A Driving Safety Evaluation Algorithm Based on TOPSIS Model of Game Theory Combination

2019 ◽  
pp. 756-768
Author(s):  
Zhenyu Wu ◽  
Guangda Chen ◽  
Jingjing Yao
Keyword(s):  
Game Theory ◽  
Safety Evaluation ◽  
Driving Safety ◽  
Evaluation Algorithm ◽  
Topsis Model ◽  
Theory Combination

scholarly journals A Novel Approach for Operating Speed Continuous Predication Based on Alignment Space Comprehensive Index

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Ying Yan ◽  
Gengping Li ◽  
Jinjun Tang ◽  
Zhongyin Guo
Keyword(s):  
Field Experiments ◽  
Prediction Models ◽  
Three Dimensional ◽  
Safety Evaluation ◽  
Driving Safety ◽  
Operating Speed ◽  
Passenger Cars ◽  
Comprehensive Index ◽  
Novel Approach ◽  
Lane Width

Operating speed is a critical indicator for road alignment consistency design and safety evaluation. Although extensive studies have been conducted on operating speed prediction, few models can finish practical continuous prediction at each point along alignment on multilane highways. This study proposes a novel method to estimate the operating speed for multilane highways in China from the aspect of the three-dimensional alignment combination. Operating speed data collected in field experiments on 304 different alignment combination sections are detected by means of Global Positioning System. First, the alignment comprehensive index (ACI) is designed and introduced to describe the function accounting for alignment continuity and driving safety. The variables used in ACI include horizontal curve radius, change rate of curvature, deflection angle of curve, grade, and lane width. Second, the influence range of front and rear alignment on speed is determined on the basis of drivers’ fixation range and dynamical properties of vehicles. Furthermore, a prediction model based on exponential relationships between road alignment and speeds is designed to predict the speed of passenger cars and trucks. Finally, three common criteria are utilized to evaluate the effectiveness of the prediction models. The results indicate that the prediction models outperform the other two operating speed models for their higher prediction accuracy.

scholarly journals Applying Heuristics to Generate Test Cases for Automated Driving Safety Evaluation

2021 ◽  
Vol 11 (21) ◽  
pp. 10166
Author(s):  
Leonard Stepien ◽  
Silvia Thal ◽  
Roman Henze ◽  
Hiroki Nakamura ◽  
Jacobo Antona-Makoshi ◽  
...  
Keyword(s):  
Safety Evaluation ◽  
Driving Safety ◽  
Test Case ◽  
Test Cases ◽  
Generation Process ◽  
Complex Environments ◽  
Automated Driving ◽  
Evaluation Approach ◽  
Naturalistic Driving ◽  
Real Traffic

Comprehensive safety evaluation methodologies for automated driving systems that account for the large complexity real traffic are currently being developed. This work adopts a scenario-based safety evaluation approach and aims at investigating an advanced methodology to generate test cases by applying heuristics to naturalistic driving data. The targeted requirements of the generated test cases are severity, exposure, and realism. The methodology starts with the extraction of scenarios from the data and their split in two subsets—containing the relatively more critical scenarios and, respectively, the normal driving scenarios. Each subset is analysed separately, in regard to the parameter value distributions and occurrence of dependencies. Subsequently, a heuristic search-based approach is applied to generate test cases. The resulting test cases clearly discriminate between safety critical and normal driving scenarios, with the latter covering a wider spectrum than the former. The verification of the generated test cases proves that the proposed methodology properly accounts for both severity and exposure in the test case generation process. Overall, the current study contributes to fill a gap concerning the specific applicable methodologies capable of accounting for both severity and exposure and calls for further research to prove its applicability in more complex environments and scenarios.

Fishing Vessel Safety Evaluation Algorithm Based on Cloud Model

2014 ◽  
Vol 644-650 ◽  
pp. 2194-2197
Author(s):  
Jie Yao ◽  
Zhao Lin Wu ◽  
Zhi Yuan Xu ◽  
Yu Qing Ren
Keyword(s):  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Cloud Model ◽  
Safety Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Fishing Vessel ◽  
Comprehensive Evaluation Method ◽  
Droplet Distribution ◽  
Fishing Vessels ◽  
Evaluation Algorithm

The safety evaluation of fishing vessels is a system and uncertain problem. A fishing vessel safety evaluation algorithm based on cloud model was proposed in this paper. Firstly, we established index system and weights by the AHP; Secondly, the cloud generator completed the conversion between qualitative and quantitative indicators; Thirdly, the evaluation cloud model was achieved by the comprehensive cloud algorithm; Finally, the forward cloud generator restored the droplet distribution. Compared with the fuzzy comprehensive evaluation method, the experimental results show that our work is effective and accurate.

scholarly journals Safety Evaluation of Hydraulic Steel Gate Based on TOPSIS Model

2021 ◽  
Vol 2029 (1) ◽  
pp. 012100
Author(s):  
Y.J Shi ◽  
Y.Y Shao ◽  
Z.M Zhang ◽  
Y Jiang ◽  
L Qi
Keyword(s):  
Safety Evaluation ◽  
Steel Gate ◽  
Topsis Model

scholarly journals A Maneuver Evaluation Algorithm for Lane-Change Assistance System

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 774
Author(s):  
Bohan Jiang ◽  
Xiaohui Li ◽  
Yujun Zeng ◽  
Daxue Liu
Keyword(s):  
Semantic Information ◽  
Decision Aids ◽  
Experimental Results ◽  
Driving Safety ◽  
Lane Change ◽  
Simulation Experiments ◽  
Evaluation Approach ◽  
Evaluation Algorithm ◽  
The Cost ◽  
Lane Keeping

This paper proposes a maneuver evaluation approach to enhance driving safety by providing decision aids. Based on the deliberative understanding of environmental semantic information, the proposed algorithm evaluates the risk of candidate driving maneuvers, including aggressive lane-change maneuver, passive lane-change maneuver, lane-change abort maneuver, and lane-keeping maneuver. The effectiveness of the proposed method is validated through various simulation experiments. The experimental results demonstrate that the proposed approach is capable of efficiently evaluating the feasibility and the cost of each candidate driving maneuver. The approach also provides suggestions on how to adjust the speed, and when to initiate a lane-change maneuver.

scholarly journals Research on Evaluation Model for Secondary Task Driving Safety Based on Driver Eye Movements

2014 ◽  
Vol 6 ◽  
pp. 624561 ◽  
Author(s):  
Lisheng Jin ◽  
Huacai Xian ◽  
Yuying Jiang ◽  
Qingning Niu ◽  
Meijiao Xu ◽  
...  
Keyword(s):  
Eye Movements ◽  
Secondary Task ◽  
Clustering Algorithm ◽  
Driving Simulator ◽  
Evaluation Model ◽  
Safety Evaluation ◽  
Evaluation Index System ◽  
Driving Safety ◽  
Significant Difference ◽  
Driving Conditions

This study was designed to gain insight into the influence of performing different types of secondary task while driving on driver eye movements and to build a safety evaluation model for secondary task driving. Eighteen young drivers were selected and completed the driving experiment on a driving simulator. Measures of fixations, saccades, and blinks were analyzed. Based on measures which had significant difference between the baseline and secondary tasks driving conditions, the evaluation index system was built. Method of principal component analysis (PCA) was applied to analyze evaluation indexes data in order to obtain the coefficient weights of indexes and build the safety evaluation model. Based on evaluation scores, the driving safety was grouped into five levels (very high, high, average, low, and very low) using K-means clustering algorithm. Results showed that secondary task driving severely distracts the driver and the evaluation model built in this study could estimate driving safety effectively under different driving conditions.

Lane Change Decision Analysis Based on Drivers' Perception-Judgment and Game Theory

2013 ◽  
Vol 361-363 ◽  
pp. 1875-1879 ◽  
Author(s):  
Jin Shuan Peng ◽  
Ying Shi Guo ◽  
Yi Ming Shao
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Nash Equilibrium ◽  
Equilibrium Solution ◽  
Information Source ◽  
Driving Safety ◽  
External Information ◽  
Lane Change ◽  
Safety Level ◽  
Lane Changing

To clearly understand the mechanism of drivers lane-changing decision, based on drivers perception of external information, integrated cognitive judgment and game theory, the decision-making model was established, then the structure and operating mechanism of the model were detailedly analyzed. By introducing game theory-related knowledge, the non-cooperative mixed strategy game between the object vehicle and the following vehicle in the target lane was further discussed. Then, the benefits and Nash equilibrium solution of the participants in the game were deeply researched. Analysis shows that lane-changing decision is composed of information perception and three judgment-decision processes, the factors which would affect decision-making level include information source characteristics, the ability of drivers perception and comprehensive cognitive judgment, driving behavior characteristics and so on. The Nash equilibrium solution of the lane change game is determined by driving safety level, journey time and importance degree of the revenues.

Congestion Control investigation into 5G V2V

2021 ◽  
Author(s):  
Houda CHIHI ◽  
Ridha Boualegue
Keyword(s):  
Game Theory ◽  
Congestion Control ◽  
Data Exchange ◽  
Driving Safety ◽  
Network Density ◽  
Traffic Density ◽  
Vehicular Communication ◽  
Continuous Increase ◽  
V2v Communication ◽  
The Difference

Abstract Congestion control is a hot research topic according to the continuous increase of traffic density together with great mobility of cars. In this context, in this survey we present an overview about the different vehicle to vehicle (V2V) communication enablers by describing the difference between them performing better driving assistance together with efficient congestion control ensuring driving safety. New radio (NR) 5G is the heuristic enabler which provides scalability and reliability towards vehicular communication. Indeed, NR 5G is the best solution supporing the great increase of network density. 5G technology is expected to allow much advanced services and application with a huge capacity of data exchange. Congestion occurance impacts the quality of service of vehicular network, for this accurate quantification is required. In our analysis we consider channel busy rate CBR as indicator of network density. Channel load control is mondatory to overcome traffic jam which could be highlighted by different metrics. The connectivity between cars is modeled with a game theory framework considering a non cooperative vehicular mobility. Each vehicle adjusts its transmitted power in dynamic way taking into account the traffic density measured by channel busy rate (CBR). Consequently, we follow a theoretical modeling to determine the efficient allocated power ensuring awareness messages exchange without saturating the communication channel under the respect of a fixed threshold. Therefore, channel saturation control is investigated following a theoretical analysis exploiting game theory under the assumption of a non cooperative strategy. Each vehicle acts as a player presenting a specific driving behavior different to the other cars participating into the same scenario. The optimization framework is about determining the optimal allocated power for congestion minimization.

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