scholarly journals Analysis of Differences in ECG Characteristics for Different Types of Drivers under Anxiety

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yongqing Guo ◽  
Xiaoyuan Wang ◽  
Qing Xu ◽  
Quan Yuan ◽  
Chenglin Bai ◽  
...  
Keyword(s):  
Traffic Safety ◽  
Road Traffic ◽  
Warning System ◽  
Actual State ◽  
Ecg Signal ◽  
Test Analysis ◽  
Driving Experience ◽  
Road Traffic Safety ◽  
Different Types ◽  
Unpleasant Feeling

Anxiety is a complex emotion characterized by an unpleasant feeling of tension when people anticipate a threat or negative consequence. It is regarded as a comprehensive reflection of human thought processes, physiological arousal, and external stimuli. The actual state of emotion can be represented objectively by human physiological signals. This study aims to analyze the differences of ECG (electrocardiogram) characteristics for various types of drivers under anxiety. We used several methods to induce drivers’ mood states (calm and anxiety) and then conducted the real and virtual driving experiments to collect driver’s ECG signal data. Physiological changes in ECG during the experiments were recorded using the PSYLAB software. The independent sample t-test analysis was conducted to determine if there are significant differences in ECG characteristics for different types of drivers in anxious state during driving. The results show that there are significant differences in ECG signal characteristics of drivers by gender, age, and driving experience, in time domain, frequency domain, and waveform under anxiety. Our findings of this study contribute to the development of more intelligent and personalized driver warning system, which could improve road traffic safety.

Human Factor Issues Associated with Lane Change Collision Avoidance Systems: Effects of Authority, Control, and Ability on Drivers’ Performance and Situation Awareness

2017 ◽  
Vol 61 (1) ◽  
pp. 1634-1638 ◽  
Author(s):  
Husam Muslim ◽  
Makoto Itoh
Keyword(s):  
Human Factors ◽  
Collision Avoidance ◽  
Situation Awareness ◽  
Traffic Safety ◽  
Force Feedback ◽  
Road Traffic ◽  
Warning System ◽  
Lane Change ◽  
Road Traffic Safety ◽  
Automatic Action

In order to improve road traffic safety, increasingly sophisticated and robust collision avoidance systems are being developed. When employed in safety-critical situations, however, the interaction between the human factors and these systems may increase the complexity of the task of driving. Due to these human factors, the ability of the driver to respond to various traffic dangers is considered to be a function of the level of automation, balance of control authority, and the innate ability of the driver. For the purpose of this study, a driving experiment was designed using two types of lane change collision avoidance systems. One was a haptic warning system that provides a steering force feedback to avoid hazardous lane change, and the other, a semi-autonomous system that provides an automatic action to prevent hazardous lane change. While drivers had the final authority over the haptic system, they were unable to override the automatic action. Both systems were examined in three conditions: i) hazard that can be detected only by the system, ii) hazard that can be detected only by the driver, and iii) combined hazards. The different support systems were applied to the different hazards resulting in significant differences in drivers’ reaction time and steering behavior. The drivers’ subjective post-hazard assessments were significantly affected by the type of encountered hazard.

Development of Road Traffic Safety Education System Based on Virtual Reality Technology

2012 ◽  
Vol 229-231 ◽  
pp. 1710-1714
Author(s):  
Xue Jian Jiao ◽  
Shan Chai
Keyword(s):  
Virtual Reality ◽  
Traffic Safety ◽  
Education System ◽  
Single Channel ◽  
Road Traffic ◽  
Dynamics Simulation ◽  
Safety Education ◽  
Projection System ◽  
Driving Experience ◽  
Road Traffic Safety

Road traffic safety is a major security problem faced by our society. It has great significance for the society to give the driver a safety education in the totally immersed virtual reality environment. With the single channel stereo display projection system, we established the road traffic safety education system, and solved some key issues, such as the physical modeling of immersive driving experience, the vehicle dynamics simulation and so on. Practical application shows that the system has achieved the purpose of road traffic safety education.

Pre-Warning Information System of Traffic Safety

2011 ◽  
Vol 368-373 ◽  
pp. 3320-3323
Author(s):  
Jun Long Peng ◽  
Da Wang
Keyword(s):  
Traffic Safety ◽  
Traffic Management ◽  
Road Traffic ◽  
Safety Evaluation ◽  
Warning System ◽  
Processing Method ◽  
Average Speed ◽  
Road Traffic Safety ◽  
System Composition ◽  
Highway Transportation

Traffic safety dynamic trend pre-warning could effectively strengthenmonitoring strength of traffic management department, reduce the number of trafficaccident and ensure highway transportation orderly and smooth. This article analysestrend pre-warning system of traffic safety from the highway operation managementangle. Based on the above analysis, the trend dynamic pre-warning system composition and the information processing method are advanced. The processingmethods in according to the characteristics of road traffic safety, from trend impactsof traffic safety evaluation indicators use six indicators to reflect all aspects ofsecurity potential crises, such as average speed, traffic flow size, etc.

scholarly journals Analysis on the Influencing Factors of Driving Behaviours Based on Theory of Planned Behaviour

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Lisheng Jin ◽  
Baicang Guo ◽  
Yuying Jiang ◽  
Qiang Hua
Keyword(s):  
Traffic Safety ◽  
Latent Variables ◽  
Structural Equation ◽  
Theory Of Planned Behaviour ◽  
Road Traffic ◽  
Analysis Model ◽  
Planned Behaviour ◽  
Driving Experience ◽  
Road Traffic Safety ◽  
Driving Behaviour

Driving behaviour is a complex and multidisciplinary research domain, and bad driving behaviours that threaten the safety of road users should be refrained. In order to better educate, manage, and restrain driver’s behaviours, from the perspective of human factors and psychology, the present study deconstructed driving behaviours based on theory of planned behaviour (TPB) into five categories: mistakes (Mis), lapses and slips (LaS), violations (Vio), driving experience (Exp), and safety attitude and awareness (SAA). According to today’s practical traffic rules and conditions in China, a driving behaviour questionnaire was built as an analysing tool and the survey data were collected in accordance with the demographic of Chinese drivers. Furthermore, a driving behaviour analysis model contains the aforementioned categories was established by using the structural equation model (SEM). Through the path analysis results among latent variables and manifested variables, it was found that Exp has an impact on Vio and LaS, and better SAA can inhibit Vio and Mis. In conclusion, the prime aim of improving road traffic safety is to reduce Vio by means of educating and improving the drivers’ Exp and SAA. Moreover, drivers’ LaS and Mis are transition processes which should be corrected timely and prevented from continuing to evolve into Vio.

Analysis of Rear-End Collision Accident of Urban Traffic Based on Safety Pre-Warning Algorithm

2020 ◽  
Author(s):  
Sizhuo Wang ◽  
Wei Li ◽  
Chunyu Kong
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Warning System ◽  
Urban Traffic ◽  
Effective Response ◽  
Collision Warning ◽  
Road Traffic Safety ◽  
Vehicle Collision ◽  
Property Losses

Abstract With the increase of per capita car ownership, traffic accidents frequently occur, in which rear-end collision accounts for 30% to 40% of the total accidents; thus, rear-end collision has become the primary factor of traffic environment deterioration. Therefore, how to improve road traffic safety and reduce the probability of rear-end collision has become a major social concern. In this study, based on the safety pre-warning algorithm, a vehicle collision model was built, and a vehicle anti-collision warning system was established. The calculation was performed based on the sample data to obtain the prediction value of vehicle collision time under different driving speeds, so as to provide drivers with effective response time and reduce the casualties and property losses caused by a vehicle collision. The experimental results showed that the accuracy rate of the pre-warning reached 80% when the speed was regarded as a variable, and the simulation results showed that the early pre-warning or delayed pre-warning rate was very low, and the timeliness rate reached 89%, which enables drivers to react quickly in the appropriate time and effectively reduces the risk of vehicle rear-end collision.

Safety Enhancement by Automated Driving: What are the Relevant Scenarios?

2020 ◽  
Vol 64 (1) ◽  
pp. 1686-1690
Author(s):  
Niklas Grabbe ◽  
Michael Höcher ◽  
Alexander Thanos ◽  
Klaus Bengler
Keyword(s):  
Traffic Safety ◽  
Road Traffic ◽  
Test Cases ◽  
Automated Driving ◽  
Road Traffic Safety ◽  
Human Driver ◽  
Driving Task ◽  
Promising Solution ◽  
Vehicle Automation ◽  
Safety Enhancement

Automated driving offers great possibilities in traffic safety advancement. However, evidence of safety cannot be provided by current validation methods. One promising solution to overcome the approval trap (Winner, 2015) could be the scenario-based approach. Unfortunately, this approach still results in a huge number of test cases. One possible way out is to show the current, incorrect path in the argumentation and strategy of vehicle automation, and focus on the systemic mechanisms of road traffic safety. This paper therefore argues the case for defining relevant scenarios and analysing them systemically in order to ultimately reduce the test cases. The relevant scenarios are based on the strengths and weaknesses, in terms of the driving task, for both the human driver and automation. Finally, scenarios as criteria for exclusion are being proposed in order to systemically assess the contribution of the human driver and automation to road safety.

scholarly journals Assessing inequality, irregularity, and severity regarding road traffic safety during COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lei Lin ◽  
Feng Shi ◽  
Weizi Li
Keyword(s):  
New York ◽  
Los Angeles ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Human Mobility ◽  
Critical Conditions ◽  
Road Traffic Safety ◽  
Accident Data ◽  
The Impact

AbstractCOVID-19 has affected every sector of our society, among which human mobility is taking a dramatic change due to quarantine and social distancing. We investigate the impact of the pandemic and subsequent mobility changes on road traffic safety. Using traffic accident data from the city of Los Angeles and New York City, we find that the impact is not merely a blunt reduction in traffic and accidents; rather, (1) the proportion of accidents unexpectedly increases for “Hispanic” and “Male” groups; (2) the “hot spots” of accidents have shifted in both time and space and are likely moved from higher-income areas (e.g., Hollywood and Lower Manhattan) to lower-income areas (e.g., southern LA and southern Brooklyn); (3) the severity level of accidents decreases with the number of accidents regardless of transportation modes. Understanding those variations of traffic accidents not only sheds a light on the heterogeneous impact of COVID-19 across demographic and geographic factors, but also helps policymakers and planners design more effective safety policies and interventions during critical conditions such as the pandemic.

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