Suggestive Sound Design - How to use Active Interior Sound Design to improve traffic safety

2021 ◽  
Vol 263 (5) ◽  
pp. 1561-1573
Author(s):  
Manuel Petersen ◽  
Marc Etri ◽  
Matthias Behrendt ◽  
Albert Albers ◽  
Manuel Spekker ◽  
...  
Keyword(s):  
Traffic Safety ◽  
Road Safety ◽  
Driving Simulator ◽  
Driving Behavior ◽  
Sound Design ◽  
Driving Experience ◽  
Safety Distance ◽  
Electrical Vehicles ◽  
Important Addition ◽  
External Signals

Active sound design becomes an important addition to the newest generation of premium class electrical vehicles to enhance the emotionality of the driving experience. Musicological research indicates that emotions are altered by certain harmonic sets of pitches, whereas results in traffic psychology show that emotions can influence the driving behavior. Despite these findings, there is no research done on how changes to an active vehicle sound could influence the driving behavior. In this paper, we describe an approach for a suggestive sound design. It's based on the hypothesis, that the chosen safety distance by a driver could be altered by changing the inherent dissonance of an active interior vehicle sound based on the current safety distance. The suggestive sound design is based on an additive synthesizer utilizing the Shepard-Risset glissando. The sound can be controlled by external signals e.g. CAN signals from real or virtual vehicles. To verify this hypothesis, a driving simulator was built in which the driving experience with a suggestive sound and the resulting driving behavior can be validated through subject studies within an immersive and reproducible virtual reality environment. The research aims at improving road safety by influencing the driver through changes in the interior vehicle sound.

scholarly journals Research on the classification for road traffic visibility based on the characteristics of driving behaviour – a driving simulator experiment

2020 ◽  
Vol 3 (1) ◽  
pp. 30-36
Author(s):  
Kun Wang ◽  
Weihua Zhang ◽  
Zhongxiang Feng ◽  
Cheng Wang
Keyword(s):  
Traffic Safety ◽  
Driving Simulator ◽  
Road Traffic ◽  
Driving Behavior ◽  
Control Measures ◽  
Content Type ◽  
The Road ◽  
Road Traffic Safety ◽  
Fine Classification

Purpose The purpose of this paper is to perform fine classification of road traffic visibility based on the characteristics of driving behavior under different visibility conditions. Design/methodology/approach A driving simulator experiment was conducted to collect data of speed and lane position. ANOVA was used to explore the difference in driving behavior under different visibility conditions. Findings The results show that only average speed is significantly different under different visibility conditions. With the visibility reducing, the average vehicle speed decreases. The road visibility conditions in a straight segment can be divided into five levels: less than 20, 20-30, 35-60, 60-140 and more than 140 m. The road visibility conditions in a curve segment can be also divided into four levels: less than 20, 20-30, 35-60 and more than 60 m. Originality/value A fine classification of road traffic visibility has been performed, and these classifications help to establish more accurate control measures to ensure road traffic safety under low-visibility conditions.

scholarly journals MODELING THE PROBABILITY OF SPEEDING BEHAVIOUR AND ACCIDENT INVOLVEMENT USING BINARY LOGISTIC REGRESSION IN EAST JAVA PROVINCE

2020 ◽  
Vol 2 (3) ◽  
pp. 149
Author(s):  
Willy Kriswardhana ◽  
Sonya Sulistyono ◽  
Iin Ervina ◽  
Dadang Supriyanto ◽  
Nunung Nuring Hayati ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Traffic Safety ◽  
High Speed ◽  
Probability Model ◽  
Binary Logistic Regression ◽  
Driving Behavior ◽  
Maximum Speed ◽  
Speed Limit ◽  
Negative Consequences ◽  
Driving Experience

Driving at high speed has negative consequences, namely, the high number of accidents. Several factors have been considered as causes of the increasing severity of victims of traffic accidents, such as a human, vehicle, and environmental factors. The risky driving behavior factor is a factor that needs to be considered in traffic safety studies. This study aims to determine the probability model of speeding behavior based on several driver characteristics and their relationship to accident involvement. This study used a binary logistic regression method to determine the probability of driving behavior exceeding the speed limit and accident involvement. The results showed that the younger a person is, the higher the probability of breaking the maximum speed limit. Furthermore, driving experience also shows a similar trend, where the longer the driving experience of someone, the less likely it is to be involved in an accident. Directions for further research are also presented. Berkendara dengan kecepatan tinggi mempunyai konsekuensi negatif, yaitu tingginya angka kecelakaan. Beberapa faktor telah dipertimbangkan sebagai penyebab dari peningkatan tingkat keparahan korban kecelakaan lalulintas. Faktor tersebut seperti faktor manusia, kendaraan, dan lingkungan. Faktor perilaku berkendara yang berbahaya, menjadi faktor yang perlu diperhatikan dalam kajian keselamatan lalulintas. Penelitian ini bertujuan untuk mengetahui model probabilitas pada perilaku speeding berdasarkan beberapa karakteristik pengendara, serta hubungannya dengan keterlibatan kecelakaan. Penelitian ini menggunakan metode regresi logistik biner untuk mengetahui probabilitas perilaku berkendara melebihi batas kecepatan dan keterlibatan kecelakaan. Hasil penelitian menunjukkan bahwa semakin muda usia seseorang, maka semakin tinggi probabilitasnya dalam melanggar batas kecepatan maksimum. Lebih lanjut diperlihatkan bahwa pengalaman mengemudi juga menunjukkan tren yang serupa. Pengalaman mengemudi seseroang, yang lebih lama akan memperkecil kemungkinan dalam keterlibatan kecelakaan. Arahan untuk penelitian selanjutnya juga ditampilkan.

Senior Driver Performance on Airport Road Access Wayfinding Design

2019 ◽  
Vol 16 (12) ◽  
pp. 4937-4942
Author(s):  
Nur Khairiel Anuar ◽  
Rohafiz Sabar ◽  
Mazli Mutazam
Keyword(s):  
Road Safety ◽  
Driving Simulator ◽  
Driving Behavior ◽  
Age Group ◽  
Traffic Light ◽  
Simulated Driving ◽  
The Road ◽  
Road Design ◽  
Driver Performance ◽  
Study Participants

The purpose of this study was to evaluate the wayfinding and signage provisions, sensitivity of senior driving behavior and road safety. Three scenario types were designed using driving simulator to simplify the airport navigation and driving complexity of the road designs to the airport. An assorted road furniture was included on alternative airport road access to provide a variety of wayfinding complexity. Fifteen experience car drivers in range of age 50–54, 55–59 and over 60 years were selected to perform the study. Participants were asked to drove for approximately 20 minutes to complete the simulated driving. The types of errors (parameter) of simulated driving were identified, evaluated and compared to the age group. Results were analyzed by ANOVA and discussed with reference to the use of driving simulator. The ANOVA confirmed that senior drivers’ age group have no significant effect on the airport road design, wayfinding and all research parameters; risk of collisions, exceed the speed limit, traffic light tickets, centerline crossings and road edge excursions.

scholarly journals Effectiveness of Variable Message Signs on Driving Behavior Based on a Driving Simulation Experiment

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Xuedong Yan ◽  
Jiawei Wu
Keyword(s):  
Traffic Safety ◽  
Road Network ◽  
Simulation Experiment ◽  
Driving Simulator ◽  
Driving Behavior ◽  
Driving Simulation ◽  
Traffic Information ◽  
Variable Message Signs ◽  
Information Format ◽  
Message Signs

Variable message signs (VMSs), as one of the important ITS devices, provide real-time traffic information of road network to drivers in order to improve route choice and relieve the traffic congestion. In this study, the effectiveness of VMS on driving behavior was tested based on a driving simulation experiment. A road network with three levels of VMS location to route-diverging intersection and three types of VMS information format was designed in a high fidelity driving simulator platform. Fifty-two subjects who were classified by driver age, gender, and vocation successfully completed this experiment. The experimental results showed that driver characteristics, VMS location, and information format profoundly influence driving behaviors. Based on the research findings, it is suggested that VMS would be positioned between 150 m and 200 m upstream of the diverging point to balance the VMS effects on traffic safety and operation and the graphic information VMS format is better than the format with text massage only.

scholarly journals Study and Simulation Analysis of Vehicle Rear-End Collision Model considering Driver Types

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Qiang Luo ◽  
Xinqiang Chen ◽  
Jie Yuan ◽  
Xiaodong Zang ◽  
Junheng Yang ◽  
...  
Keyword(s):  
Reaction Time ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Simulation Analysis ◽  
Fuzzy Theory ◽  
Driving Safety ◽  
Driving Experience ◽  
Factors Affecting ◽  
Safety Distance ◽  
Traffic Regulation

The reasonable distance between adjacent cars is very crucial for roadway traffic safety. For different types of drivers or different driving environments, the required safety distance is different. However, most of the existing rear-end collision models do not fully consider the subjective factor such as the driver. Firstly, the factors affecting driving drivers’ characteristics, such as driver age, gender, and driving experience are analyzed. Then, on the basis of this, drivers are classified according to reaction time. Secondly, three main factors affecting driving safety are analyzed by using fuzzy theory, and the new calculation method of the reaction time is obtained. Finally, the improved car-following safety model is established based on different reaction time. The experimental results have shown that our proposed model obtained more accurate vehicle safety distance with varied traffic kinematic conditions (i.e., different traffic states, varied driver types, etc.). The findings can help traffic regulation departments issue early warnings to avoid potential traffic accidents on roads.

scholarly journals Driving Behavior Based on Big Data Analysis and EEG Data Analysis

2021 ◽  
Vol 2066 (1) ◽  
pp. 012096
Author(s):  
Tao Zhang ◽  
Wang Hong
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Traffic Safety ◽  
Road Safety ◽  
Big Data Analysis ◽  
Driving Behavior ◽  
Economic Losses ◽  
Time Zone ◽  
Complex Activity ◽  
Eeg Data

Abstract In recent years, as the number of automobiles in my country has increased year by year, the number of automobile accidents and casualties and the direct economic losses caused by them are very high. How to improve the level of road safety has become an important research content in the field of transportation. Driving a car is a complex activity involving perception, judgment, decision-making and manipulation, and requires the brain to coordinate and guide the driver’s driving functions. EEG signals can reflect the driver’s psychophysiological state, and then represent the driver’s perception activities. The application of EEG data analysis in driving behavior research explains the mechanism of driving behavior from a new perspective of cognitive neuroscience and brings new solutions to traffic safety problems. Driving behavior research is the main research content in the field of road safety. Recognizing and predicting the state of driving behavior is very important for the development of intelligent driving assistance systems and the improvement of road safety. This paper analyzes the EEG data while driving based on big data analysis. Firstly, the literature research method is used to summarize the EEG data analysis process and the research significance, and then the driver’s EEG data is analyzed and researched through simulated driving experiments. The relationship between its parameters and driving behavior. Experimental results show that the front area and buffer area have a strong correlation with all variables of driving behavior, especially the correlation with acceleration and forward time is about 35%. In addition, compared with other driving behavior variables, time zone has the strongest correlation with speed, about 56%. Approximately 46% of the samples are beta waves that are significantly related to driving behavior. In addition, alpha waves account for about 20% of the total number of samples, while the correlation between delta waves and driving behavior is the weakest, accounting for only about 10% of the total number of samples.

Research of Driver’s Visual Perception Model

2012 ◽  
Vol 198-199 ◽  
pp. 932-935
Author(s):  
Qing Xue ◽  
Xiao Ming Ren ◽  
Chang Wei Zheng ◽  
Yong Hong Li
Keyword(s):  
Visual Perception ◽  
Bounded Rationality ◽  
Traffic Safety ◽  
Visual Information ◽  
Hot Spot ◽  
Driving Behavior ◽  
Driving Experience ◽  
Perception Model ◽  
Driving Fatigue ◽  
Fatigue Driving

Driving behavior research is the hot spot in the field of transportation nowadays owning to the stern traffic safety. The visual perception model based on bounded rationality has incorporated the attention distribution and concentration; driving fatigue; driving experience and visual information retrieve which provides a vivid simulation of real driver’s visual perception procedure and it lays the foundation for the study of driver’s decision and manipulation behavior.

scholarly journals The impact of the interfaces of the driving automation system on a driver with regard to road traffic safety

2018 ◽  
Vol 231 ◽  
pp. 04011 ◽  
Author(s):  
Paula Razin ◽  
Arkadiusz Matysiak ◽  
Mikołaj Kruszewski ◽  
Michał Niezgoda
Keyword(s):  
Traffic Safety ◽  
Road Safety ◽  
Driving Simulator ◽  
Road Traffic ◽  
Automation System ◽  
The Road ◽  
Road Traffic Safety ◽  
System Interfaces ◽  
The Impact ◽  
Significant Question

The article presents the results of the road safety-targeted research on the influence of driving automation system interfaces, regarding the highway chauffeur scenario. The verification of multisensory test stand operation was planned through the research targeting transfer of control in a driving simulator. Such examination on one hand allowed to verify its efficiency as a whole (as well as its modules), while on the other hand it helped to answer a significant question regarding the efficient and time-minimizing communication form with driver through the HMI. One of the main analyzed, road safety-targeted parameters was time needed for taking over the control of the vehicle. The results of conducted experiment show that providing the RtI information using all interfaces available in the vehicle may not to be the most effective way. The examinees achieved the best results when informed through visual and auditory interfaces (t=3,84 s). The next stage of the research will cover the analysis of the maneuvers made after the control takeover.

The Characteristics of Traffic Accident Perpetrators in China and Countermeasure Analysis

2013 ◽  
Vol 409-410 ◽  
pp. 1047-1052
Author(s):  
Jun Jun Zou ◽  
Chuan Jiao Sun
Keyword(s):  
Traffic Safety ◽  
Road Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Human Factor ◽  
Safety Education ◽  
Driving Experience ◽  
Main Factors

In the context of rapid increase in car drivers and all citizens being drivers, the driving experience of traffic accident perpetrators has showed a shorter trend. The driver is an important factor that influences the traffic accident, and the drivers behaviors such as speeding, driving on wrong lane and others are the main factors causing traffic accidents. As for the human factor influencing the traffic safety, it is very important to conduct road safety education and publicity work.

scholarly journals Could Road Safety Education (RSE) Help Parents Protect Children? Examining Their Driving Crashes with Children on Board

2021 ◽  
Vol 18 (7) ◽  
pp. 3611
Author(s):  
Francisco Alonso ◽  
Sergio A. Useche ◽  
Eliseo Valle ◽  
Cristina Esteban ◽  
Javier Gene-Morales
Keyword(s):  
Traffic Safety ◽  
Road Safety ◽  
Cross Sectional Study ◽  
Driving Behavior ◽  
Study Data ◽  
Logit Analysis ◽  
Safety Education ◽  
Cross Sectional ◽  
Risky Driving ◽  
Safety Outcomes

Recent evidence suggests that driving behavior and traffic safety outcomes of parents may be influenced by the extent to which they receive information and education on road safety, as well as the fact of driving with their children on board, which may increase their risk perception. However, there are no studies specifically addressing the case of crashes suffered while driving with children. Hence, this study aimed to describe the relationship between road safety education-related variables and parents’ traffic safety outcomes while driving with children on board. For this cross-sectional study, data was retrieved from a sample composed of 165 Spanish parents—all of them licensed drivers—with a mean age of 45.3 years. Through binary logistic regression (logit) analysis, it was found that factors such as gender, having received road safety education (RSE), and having been sanctioned for the performance of risky driving behavior contribute to modulating the likelihood of suffering crashes while driving with children on board. Gender differences showed a riskier status for male parents. In this study, a set of risk factors explaining the involvement in traffic crashes when driving with children as passengers was identified among parents: gender, traffic sanctions, valuation, and exposure to road safety campaigns. Also, substantial limitations in the self-reported degree of received RSE were found, especially considering that risky driving behavior and traffic crash rates with children on board still have a high prevalence among parents.

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