Transport Ergonomics issues in a jet car crash

2009 ◽  
pp. 686-692
Keyword(s):  
2020 ◽  
Author(s):  
Aishani Mukerji ◽  
Rounak Chakraborty ◽  
Kalyan Chatterjee ◽  
Sayanti Banerjee
Keyword(s):  

Author(s):  
Naouress Fatfouta ◽  
Julie Stal-Le Cardinal ◽  
Christine Royer

AbstractCar crash simulation analysis is an important phase within the vehicle development. It intends to analyse the crashworthiness of the vehicle model and examine the level of passive security. However, this activity is not trivial because of the considerable collaboration within the project, the large amount of analysed and exchanged data and a high exigency. Consequently, a solution to assist, ease and reduce the time of the process is desired.To study the current practices followed in the car crash simulation analysis an empirical study has been conducted. This study has been applied within the simulation analysis team, in the development phase, within an automotive company. This paper describes a qualitative analysis of the industrial context and diagnoses the dysfunctions in the current practices. This paper also highlights the current challenges encountered in the car crash simulation analysis.


2020 ◽  
Vol 4 (3) ◽  
pp. 20 ◽  
Author(s):  
Giuseppe Ciaburro

Parking is a crucial element in urban mobility management. The availability of parking areas makes it easier to use a service, determining its success. Proper parking management allows economic operators located nearby to increase their business revenue. Underground parking areas during off-peak hours are uncrowded places, where user safety is guaranteed by company overseers. Due to the large size, ensuring adequate surveillance would require many operators to increase the costs of parking fees. To reduce costs, video surveillance systems are used, in which an operator monitors many areas. However, some activities are beyond the control of this technology. In this work, a procedure to identify sound events in an underground garage is developed. The aim of the work is to detect sounds identifying dangerous situations and to activate an automatic alert that draws the attention of surveillance in that area. To do this, the sounds of a parking sector were detected with the use of sound sensors. These sounds were analyzed by a sound detector based on convolutional neural networks. The procedure returned high accuracy in identifying a car crash in an underground parking area.


1998 ◽  
Vol 111 (4) ◽  
pp. 205-207 ◽  
Author(s):  
M. Augsburger ◽  
C. Giroud ◽  
L. Rivier ◽  
A. Tracqui ◽  
P. Mangin
Keyword(s):  

2020 ◽  
pp. 1-12
Author(s):  
Carl J. Wenning ◽  
Rebecca E. Vieyra
Keyword(s):  

Author(s):  
Zhi Xiao ◽  
Li Wang ◽  
Fuhao Mo ◽  
Siqi Zhao ◽  
Cuina Liu

With the rapid development of car crash sensing and identification technology, the application of pre-triggering airbag system is becoming an important option to improve vehicle safety. Thus, the present study aims to investigate the injury protection ability of pre-triggering airbag system and optimize its performance in frontal crashes regarding the key physical parameters. A driver restraint system model established and validated by National Crash Analysis Center was employed and validated for studying the injury protection ability of pre-triggering airbag system. Then, the influences of airbag triggering time, airbag volume scaling factor, inflator mass flow, and exhaust orifice size of pre-triggering airbag system on driver’s head and chest injuries were analyzed. Finally, the weighted injury criterion was selected as the evaluation index to optimize the pre-triggering airbag system. The results show the pre-triggering airbag should be designed with a larger airbag volume and inflator mass flow rate and smaller exhaust orifice. The optimized restraint system design presents a reduction of weighted injury criterion values in 100% and 40% overlapped frontal impacts reaching 25.63% and 42.23%, respectively.


Journalism ◽  
2017 ◽  
Vol 21 (7) ◽  
pp. 1007-1022
Author(s):  
Kate Willman

The subjects of the two texts analysed in this article are two highly significant recent historical events: the death of Lady Diana in a car crash after being chased by paparazzi on 31 August 1997 and the attacks on the World Trade Center in New York City on 11 September 2001, which are addressed by the Italian writer Beppe Sebaste and the French writer Frédéric Beigbeder, respectively. An analysis of each text shows that they not only examine the events in question through reportage, but they are also strongly personal and subjective. Both texts also put forward literary writers to help ‘read’ extensively mediated events, provoking reflection on how news travels and is mediated in increasingly immediate ways in today’s world, while also harking back to New Journalism. They could be called ‘unidentified narrative objects’, a label I borrow from the Italian writer Roberto Bui, alias Wu Ming 1, who has applied it to a corpus of recent Italian texts (including that of Sebaste), that combine modes of writing – such as journalism, history, detective fiction and life-writing – often blurring the boundaries between fiction and nonfiction, in order to more effectively draw their readers’ attention to the national and global issues they address. Here, I extend the term unidentified narrative objects beyond Italy’s borders to the work of Beigbeder and others, suggesting that such hybridity is connected to how we process the world around us today and a new iteration of literary journalism.


Author(s):  
Mr. Aniket Ashok Bhamani ◽  
Mr. Sanyam Sanjay Mehta

There are a lot of road accidents that occur due to drowsy driving. Drowsy driving is when the driver of a vehicle is found to be sleepy and probable to get into a car crash because of the same. Being drowsy might cause the driver to lose concentration from the road, and also reduce the reaction time. Statistics suggest how thousands of deaths and crashes happen every year due to it. Major victims of such crashes tend to be the commercial drivers who need to drive long distances overnight. Our project intends to propose a solution to this problem by providing an Internet of Things based approach. This approach monitors the driver’s face while he or she is driving the vehicle and in case if the driver is to be found falling asleep, an instant voice call is made to the driver’s registered phone number. Additionally, a text message is also sent to the driver’s emergency contact which will get him/her notified and provide the driver with quick assistance if needed. This approach is unique and different in its own way as it provides cross platform support and remote monitoring of the driver. Additionally, it also makes drowsy-detection ‘device independent’. It offers a simplified mechanism to derive real time accurate results and readings with reduced complexities. This project does have a lot of scope, especially considering that there is a lack of methodologies currently being implemented to prevent road accidents due to drowsy driving. KEYWORDS- Drowsy Driving, Monitoring, Machine Learning, Internet of Things, Remote, Algorithm, Eye Aspect Ratio, Python.


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