scholarly journals A Comparative Study of Accident Risk Related to Speech-Based and Handheld Texting during a Sudden Braking Event in Urban Road Environments

2020 ◽  
Vol 17 (16) ◽  
pp. 5675 ◽  
Author(s):  
Rui Fu ◽  
Yunxing Chen ◽  
Qingjin Xu ◽  
Yuxi Guo ◽  
Wei Yuan
Keyword(s):  
Mobile Phone ◽  
Driving Behavior ◽  
Initial Time ◽  
Accident Risk ◽  
Urban Road ◽  
Time Headway ◽  
Young Drivers ◽  
Deceleration Rate ◽  
Accident Probability ◽  
Behavior Characteristics

The use of mobile phones while driving is a very common phenomenon that has become one of the main causes of traffic accidents. Many studies on the effects of mobile phone use on accident risk have focused on conversation and texting; however, few studies have directly compared the impacts of speech-based texting and handheld texting on accident risk, especially during sudden braking events. This study aims to statistically model and quantify the effects of potential factors on accident risk associated with a sudden braking event in terms of the driving behavior characteristics of young drivers, the behavior of the lead vehicle (LV), and mobile phone distraction tasks (i.e., both speech-based and handheld texting). For this purpose, a total of fifty-five licensed young drivers completed a driving simulator experiment in a Chinese urban road environment under five driving conditions: baseline (no phone use), simple speech-based texting, complex speech-based texting, simple handheld texting, and complex handheld texting. Generalized linear mixed models were developed for the brake reaction time and rear-end accident probability during the sudden braking events. The results showed that handheld texting tasks led to a delayed response to the sudden braking events as compared to the baseline. However, speech-based texting tasks did not slow down the response. Moreover, drivers responded faster when the initial time headway was shorter, when the initial speed was higher, or when the LV deceleration rate was greater. The rear-end accident probability respectively increased by 2.41 and 2.77 times in the presence of simple and complex handheld texting while driving. Surprisingly, the effects of speech-based texting tasks were not significant, but the accident risk increased if drivers drove the vehicle with a shorter initial time headway or a higher LV deceleration rate. In summary, these findings suggest that the effects of mobile phone distraction tasks, driving behavior characteristics, and the behavior of the LV should be taken into consideration when developing algorithms for forward collision warning systems.

scholarly journals Mobile Phone Use in a Car-Following Situation: Impact on Time Headway and Effectiveness of Driver’s Rear-End Risk Compensation Behavior via a Driving Simulator Study

2020 ◽  
Vol 17 (4) ◽  
pp. 1328 ◽  
Author(s):  
Yunxing Chen ◽  
Rui Fu ◽  
Qingjin Xu ◽  
Wei Yuan
Keyword(s):  
Regression Model ◽  
Mobile Phone ◽  
Driving Simulator ◽  
Accident Risk ◽  
Mobile Phone Use ◽  
Car Following ◽  
Time Headway ◽  
Accident Probability ◽  
Compensation Behavior ◽  
The Relationship

Mobile phone use while driving has become one of the leading causes of traffic accidents and poses a significant threat to public health. This study investigated the impact of speech-based texting and handheld texting (two difficulty levels in each task) on car-following performance in terms of time headway and collision avoidance capability; and further examined the relationship between time headway increase strategy and the corresponding accident frequency. Fifty-three participants completed the car-following experiment in a driving simulator. A Generalized Estimating Equation method was applied to develop the linear regression model for time headway and the binary logistic regression model for accident probability. The results of the model for time headway indicated that drivers adopted compensation behavior to offset the increased workload by increasing their time headway by 0.41 and 0.59 s while conducting speech-based texting and handheld texting, respectively. The model results for the rear-end accident probability showed that the accident probability increased by 2.34 and 3.56 times, respectively, during the use of speech-based texting and handheld texting tasks. Additionally, the greater the deceleration of the lead vehicle, the higher the probability of a rear-end accident. Further, the relationship between time headway increase patterns and the corresponding accident frequencies showed that all drivers’ compensation behaviors were different, and only a few drivers increased their time headway by 60% or more, which could completely offset the increased accident risk associated with mobile phone distraction. The findings provide a theoretical reference for the formulation of traffic regulations related to mobile phone use, driver safety education programs, and road safety public awareness campaigns. Moreover, the developed accident risk models may contribute to the development of a driving safety warning system.

scholarly journals Portable System for Monitoring and Controlling Driver Behavior and the Use of a Mobile Phone While Driving

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1563 ◽  
Author(s):  
Amith Khandakar ◽  
Muhammad E.H. Chowdhury ◽  
Rashid Ahmed ◽  
Ahmed Dhib ◽  
Mohammed Mohammed ◽  
...  
Keyword(s):  
Mobile Phone ◽  
Mobile Application ◽  
Electronic Device ◽  
Driving Behavior ◽  
Lane Changes ◽  
Young Drivers ◽  
Mobile Phone Applications ◽  
Portable System ◽  
Specific Speed ◽  
Vehicle Information

There is an utmost requirement for technology to control a driver’s phone while driving, which will prevent the driver from being distracted and thus saving the driver’s and passenger’s lives. Information from recent studies has shown that 70% of the young and aware drivers are used to texting while driving. There are many different technologies used to control mobile phones while driving, including electronic device control, global positioning system (GPS), on-board diagnostics (OBD)-II-based devices, mobile phone applications or apps, etc. These devices acquire the vehicle information such as the car speed and use the information to control the driver’s phone such as preventing them from making or receiving calls at specific speed limits. The information from the devices is interfaced via Bluetooth and can later be used to control mobile phone applications. The main aim of this paper is to propose the design of a portable system for monitoring the use of a mobile phone while driving and for controlling a driver’s mobile phone, if necessary, when the vehicle reaches a specific speed limit (>10 km/h). A paper-based self-reported questionnaire survey was carried out among 600 teenage drivers from different nationalities to see the driving behavior of young drivers in Qatar. Finally, a mobile application was developed to monitor the mobile usage of a driver and an OBD-II module-based portable system was designed to acquire data from the vehicle to identify drivers’ behavior with respect to phone usage, sudden lane changes, and abrupt breaking/sharp speeding. This information was used in a mobile application to control the driver’s mobile usage as well as to report the driving behavior while driving. The application of such a system can significantly improve drivers’ behavior all over the world.

scholarly journals Mobile Phone Use “on the Road”: A Self-Report Study on Young Drivers

2021 ◽  
Vol 12 ◽  
Author(s):  
Angelo Fraschetti ◽  
Pierluigi Cordellieri ◽  
Giulia Lausi ◽  
Emanuela Mari ◽  
Elena Paoli ◽  
...  
Keyword(s):  
Risk Perception ◽  
Mobile Phone ◽  
Self Efficacy ◽  
Sensation Seeking ◽  
Self Report ◽  
Accident Risk ◽  
Mobile Phone Use ◽  
The Road ◽  
Young Drivers ◽  
On The Road

BackgroundExtensive research showed that multitasking negatively affects driving performance. Multitasking activities can range from talking and texting to listening to music; particularly among young drivers, multitasking behavior is caused mainly from mobile phone use while driving which is one of the main causes of road accidents.ObjectiveThe main purpose of this study was to investigate whether some variables (e.g., Sensation-Seeking, preferences of Multitasking) could affect mobile phone use while driving in young drivers and whether any gender differences were present among the examined variables.Setting and participantsThe sample consists of 424 Italian students (56% males) with an age range of 18–21 years. A self-report questionnaire was specifically developed to assess variables such as: Attitude toward Multitasking, Perceived Self-efficacy in Multitasking, Accident Risk Perception, General Multitasking Habits, and Sensation Seeking.ResultsThrough SEM modeling, we found the attitude to multitasking while driving to be largely explained by the considered variables. Using multigroup analysis (MGSEM), the model we developed appears to be suitable for explaining the behaviors of both male and female young drivers. Furthermore, data comparison showed that females were more likely to risk perception toward multitasking, and risk perception when using a mobile phone while driving, while males obtained higher mean scores in Sensation Seeking, Perceived Self-Efficacy in Multitasking, and in Multitasking caused by mobile phone use while driving.ConclusionOur research showed how some variables may influence the inclination of some subjects to engage in multitasking while driving. Furthermore, we discussed the importance of considering these variables in the implementation of effective road safety education projects on driving multitasking.

A Graph Based Security Description Method of Driving Behavior Characteristics

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Hang Qi ◽  
Xiao-Hua Zhao ◽  
Yi-Ping Wu ◽  
Chang Liu
Keyword(s):  
Driving Behavior ◽  
Behavior Characteristics

Effects of mobile phone use on pedestrian crossing behavior and safety at unsignalized intersections

2019 ◽  
Vol 46 (5) ◽  
pp. 381-388
Author(s):  
Hualong Zhang ◽  
Cunbao Zhang ◽  
Feng Chen ◽  
YuanYuan Wei
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Logistic Regression Model ◽  
Field Survey ◽  
Mobile Phone Use ◽  
Unsignalized Intersections ◽  
Behavior Characteristics ◽  
Pedestrian Crossing

Using mobile phones can be a source of distraction for pedestrians when crossing streets, it is especially dangerous at unsignalized intersections. To investigate the effects of mobile phone use on pedestrian crossing behavior and safety at unsignalized intersections, we carried out a field survey at three selected locations in Wuhan, China. Then, the pedestrians’ crossing behavior characteristics were statistically analyzed, and a logistic regression model was established to quantitatively analyze pedestrian safety. The results showed that 15.6% of pedestrians used mobile phones when crossing unsignalized intersections and 64.1% of them were young pedestrians. Pedestrians using mobile phones while crossing unsignalized intersections were at higher risk of accident, crossed more slowly, and were less likely to look at traffic status than those not using a mobile phone. Moreover, the probability of conflicts when watching the screen, talking, and listening to music are 2.704, 1.793, and 1.114 times greater, respectively, than those who do not use a mobile phone.

Mobile phone use by young drivers: effects on traffic speed and headways

2010 ◽  
Vol 33 (4) ◽  
pp. 385-394 ◽  
Author(s):  
George Yannis ◽  
Eleonora Papadimitriou ◽  
Xenia Karekla ◽  
Efrosyni Kontodima
Keyword(s):  
Mobile Phone ◽  
Mobile Phone Use ◽  
Young Drivers ◽  
Traffic Speed

Capturing driving behavior Heterogeneity based on trajectory data

2020 ◽  
Vol 11 (03) ◽  
pp. 2050023
Author(s):  
Dong-Fan Xie ◽  
Tai-Lang Zhu ◽  
Qian Li
Keyword(s):  
Reaction Time ◽  
Fuel Consumption ◽  
Driving Behavior ◽  
Surprising Result ◽  
Trajectory Data ◽  
Dimensional Approach ◽  
Time Headway ◽  
Fuel Consumption And Emissions ◽  
Measure Index ◽  
Real Traffic

Driving behavior is heterogeneous for various drivers due to the different influencing factors as reaction time, gender, driving years and so on. Some existing works tried to reproduce some of the complex characteristics of real traffic flow by taking into account the heterogeneous driving behavior, and the drivers are generally divided into two classes (including aggressive drivers and careful drivers) or three classes (including aggressive drivers, normal drivers and careful drivers). Nevertheless, the classification approaches have not been verified, and the rationality of the classifications has not been confirmed as well. In this study, the trajectory data of drivers is extracted from the NGSIM datasets. By combining the K-Means method and Silhouette measure index, the drivers are classified into four clusters (named as clusters A, B, C and D, respectively) in accordance with the acceleration and time headway. The two-dimensional approach is applied to analyze the characteristics of different clusters. Here, one dimension consists of “Cautious” and “Aggressive” behaviors in terms of velocity and acceleration, and the other dimension consists of “Sensitive” and “Insensitive” behaviors in terms of reaction time. Finally, the fuel consumption and emissions for different clusters are calculated by using the VT-Micro model. A surprising result indicates that overly “cautious” and “sensitive” behaviors may result in more fuel consumption and emissions. Therefore, it is necessary to find the balance between the driving characteristics.

The risks associated with using a mobile phone by young drivers

Transport ◽  
2013 ◽  
Vol 28 (4) ◽  
pp. 381-388 ◽  
Author(s):  
Marjana Čubranić-Dobrodolac ◽  
Svetlana Čičević ◽  
Momčilo Dobrodolac ◽  
Milkica Nešić
Keyword(s):  
Mobile Phone ◽  
Young Drivers
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