A Comprehensive Validation Method with Surface-Surface Comparison for Vehicle Safety Applications

2017 ◽  
Vol 5 (1) ◽  
pp. 39-46 ◽  
Author(s):  
Junqi Yang ◽  
Zhenfei Zhan ◽  
Ling Zheng ◽  
Gang Guo ◽  
Changsheng Wang
Keyword(s):  
Vehicle Safety ◽  
Validation Method ◽  
Safety Applications ◽  
Surface Comparison

The Influence of Future Vehicle Safety Network Impact on Traffic Flow

2014 ◽  
Vol 505-506 ◽  
pp. 985-989
Author(s):  
Jian Qun Wang ◽  
Xu Dong Li ◽  
Ya Fei Xiong
Keyword(s):  
Traffic Flow ◽  
High Speed ◽  
Rapid Development ◽  
Vehicle Safety ◽  
Navigation Systems ◽  
The Future ◽  
Network Safety ◽  
On The Road ◽  
Safety Applications ◽  
Vehicle Network

With the rapid development of high-speed mobile networks, the mobile applications related to vehicle safety, navigation systems are increasingly present in our lives, it is more and more easy for the driver to understand the situation on the road ahead, and this kind of change will greatly affect future traffic conditions. This article uses cellular automaton to simulate basic road sections, considering two modes of vehicle network safety applications may affect the future traffic flow, through the simulation, analysis the basic traffic flow data, conclude how the future vehicle network safety applications impact on traffic flow.

A Comprehensive Metric for Comparing Time Histories in Validation of Simulation Models With Emphasis on Vehicle Safety Applications

2008 ◽  
Author(s):  
H. Sarin ◽  
M. Kokkolaras ◽  
G. Hulbert ◽  
P. Papalambros ◽  
S. Barbat ◽  
...  
Keyword(s):  
Time History ◽  
Simulation Models ◽  
Experimental Tests ◽  
Vehicle Safety ◽  
Subject Matter Experts ◽  
Time Warping ◽  
Time Histories ◽  
Dynamic Time ◽  
Safety Considerations ◽  
Safety Applications

Computer modeling and simulation are the cornerstones of product design and development in the automotive industry. Computer-aided engineering tools have improved to the extent that virtual testing may lead to significant reduction in prototype building and testing of vehicle designs. In order to make this a reality, we need to assess our confidence in the predictive capabilities of simulation models. As a first step in this direction, this paper deals with developing a metric to compare time histories that are outputs of simulation models to time histories from experimental tests with emphasis on vehicle safety applications. We focus on quantifying discrepancy between time histories as the latter constitute the predominant form of responses of interest in vehicle safety considerations. First we evaluate popular measures used to quantify discrepancy between time histories in fields such as statistics, computational mechanics, signal processing, and data mining. Then we propose a structured combination of some of these measures and define a comprehensive metric that encapsulates the important aspects of time history comparison. The new metric classifies error components associated with three physically meaningful characteristics (phase, magnitude and topology), and utilizes norms, cross-correlation measures and algorithms such as dynamic time warping to quantify discrepancies. Two case studies demonstrate that the proposed metric seems to be more consistent than existing metrics. It is also shown how the metric can be used in conjunction with ratings from subject matter experts to build regression-based validation models.

scholarly journals IMPROVEMENT OF ROAD SAFETY USING PASSIVE AND ACTIVE INTELLIGENT VEHICLE SAFETY SYSTEMS

Transport ◽  
2007 ◽  
Vol 22 (4) ◽  
pp. 284-289 ◽  
Author(s):  
Aldona Jarašūnienė ◽  
Gražvydas Jakubauskas
Keyword(s):  
Road Safety ◽  
White Paper ◽  
Transport Systems ◽  
Vehicle Safety ◽  
Intelligent Vehicle ◽  
Intelligent Transport Systems ◽  
Intelligent Transport ◽  
Mode Of Transport ◽  
Safety Systems ◽  
Safety Applications

Following the measures foreseen in the Transport White Paper 2001, situation of road safety has improved. Road fatalities have declined by more than 17 % since 2001 in the EU. However, with around 41 600 deaths and more than 1.7 million injured in 2005, road remains the least safe mode of transport and objectives to halve the number of fatalities on road by 2010 is most likely not feasible to achieve. Therefore a need for the intelligent vehicle safety systems, that enable to raise the level of road safety, is much higher than ever before. The Intelligent Vehicle Safety Systems ensure a superior safety on road would it be vehicle‐based or infrastructure‐related systems. These can be divided into passive and active safety applications where the former help people stay alive and uninjured in a crash, while the latter help drivers to avoid accidents. Some of the most promising (e‐call) and the most used (ABS, ESP) systems are analised more specifically in the paper. Possible solutions to deploying intelligent transport systems in Lithuania are also introduced.

Comparing Time Histories for Validation of Simulation Models: Error Measures and Metrics

2010 ◽  
Vol 132 (6) ◽  
Author(s):  
H. Sarin ◽  
M. Kokkolaras ◽  
G. Hulbert ◽  
P. Papalambros ◽  
S. Barbat ◽  
...  
Keyword(s):  
Time History ◽  
Simulation Models ◽  
Experimental Tests ◽  
Vehicle Safety ◽  
Time Warping ◽  
Error Measures ◽  
Time Histories ◽  
Dynamic Time ◽  
Safety Considerations ◽  
Safety Applications

Computer modeling and simulation are the cornerstones of product design and development in the automotive industry. Computer-aided engineering tools have improved to the extent that virtual testing may lead to significant reduction in prototype building and testing of vehicle designs. In order to make this a reality, we need to assess our confidence in the predictive capabilities of simulation models. As a first step in this direction, this paper deals with developing measures and a metric to compare time histories obtained from simulation model outputs and experimental tests. The focus of the work is on vehicle safety applications. We restrict attention to quantifying discrepancy between time histories as the latter constitute the predominant form of responses of interest in vehicle safety considerations. First, we evaluate popular measures used to quantify discrepancy between time histories in fields such as statistics, computational mechanics, signal processing, and data mining. Three independent error measures are proposed for vehicle safety applications, associated with three physically meaningful characteristics (phase, magnitude, and slope), which utilize norms, cross-correlation measures, and algorithms such as dynamic time warping to quantify discrepancies. A combined use of these three measures can serve as a metric that encapsulates the important aspects of time history comparison. It is also shown how these measures can be used in conjunction with ratings from subject matter experts to build regression-based validation metrics.

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