, Lifang
Provizio promises its 5D Perception stack can safely compete with expensive lidar sensors at a fraction of the cost. “Safety first” is more than a catchphrase. For sensing company Provizio, it's the only way the transportation industry should introduce autonomous vehicles. In Provizio's view, using AV building blocks - technology such as automatic emergency braking and lane-keep assist - can be valuable in ADAS systems, but they should not be used to drive vehicles until the perception problem has been solved. “It's not that we're skeptical about autonomous driving, it's just that we strongly believe that the industry has taken this wrong path,” Dane Mitrev, machine learning engineer at Provizio, told SAE Media at September 2023's AutoSens Brussels conference. “The industry has looked at things the other way around. They tried to solve autonomy first, without looking at accident prevention and simpler ADAS systems. We are building a perception technology which will first eliminate road
Blanco, Sebastian
The key issues of automatic emergency braking (AEB) control algorithm are when and how to brake. This article proposes an AEB control algorithm that integrates risk perception (RP) and emergency braking characteristics of professional drivers for rear-end collision avoidance. Using the formulated RP by time to collision (TTC) and time headway (THW), the brake trigger time can be determined. Based on the professional driver fitting (PDF) characteristic, the brake pattern can be developed. Through MATLAB/Simulink simulation platform, the European New Car Assessment Programme (Euro-NCAP) test scenarios are used to verify the proposed control algorithm. The simulation results show that compared with the TTC control algorithm, PDF control algorithm, and the integrated PDF and TTC control algorithm, the proposed integrated PDF and RP control algorithm has the best performance, which can not only ensure safety and brake comfort, but also improve the road resource utilization rate
Lai, FeiHuang, ChaoqunJiang, Chengyue
The use of personal light electric vehicles (PLEVs), such as electric scooters, has rapidly increased in recent years. However, their widespread use has raised concerns about rider safety due to their vulnerability in shared traffic spaces. To address this issue, this paper presents a radar-based rider assistance system aimed at enhancing the safety of PLEV riders. The system consists of an adaptive feedback system and a single-channel anti-lock braking system (ABS). The adaptive feedback system uses multiple-input multiple-output (MIMO) radar sensors to detect nearby objects and provide real-time warnings to the rider through haptic, visual, and acoustic signals. The system takes into account traffic density and uses online data to warn about obscured objects, thereby improving the rider’s situational awareness. Results from testing the feedback system show that it effectively detects potential collisions and provides warning signals, reducing the risk of accidents. The ABS is
Pyschny, JanBerger, FelixRothen, SamuelDenker, JoachimFrantzen, MichaelRoder, FelixKneiphof, Simon
In order to reduce collision at a 90-degree intersection, an automatic emergency collision avoidance control method for intelligent vehicles based on vehicle-to-everything (V2X) technology is proposed. Most of the existing automatic emergency braking (AEB) control algorithms are designed for a single high-friction road with reference to the European New Car Assessment Programme (Euro NCAP) evaluation procedures, and they do not consider changes in road friction. Thus, it may be difficult to avoid collision successfully on a low-friction road. Although some studies have considered the variation of road friction, they are only applicable to straight-line rear-end collisions and cannot be directly applied to intersections. In addition, most studies regard the vehicle only as a particle, ignoring the actual dynamic characteristics of the vehicle. The main contribution of this article is to present an AEB control strategy by V2X technology, which can make the intelligent vehicle avoid
Lai, FeiYang, HuiHuang, Chaoqun
Volvo calls its all-new EX90 SUV the safest and most technically adept model in the company's 95-year history, which includes such achievements as the world's first three-point automotive seat belt in 1959. Even before this luxury EV logs its first mile on global roads that take more than 1 million human lives every year, Volvo asserts the EX90 will eliminate up to one in five serious injury accidents, and one in 10 accidents overall. That claim is based not on fuzzy math, said Lotta Jakobsson, a 33-year company veteran and specialist in injury protection, but on Volvo's industry-unique accident database that's been a wellspring of company safety innovations since the 1970s
Ulrich, Lawrence
The Aft Collision Assist (ACA) is an Advanced Driver Assistance System (ADAS) that is added to a vehicle and integrates with the native systems of that vehicle. The ACA is used to monitor and reengage a distracted driver of an approaching vehicle that the ACA system calculates will imminently rear-end the host vehicle. This work provides a brief overview of existing ADAS that perform similar functions, the regulatory statutes and requirements that impact the ACA functionality, and Model-Based System Engineering (MBSE) model diagrams of the ACA. The MBSE model diagrams presented are State Machine, Conceptual Data Model, Use Case, System Requirements, and Regulatory Requirements for the entire ACA system. The MBSE models and regulatory constraints presented within are used to refine and specify the ACA method of attracting a distracted driver’s attention
Rictor, AndrewChandrasekar, Chandra V.
In the intelligent transportation roadside object detection scene, due to the limited computing power of edge computing equipment, it is difficult to deploy large and complex object detection models, at the same time, most of detection models can not give consideration to precision and real-time. The complex road environment requires the model to have higher detection precision and faster detection speed. To solve this problem, an improved lightweight object detection model based on YOLOv4 is proposed(STDC_YOLO). The proposed model uses short-time dense network structure (STDC) to replace cross stage partial model structure (CSP), employs multi-scale feature fusion module which combines low-level feature and high-level feature to enrich feature information. In addition, the proposed STDC_YOLO employs re-parameterized VGG block (RepVGG) to improved parameter efficiency, thereby improving the inference speed. In order to improve the positioning precision of the predication bounding box
Yang, ZheWang, DengjiangLi, RuiWang, YajunMa, GangMa, Bing
Recent researches in autonomous driving mainly consider the uncertainty in perception and prediction modules for safety enhancement. However, obstacles which block the field-of-view (FOV) of sensors could generate blind areas and leaves environmental uncertainty a remaining challenge for autonomous vehicles. Current solutions mainly rely on passive obstacles avoidance in path planning instead of active perception to deal with unexplored high-risky areas. In view of the problem, this paper introduces the concept of information entropy, which quantifies uncertain information in the blind area, into the motion planning module of autonomous vehicles. Based on model predictive control (MPC) scheme, the proposed algorithm can plan collision-free trajectories while actively explore unknown areas to minimize environmental uncertainty. Simulation results under various challenging scenarios demonstrate the improvement in safety and comfort with the proposed perception-aware planning scheme
Chen, ZhanXiong, LuTang, Chen
Multi-sensor fusion strategies have gradually become a consensus in autonomous driving research. Among them, radar-camera fusion has attracted wide attention for its improvement on the dimension and accuracy of perception at a lower cost, however, the processing and association of radar and camera data has become an obstacle to related research. Our approach is to build a concise framework for camera and radar detection and data association: for visual object detection, the state-of-the-art YOLOv5 algorithm is further improved and works as the image detector, and before the fusion process, the raw radar reflection data is projected onto image plane and hierarchically clustered, then the projected radar echoes and image detection results are matched based on the Hungarian algorithm. Thus, the category of objects and their corresponding distance and speed information can be obtained, providing reliable input for subsequent object tracking task. Results shows that the fusion method
He, YingjieZhao, JianLyu, NanaLi, LinhuiLiu, Pengbo
Identifying typical pre-crash scenarios can assist in determining potentially dangerous road traffic situations, and provide a basis for further expansions to vehicle safety test scenarios. Firstly, for the purpose of identifying the typical pre-crash scenarios of road traffic in China, 5983 accident cases in the China Traffic Accident In-depth Study (CIDAS) Database were screened. Next, the following variables have been identified as characteristic variables of scenario identification: personnel injury, the type of road, the form of accident, accident time, the cause of the accident (including human factors, vehicle factors, and environmental factors), and the casualties in accident. Then, the correlation analysis was conducted using the Pearson correlation coefficient for the selected variables. After that, the SSE (sum of squared errors) index was used to determine the number of cluster center. Finally, we described five typical Chinese road traffic pre-crash scenarios utilizing the
Lin, MiaoLi, XiaohuWang, PengZhu, Tong
The Autonomous emergency braking system (AEB) has been widely equipped in the design and manufacture of vehicles as an active safety system for preventing rear-end collisions. It has shown great safety potential in preventing collisions and reducing collision injuries. However, there are differences in the response characteristics of drivers in emergency scenarios due to individual differences and driving habits. The impact of different driver types on the safety performance of AEB systems has not been evaluated. In this study, the typical driver response model was constructed by selecting driver response features representing alertness and braking. The AEB algorithm of distance and situation awareness was combined with the kinematic of vehicle before the collision to construct a simulation case based on the rear-end collisions in the China in-depth accident study database (CIDAS). The collision avoidance percentage, the impact speed, and the minimum relative distance were used as
Wei, TianzhengKang, KaiZhu, TongLiu, Haoxue
Several accidents on the highways are due to strong crosswind conditions. The effectiveness of wind-break fences on a sudden strong crosswind has been investigated for a generic truck model. Two wind-break fences have been designed for stretching the rise time of aerodynamic loads. The dynamic response of the vehicle to crosswind while exiting a tunnel is simulated. Moving mesh CFD simulations and vehicle dynamics simulations are used to assess the effectiveness of the fences based on a safety index and the maximum lateral displacement of the vehicle. The proposed fences mitigate sudden aerodynamic loads and avoid the rollover of the vehicle
Semeraro, Francesco FabioCioffi, AntonioPellegrino, EmanueleSchito, PaoloVignati, Michele
Collisions between opened doors and approaching vehicles such as bicycles are common occurrences in urban areas around the world. For example, in Chicago, 20% of all bicycle accidents involve collisions with doors, which occur over 300 times a year. In addition, there are concerns about a further rise in accidents due to the recent increase in home delivery services and bicycle commuting during the COVID-19 pandemic. Some advanced driver assistance systems (ADAS) that are designed to help prevent this type of accident have already been introduced. These systems detect approaching vehicles with sensors and alert the person opening the door via LED lights or a buzzer when the door is opened. The occupant must understand the meaning of the alert and stop opening the door quickly to prevent an accident. However, if the occupant is an elderly person or a child, it is difficult to stop opening the door quickly. One possible countermeasure for this issue is an ADAS that completely locks the
Takeuchi, KojiIshida, Masaho
This paper will describe the development of a load estimation algorithm that is used to estimate the load parameters necessary to detect a vehicle’s proximity to rollover. When operating a vehicle near its handling limits or with large loads, vehicle rollover must be considered for safe operation. Vehicle mass and center of gravity (CG) height play a large role in a vehicle’s rollover propensity. Cargo and passenger vehicles operate under a range of load configurations; therefore, changes in load should be estimated. Researchers have often developed load estimation and rollover detection algorithms separately. This paper will develop a load estimation algorithm and use the load estimates and vehicle states to detect rollover. The load estimation algorithm uses total least squares and is broken into two parts. First, mass is estimated based on a “full-car” dynamic ride model. Next, the CG height and inertia are estimated using the previously estimated mass and a dynamic roll model
Hilyer, TrentonBevly, David M.
According to the statistics of National Highway Traffic Safety Administration, driver’s cognitive distraction, which is usually caused by drivers using mobile phones, has become one of the main causes of traffic accidents. To solve this problem and guarantee the safety of man-vehicle-road system, the most critical work is to improve the accuracy of driver’s cognitive state detection. In this paper, a novel driver’s cognitive state detecting method based on LightGBM (Light Gradient Boosting Machine) is proposed. Firstly, cognitive distraction experiments of making calls are carried out on a driving simulator to collect vehicle states, eye tracking and EEG (electron encephalogram) data simultaneously and feature extraction is conducted. Then a classifier considering road and individual characteristics used for detecting cognitive states is trained based on LightGBM algorithm, with 3 predefined cognitive states including concentration, ordinary distraction and extreme distraction. Finally
Li, JingyuanLiu, YahuiJi, XuewuTao, Shuxin
Vehicle to Everything (V2X) allows vehicles, pedestrians, and infrastructure to share information for the purpose of enhancing road safety, improving traffic conditions, and lowering transporation costs. Although V2X messages are authenticated, their content is not validated. Sensor errors or adversarial attacks can cause messages to be perturbed increasing the likelihood of traffic jams, compromising the decision process of other vehicles, and provoking fatal crashes. In this article, we introduce V2X Core Anomaly Detection System (VCADS), a system based on the theory presented in [1] and built for the fields provided in the periodic messages shared across vehicles (i.e., Basic Safety Messages, BSMs). VCADS uses physics-based models to constrain the values in each field and detect anomalies by finding the numerical difference between a field and and its derivation using orthogonal values. VCADS evaluation is performed with four real V2X field testing datasets and a suite of attack
Andrade Salazar, Alejandro AntonioMcDaniel, Patrick DrewSheatsley, RyanPetit, Jonathan
Due to their large volume structure, when a heavy vehicle encounters sudden road conditions, emergency turns, or lane changes, it is very easy for vehicle rollover accidents to occur; however, well-designed suspension systems can greatly reduce vehicle rollover occurrence. In this article, a novel semi-active suspension adaptive control based on AdaBoost algorithm is proposed to effectively improve the vehicle rollover stability under dangerous working conditions. This research first established a vehicle rollover warning model based on the AdaBoost algorithm. Meanwhile, the approximate skyhook damping suspension model is established as the reference model of the semi-active suspension. Furthermore, the model reference adaptive control (MRAC) system is established based on Lyapunov stability theory, and the adaptive controller is designed. Finally, on the same road condition, the rollover warning control simulations are carried out under the following conditions: the 180-degree step
Tianjun, ZhuWan, HegaoWang, ZhenfengWei, MaXu, XuejiaoZhiliang, ZouSanmiao, Du
This paper intends to present a novel optimal trajectory planning method for obstacle avoidance on highways. Firstly, a mapping from the road Cartesian coordinate system to the road Frenet-based coordinate system is built, and the path lateral offset in the road Frenet-based coordinate system is represented by a function of quintic polynomial respecting the traveled distance along the road centerline. With different terminal conditions regarding its position, heading and curvature of the endpoint, and together with initial conditions of the starting point, the path planner generates a bunch of candidate paths via solving nonlinear equation sets numerically. A path selecting mechanism is further built which considers a normalized weighted sum of the path length, curvature, consistency with the previous path, as well as the road hazard risk. The road hazard is composed of Gaussian-like functions both for the obstacle and road boundaries, which means, if one path is near the obstacle or
Cao, HaotianZhao, SongSong, XiaolinLi, Mingjun
With a path intrusion incident, it is almost always the case that the collision would have been avoided if the pedestrian had not run out, or if the vehicle on the minor road had stopped, or so on. However should the other party be thought to have been travelling at an excessive speed, often the reconstructionist is asked to make a calculation of what whether the collision would, at some alternative speed say equal to the speed limit, still have occurred. In that way causation is addressed. The paper distinguishes between those hazards which are distance limited and those which are time limited, giving definitions of the two types. Distance limited hazards are deterministic, but time limited hazards have a probabilistic basis. This difference has important implications for causation. For a hazard at a fixed distance, there is a well known formula for calculating whether the collision would have been avoided at a slower alternative speed. However a time limited hazard often has no clear
Searle, John
In recent years, the number of reported traffic accidents due to sudden deterioration in driver’s physical condition has been increasing, it is expected to develop a system that prevents accidents even if physical condition suddenly changes while driving, or reduces damage through vehicle body control. For this purpose, it is necessary to detect sudden changes of the driver’s physical condition, and research is being conducted widely. Among them, it is reported that some of such changes may appear in the heartbeat interval. In other words, by acquiring the driver’s heartbeat interval in real time, it may be possible to detect the sudden changes, and reduce traffic accident. Even if a traffic accident occurs, the damage can be reduced by emergency evacuation immediately after detecting sudden changes. Therefore, we focused on the technology to detect the heartbeat interval with 24GHz microwave Doppler radar, which can detect heartbeat non-contactly while maintaining the interior design
Tsuchiya, KentoMochizuki, KentaOhtsuki, TomoakiYamamoto, Kohei
This recommended practice provides common data output formats and definitions for a variety of data elements that may be useful for analyzing the performance of automated driving system (ADS) during an event that meets the trigger threshold criteria specified in this document. The document is intended to govern data element definitions, to provide a minimum data element set, and to specify a common ADS data logger record format as applicable for motor vehicle applications. The data elements defined in this document are unique to Levels 3, 4, or 5 ADS features, as defined by SAE J3016, and provide additional background of the events leading up to a crash or crash-like event. The data from sensors such as camera(s), LiDAR(s) etc. will provide information in the absence of a human driver. The data included in the ADS data logger is expected to be used in conjunction with the SAE J1698 EDR record and traditional accident reconstruction analysis. The event data recorder (EDR) and ADS data
Event Data Recorder Committee
The Insurance Institute for Highway Safety (IIHS) evaluates autonomous emergency braking (AEB) systems as part of its front crash prevention (FCP) ratings. To prepare the test vehicles' brakes, each vehicle must have 200 miles on the odometer and be subjected to the abbreviated brake burnish procedure of Federal Motor Vehicle Safety Standard (FMVSS) 126. Other organizations conducting AEB testing follow the more extensive burnishing procedure described in FMVSS 135; Light Vehicle Brake Systems. This study compares the effects on AEB performance of the two burnishing procedures using seven 2014 model year vehicles. Six of the vehicles achieved maximum AEB speed reductions after 60 or fewer FMVSS 135 stops. After braking performance stabilized, the Mercedes ML350, BMW 328i, and Volvo S80 showed increased speed reductions compared with stops using brand new brake components. The Acura RLX and Cadillac CTS showed no change in speed reductions, and the speed reductions of the Dodge Durango
Wilson, MylesAylor, DavidZuby, DavidNolan, Joseph
The turn signal is a vital safety feature that is not only required to be built in as standard equipment on all vehicles, but their use by the driver in everyday driving is required by law. Since not all drivers are diligent at properly actuating turn signals in every situation, the use of the turn signal is less than 100%. However, despite the fact that turn signals are a crash prevention feature, no known study relating to turn signal usage rates is available from the National Highway Traffic Safety Administration, nor from the Department of Transportation, nor from any University, nor from other private safety organizations. This paper summarizes a first-ever published comprehensive study related to turn signal usage rates by everyday drivers and summarizes it in a simple, yet highly accurate naturalistic observation format with the following basic premise: A vehicle is observed to be turning in a situation that is deemed by the observer to require a turn signal: was the turn signal
Ponziani, Richard
No bike can express what it actually feels. Talking bike indicates as and when changes occur in a bike that is unknown to the driver. So here we have attempted to indicate what actually bike feels in the dashboard using LEDs. It is necessary to keep the vehicle in proper condition for effective running, longer life and accident prevention. If the problem in a bike is not sensed well before, then efficient running is not possible. Hence vehicle condition monitoring system through dashboard is implemented which displays the exact condition of the vehicle. Different cheap sensors are developed and attached to different parts of the bike and its condition is indicated by LED in the dashboard. These cheap sensors can able to sense fuel level, Engine oil condition, tire pressure condition, chain tightness and battery condition. If this conditions are not measured in time then mileage of the vehicle will come low; emission problem will arise; prone to get accident as well as lower life of the
Martin, A. DanielPrakash, R.Raja, K. Thiruppathi
Although some form of turn signals have been on vehicles since shortly after the invention of the automobile, the advancements and improvements in control of turn signals has stagnated for the last 70 years. The Smart Turn Signal adds little or no cost to the vehicle, and is a significant safety improvement that effects all aspects of driving- cars or trucks, day or night, during all seasons, rain or shine or snow, north or south, east or west, male or female, young or old, driver or passenger or pedestrian, city or highway. Smart Turn Signals are a vital link towards the goal of an intelligent transportation system that not only ensures that drivers use turn signals at all turns, but assures that the turn signal is appropriately shut off after each turn or lane change. The Smart Turn Signal also serves to combat distracted driving as well as road rage. The proper use of the turn signal is more important today than when the first flashing turn signals were installed on cars in the late
Ponziani, Richard
The guidelines for operator and bystander protection in this recommended practice apply to towed, semimounted or mounted flail mowers and flail power rakes when powered by a propelling tractor or machine of at least 15 kw (20 hp), intended for marketing as industrial mowing equipment and designed for cutting grass and other growth in public use areas such as parks, cemeteries and along roadways and highways. The use of the word "industrial" is not to be confused with "in-plant industrial equipment". This document does not apply to: 1 Turf care equipment primarily designed for personal use, consumption or enjoyment of a consumer in or around a permanent or temporary household or residence. 2 Machines designed primarily for agricultural purposes but which may be used for industrial use. 3 Self powered or self propelled mowers or mowing machines. Where other standards are referenced, such reference applies only to the document identified, not revisions thereof
OPTC1, Personnel Protection (General)
Items per page:
1 – 50 of 92