Pedestrians, much like drivers, have always been engaged in multi-tasking like using handheld devices, listening to music, snacking, or reading while walking. The effects are similar to those experienced by distracted...Pedestrians, much like drivers, have always been engaged in multi-tasking like using handheld devices, listening to music, snacking, or reading while walking. The effects are similar to those experienced by distracted drivers. However, distracted walking has not received similar policies and effective interventions as distracted driving to improve pedestrian safety. This study reviewed the state-of-practice on policies, campaigns, available data, identified research needs, and opportunities pertaining to distracted walking. A comprehensive review of literature revealed that some of the agencies/organizations disseminate useful information about certain distracting activities that pedestrians should avoid while walking to improve their safety. Various walking safety rules/tips have been given, such as not wearing headphones or talking on a cell phone while crossing a street, keeping the volume down, hanging up the phone while walking, being aware of traffic, and avoiding distractions like walking with texting. The majority of the past observational-based and experimental-based studies reviewed in this study on distracted walking is in agreement that there is a positive correlation between distraction and unsafe walking behavior. However, limitations of the existing crash data suggest that distracted walking may not be a severe threat to the public health. Current pedestrian crash data provide insufficient information for researchers to examine the extent to which distracted walking causes and/ or contributes to actual pedestrian safety problems.展开更多
Professional drivers are more frequently exposed to longer driving distance and travel time,leading to a higher possibility of safety risk for distraction and fatigue.The widespread and common use of commercial driver...Professional drivers are more frequently exposed to longer driving distance and travel time,leading to a higher possibility of safety risk for distraction and fatigue.The widespread and common use of commercial driver monitoring systems(DMS)provides a potential for data collection.It increases the amount of data characterizing driver behavior that can be used for further safety research.This study utilized DMS warning-based data and applied an association rule mining approach to explore risk factors contributing to hazardous materials(HAZMAT)truck driver inattention.A total of 499 HAZMAT truck driver inattentive warning events were used to find rules that will predict the occurrence of driver’s fatigue and distraction.First,Fisher’s exact tests were performed to examine the association between the frequency of driver inattentive behavior warnings and risk factors.Second,support,confidence,and lift values were used as measurements to quantify the relative strength of the association rules generated by the Apriori algorithm.Results show that speed between 40and 49 km/h,relatively longer travel time(3-6 h),freeway,tangent section,off-peak hour and clear weather condition are found to be highly associated with fatigue driving,while nighttime during 18:00 to 23:59,speed between 70 and 80 km/h,travel time between 1 and 3 h,freeways,acceleration less than 0.5 m/s^(2),visibility greater than 1000 m,and tangent roadway section are found to be highly associated with distracted driving.By focusing on the specific feature groups,these association rules would help in the development of mitigating distraction and fatigue driving countermeasures and enforcement approaches.展开更多
Smart mobile applications are software applications that are designed to run on smart phones, tablets, and other mobile electronic devices. In this era of rapid technological advances, these applications have become o...Smart mobile applications are software applications that are designed to run on smart phones, tablets, and other mobile electronic devices. In this era of rapid technological advances, these applications have become one of the primary tools we use daily both in our personal and professional lives. The applications play key roles in facilitating many applications that are pivotal in our today＇s society including communication, education, business, entertainment, medical, finance, travel, utilities, social, and transportation. This paper reviewed the opportunities and challenges of the applications related to transportation. The opportunities revealed include route planning, ridesharing/carpooling, traffic safety, parking information, transportation data collection, fuel emissions and consumption, and travel information. The potential users of these applications in the field of transportation include （I） transportation agencies for travel data collection, travel information, ridesharing/carpooling, and traffic safety, （2） engineering students for field data collection such as travel speed, travel time, and vehicle count, and （3） general traveling public for route planning, ridesharing/carpooling, parking, traffic safety, and travel information. Significant usage of smart mobile applications can be potentially very beneficial, particularly in automobile travel mode to reduce travel time, cost, and vehicle emissions. In the end this would make travel safer and living environments greener and healthier. However, road users＇ interactions with these applications could manually, visually, and cognitively divert their attention from the primary task of driving or walking. Distracted road users expose themselves and others to unsafe behavior than undistracted. Road safety education and awareness programs are vital to discourage the use of applications that stimulate unsafe driving/walking behaviors. Educating the traveling public about the dangers of unsafe driving/walking behavior could have significant 展开更多
Risky driving behavior of taxi drivers typically evaluated for full operation or sometimes sorted into occupied and empty running trips.In this paper,we simultaneously analyze aggressive driving and distracted driving...Risky driving behavior of taxi drivers typically evaluated for full operation or sometimes sorted into occupied and empty running trips.In this paper,we simultaneously analyze aggressive driving and distracted driving of taxi drivers under three different trip categories.Trip origin is considered a transition from without ride-order to with ride-order travelling or from with ride-order to occupied travelling,and a destination as a transition from occupied to without ride-order travelling and vice versa.Distracted driving is characterized by driver interference,driver mobile use and some entertainment aspects,while specific harmful and risky actions are considered for aggressive driving.High-resolution and real-time kinematic parameters of taxis were recorded by the in-vehicle recorder VBOX for overall 562 trips.The distracted driving parameters and aggressive driving actions were monitored through python data collector web application that was specially programmed for this particular research.Besides dual dash cam(i.e.,front and inside car camera),drivers’ whole day driving history from their Chinese ride-hailing Di Di smart application was used to differentiate occupied trips,unoccupied trips with ride-order and unoccupied trips without ride-order.Structural equation modeling(SEM) is practiced in this paper to understand the influence of distracted driving indicators on aggressive driving behaviors.The multi-group model analysis of SEM indicated that handling distracted risky driving could control aggressive driving behavior up to 96% and 98% inunoccupied without ride-order trips and unoccupied trips with ride-order respectively.The model has also identified the sensitive risky driving indicators for each group separately.展开更多
Distracted driving occurs when a driver diverts the primary attention from driving to another task. Using mobile devices such as a cellphone for texting, calls, or other manipulation while driving has the highest pote...Distracted driving occurs when a driver diverts the primary attention from driving to another task. Using mobile devices such as a cellphone for texting, calls, or other manipulation while driving has the highest potential for distraction because it combines both forms of distractions, manual, visual, and cognitive. Some states in the US have posted slogans including “</span><i><span style="font-family:Verdana;">W</span></i><span style="font-family:Verdana;">8 2 </span><i><span style="font-family:Verdana;">TXT</span></i><span style="font-family:Verdana;">, </span><i><span style="font-family:Verdana;">it</span></i><span style="font-family:Verdana;">’</span><i><span style="font-family:Verdana;">s</span></i> <i><span style="font-family:Verdana;">a</span></i> <i><span style="font-family:Verdana;">law</span></i><span style="font-family:Verdana;">”, “</span><i><span style="font-family:Verdana;">Don</span></i><span style="font-family:Verdana;">’</span><i><span style="font-family:Verdana;">t</span></i> <i><span style="font-family:Verdana;">Drive</span></i> <i><span style="font-family:Verdana;">inTEXTicated</span></i><span style="font-family:Verdana;">”, “</span><i><span style="font-family:Verdana;">PLS</span></i> <i><span style="font-family:Verdana;">dnt</span></i> <i><span style="font-family:Verdana;">txt</span></i> <i><span style="font-family:Verdana;">n</span></i> <i><span style="font-family:Verdana;">drv</span></i><span style="font-family:Verdana;">”, “</span><i><span style="font-family:Verdana;">Don</span></i><span style="font-family:Verdana;">’</span><i><span style="font-family:Verdana;">t</span></i> <i><span style="font-family:Verdana;">tempt</span></i> <i><span style="font-family:Verdana;">F</span></i><span style="font-family:Verdana;">8 </span><i><span style="font-family:Verdana;">that</span></i> <i><span style="font-family:Verdana;">txt</span></i> <i><span style="font-family:Verdana;">can</span></i> <i><span style="font-family:Verdana;">w</span></i><span style="font-family:Verdana;">8”, </展开更多
Purpose–The purpose of this paper is to investigate the influence of driver demographic characteristics on the driving safety involving cell phone usages.Design/methodology/approach–A total of 1,432 crashes and 19,71...Purpose–The purpose of this paper is to investigate the influence of driver demographic characteristics on the driving safety involving cell phone usages.Design/methodology/approach–A total of 1,432 crashes and 19,714 baselines were collected for the Strategic Highway Research Program 2 naturalistic driving research.The authors used a case-control approach to estimate the prevalence and the population attributable risk percentage.The mixed logistic regression model is used to evaluate the correlation between different driver demographic characteristics(age,driving experience or their combination)and the crash risk regarding cell phone engagements,as well as the correlation among the likelihood of the cell phone engagement during the driving,multiple driver demographic characteristics(gender,age and driving experience)and environment conditions.Findings–Senior drivers face an extremely high crash risk when distracted by cell phone during driving,but they are not involved in crashes at a large scale.On the contrary,cell phone usages account for a far larger percentage of total crashes for young drivers.Similarly,experienced drivers and experienced-middle-aged drivers seem less likely to be impacted by the cell phone while driving,and cell phone engagements are attributed to a lower percentage of total crashes for them.Furthermore,experienced,senior or male drivers are less likely to engage in cell phone-related secondary tasks while driving.Originality/value–The results provide support to guide countermeasures and vehicle design.展开更多
The Philippines is expecting a rise in the number of drivers that use mobile phones while driving.It is known as the“texting capital of the world”.The objectives of this study were to determine the predictors,risk p...The Philippines is expecting a rise in the number of drivers that use mobile phones while driving.It is known as the“texting capital of the world”.The objectives of this study were to determine the predictors,risk perceptions and the prevalence of cell phone use while driving among trainee residents of the University of the Philippines-Philippine General Hospital.This cross-sectional study employed total enumeration.A survey was first distributed to the target population,followed by a focus group discussion.Chi-square and multiple logistic regression were used to analyze data.Included in the final analysis were 175 drivers aged 25-30 years(mean=27.90+1.34).There was no significant difference in the risk perceptions of cell phone users vs.non-users,and most perceived hands-free devices safer to use(p=0.030).The reported prevalence is 90.68%;drivers have a significant overall unsafe attitude(p=0.007),and an unsafe attitude when using handsets when driving,even when this is known to be dangerous(p=0.003).In conclusion,driving with hands-free devices was perceived to be safer,although drivers have a high overall unsafe attitude.Driving for more than two years and having an unsafe attitude were found to be significant predictors of cell phone use while driving.Countermeasures must take into account these factors when instituting behavioral modification strategies and road safety policies concerning unsafe and distracted driving.展开更多
驾驶人在驾驶车辆的过程中总会面临由自身或外界条件所带来的或高或低的风险,即驾驶风险,通过对驾驶风险进行识别、分析及评估是对风险进行管理的有效对策,明确由人为因素(即驾驶人个体特征及驾驶行为)所带来的驾驶风险并对驾驶人进行...驾驶人在驾驶车辆的过程中总会面临由自身或外界条件所带来的或高或低的风险,即驾驶风险,通过对驾驶风险进行识别、分析及评估是对风险进行管理的有效对策,明确由人为因素(即驾驶人个体特征及驾驶行为)所带来的驾驶风险并对驾驶人进行安全管理尤为重要。为了全面了解各类危险驾驶行为和各种驾驶人群体的驾驶风险行为研究进展,对驾驶风险领域重点问题进行了总体概述。从驾驶人个体特征及驾驶行为的角度出发,探究了驾驶风险领域目前的研究现状,并利用科学知识图谱展示驾驶风险领域研究的发展进程与结构关系。通过Web of Science核心合集数据库获取了3406篇在1986~2020年(截至2020年2月29日)间出版的驾驶风险研究相关英文文献,共涵盖8684位作者及6018个关键词,基于科学知识图谱对该领域文献进行梳理与分析。结果表明:驾驶风险领域的国外研究在驾驶人选择方面主要从年轻驾驶人、老年驾驶人、新手驾驶人及职业驾驶人的角度进行切入,重点围绕酒驾、药驾、分心驾驶及疲劳驾驶等主题开展研究。与国外研究相比,中国在分心驾驶、疲劳驾驶领域的研究相对丰富,而针对酒驾、药驾的研究试验手段较为单一,研究不够全面;在研究对象的选取上,有必要进一步增加老年驾驶人及新手驾驶人的深入研究,包括老年驾驶人适驾性评估与教育培训,以及新手驾驶人驾照分级制度的可行性探索。在研究方法方面,国外常见研究方法包括问卷调查、驾驶模拟器试验、实车试验以及自然驾驶研究等,而中国在自然驾驶研究领域尚未充分开发利用;未来应考虑多种方法相结合并从不同角度促进对驾驶行为及驾驶风险的全面理解。展开更多
文摘Pedestrians, much like drivers, have always been engaged in multi-tasking like using handheld devices, listening to music, snacking, or reading while walking. The effects are similar to those experienced by distracted drivers. However, distracted walking has not received similar policies and effective interventions as distracted driving to improve pedestrian safety. This study reviewed the state-of-practice on policies, campaigns, available data, identified research needs, and opportunities pertaining to distracted walking. A comprehensive review of literature revealed that some of the agencies/organizations disseminate useful information about certain distracting activities that pedestrians should avoid while walking to improve their safety. Various walking safety rules/tips have been given, such as not wearing headphones or talking on a cell phone while crossing a street, keeping the volume down, hanging up the phone while walking, being aware of traffic, and avoiding distractions like walking with texting. The majority of the past observational-based and experimental-based studies reviewed in this study on distracted walking is in agreement that there is a positive correlation between distraction and unsafe walking behavior. However, limitations of the existing crash data suggest that distracted walking may not be a severe threat to the public health. Current pedestrian crash data provide insufficient information for researchers to examine the extent to which distracted walking causes and/ or contributes to actual pedestrian safety problems.
基金supported by National Key R&D Program of China(2021YFC3001500).
文摘Professional drivers are more frequently exposed to longer driving distance and travel time,leading to a higher possibility of safety risk for distraction and fatigue.The widespread and common use of commercial driver monitoring systems(DMS)provides a potential for data collection.It increases the amount of data characterizing driver behavior that can be used for further safety research.This study utilized DMS warning-based data and applied an association rule mining approach to explore risk factors contributing to hazardous materials(HAZMAT)truck driver inattention.A total of 499 HAZMAT truck driver inattentive warning events were used to find rules that will predict the occurrence of driver’s fatigue and distraction.First,Fisher’s exact tests were performed to examine the association between the frequency of driver inattentive behavior warnings and risk factors.Second,support,confidence,and lift values were used as measurements to quantify the relative strength of the association rules generated by the Apriori algorithm.Results show that speed between 40and 49 km/h,relatively longer travel time(3-6 h),freeway,tangent section,off-peak hour and clear weather condition are found to be highly associated with fatigue driving,while nighttime during 18:00 to 23:59,speed between 70 and 80 km/h,travel time between 1 and 3 h,freeways,acceleration less than 0.5 m/s^(2),visibility greater than 1000 m,and tangent roadway section are found to be highly associated with distracted driving.By focusing on the specific feature groups,these association rules would help in the development of mitigating distraction and fatigue driving countermeasures and enforcement approaches.
文摘Smart mobile applications are software applications that are designed to run on smart phones, tablets, and other mobile electronic devices. In this era of rapid technological advances, these applications have become one of the primary tools we use daily both in our personal and professional lives. The applications play key roles in facilitating many applications that are pivotal in our today＇s society including communication, education, business, entertainment, medical, finance, travel, utilities, social, and transportation. This paper reviewed the opportunities and challenges of the applications related to transportation. The opportunities revealed include route planning, ridesharing/carpooling, traffic safety, parking information, transportation data collection, fuel emissions and consumption, and travel information. The potential users of these applications in the field of transportation include （I） transportation agencies for travel data collection, travel information, ridesharing/carpooling, and traffic safety, （2） engineering students for field data collection such as travel speed, travel time, and vehicle count, and （3） general traveling public for route planning, ridesharing/carpooling, parking, traffic safety, and travel information. Significant usage of smart mobile applications can be potentially very beneficial, particularly in automobile travel mode to reduce travel time, cost, and vehicle emissions. In the end this would make travel safer and living environments greener and healthier. However, road users＇ interactions with these applications could manually, visually, and cognitively divert their attention from the primary task of driving or walking. Distracted road users expose themselves and others to unsafe behavior than undistracted. Road safety education and awareness programs are vital to discourage the use of applications that stimulate unsafe driving/walking behaviors. Educating the traveling public about the dangers of unsafe driving/walking behavior could have significant
基金supported by the National Key R&D Program of China(2018YFB1601600)。
文摘Risky driving behavior of taxi drivers typically evaluated for full operation or sometimes sorted into occupied and empty running trips.In this paper,we simultaneously analyze aggressive driving and distracted driving of taxi drivers under three different trip categories.Trip origin is considered a transition from without ride-order to with ride-order travelling or from with ride-order to occupied travelling,and a destination as a transition from occupied to without ride-order travelling and vice versa.Distracted driving is characterized by driver interference,driver mobile use and some entertainment aspects,while specific harmful and risky actions are considered for aggressive driving.High-resolution and real-time kinematic parameters of taxis were recorded by the in-vehicle recorder VBOX for overall 562 trips.The distracted driving parameters and aggressive driving actions were monitored through python data collector web application that was specially programmed for this particular research.Besides dual dash cam(i.e.,front and inside car camera),drivers’ whole day driving history from their Chinese ride-hailing Di Di smart application was used to differentiate occupied trips,unoccupied trips with ride-order and unoccupied trips without ride-order.Structural equation modeling(SEM) is practiced in this paper to understand the influence of distracted driving indicators on aggressive driving behaviors.The multi-group model analysis of SEM indicated that handling distracted risky driving could control aggressive driving behavior up to 96% and 98% inunoccupied without ride-order trips and unoccupied trips with ride-order respectively.The model has also identified the sensitive risky driving indicators for each group separately.
文摘Distracted driving occurs when a driver diverts the primary attention from driving to another task. Using mobile devices such as a cellphone for texting, calls, or other manipulation while driving has the highest potential for distraction because it combines both forms of distractions, manual, visual, and cognitive. Some states in the US have posted slogans including “</span><i><span style="font-family:Verdana;">W</span></i><span style="font-family:Verdana;">8 2 </span><i><span style="font-family:Verdana;">TXT</span></i><span style="font-family:Verdana;">, </span><i><span style="font-family:Verdana;">it</span></i><span style="font-family:Verdana;">’</span><i><span style="font-family:Verdana;">s</span></i> <i><span style="font-family:Verdana;">a</span></i> <i><span style="font-family:Verdana;">law</span></i><span style="font-family:Verdana;">”, “</span><i><span style="font-family:Verdana;">Don</span></i><span style="font-family:Verdana;">’</span><i><span style="font-family:Verdana;">t</span></i> <i><span style="font-family:Verdana;">Drive</span></i> <i><span style="font-family:Verdana;">inTEXTicated</span></i><span style="font-family:Verdana;">”, “</span><i><span style="font-family:Verdana;">PLS</span></i> <i><span style="font-family:Verdana;">dnt</span></i> <i><span style="font-family:Verdana;">txt</span></i> <i><span style="font-family:Verdana;">n</span></i> <i><span style="font-family:Verdana;">drv</span></i><span style="font-family:Verdana;">”, “</span><i><span style="font-family:Verdana;">Don</span></i><span style="font-family:Verdana;">’</span><i><span style="font-family:Verdana;">t</span></i> <i><span style="font-family:Verdana;">tempt</span></i> <i><span style="font-family:Verdana;">F</span></i><span style="font-family:Verdana;">8 </span><i><span style="font-family:Verdana;">that</span></i> <i><span style="font-family:Verdana;">txt</span></i> <i><span style="font-family:Verdana;">can</span></i> <i><span style="font-family:Verdana;">w</span></i><span style="font-family:Verdana;">8”, </
基金supported in part by the Joint Laboratory for Internet of Vehicles,Ministry of Education-China Mobile Communications Corporation under Grant ICV-KF2018-01in part by the National Natural Science Foundation of China underGrant 51975194 and 51905161.
文摘Purpose–The purpose of this paper is to investigate the influence of driver demographic characteristics on the driving safety involving cell phone usages.Design/methodology/approach–A total of 1,432 crashes and 19,714 baselines were collected for the Strategic Highway Research Program 2 naturalistic driving research.The authors used a case-control approach to estimate the prevalence and the population attributable risk percentage.The mixed logistic regression model is used to evaluate the correlation between different driver demographic characteristics(age,driving experience or their combination)and the crash risk regarding cell phone engagements,as well as the correlation among the likelihood of the cell phone engagement during the driving,multiple driver demographic characteristics(gender,age and driving experience)and environment conditions.Findings–Senior drivers face an extremely high crash risk when distracted by cell phone during driving,but they are not involved in crashes at a large scale.On the contrary,cell phone usages account for a far larger percentage of total crashes for young drivers.Similarly,experienced drivers and experienced-middle-aged drivers seem less likely to be impacted by the cell phone while driving,and cell phone engagements are attributed to a lower percentage of total crashes for them.Furthermore,experienced,senior or male drivers are less likely to engage in cell phone-related secondary tasks while driving.Originality/value–The results provide support to guide countermeasures and vehicle design.
文摘The Philippines is expecting a rise in the number of drivers that use mobile phones while driving.It is known as the“texting capital of the world”.The objectives of this study were to determine the predictors,risk perceptions and the prevalence of cell phone use while driving among trainee residents of the University of the Philippines-Philippine General Hospital.This cross-sectional study employed total enumeration.A survey was first distributed to the target population,followed by a focus group discussion.Chi-square and multiple logistic regression were used to analyze data.Included in the final analysis were 175 drivers aged 25-30 years(mean=27.90+1.34).There was no significant difference in the risk perceptions of cell phone users vs.non-users,and most perceived hands-free devices safer to use(p=0.030).The reported prevalence is 90.68%;drivers have a significant overall unsafe attitude(p=0.007),and an unsafe attitude when using handsets when driving,even when this is known to be dangerous(p=0.003).In conclusion,driving with hands-free devices was perceived to be safer,although drivers have a high overall unsafe attitude.Driving for more than two years and having an unsafe attitude were found to be significant predictors of cell phone use while driving.Countermeasures must take into account these factors when instituting behavioral modification strategies and road safety policies concerning unsafe and distracted driving.
文摘驾驶人在驾驶车辆的过程中总会面临由自身或外界条件所带来的或高或低的风险,即驾驶风险,通过对驾驶风险进行识别、分析及评估是对风险进行管理的有效对策,明确由人为因素(即驾驶人个体特征及驾驶行为)所带来的驾驶风险并对驾驶人进行安全管理尤为重要。为了全面了解各类危险驾驶行为和各种驾驶人群体的驾驶风险行为研究进展,对驾驶风险领域重点问题进行了总体概述。从驾驶人个体特征及驾驶行为的角度出发,探究了驾驶风险领域目前的研究现状,并利用科学知识图谱展示驾驶风险领域研究的发展进程与结构关系。通过Web of Science核心合集数据库获取了3406篇在1986~2020年(截至2020年2月29日)间出版的驾驶风险研究相关英文文献,共涵盖8684位作者及6018个关键词,基于科学知识图谱对该领域文献进行梳理与分析。结果表明:驾驶风险领域的国外研究在驾驶人选择方面主要从年轻驾驶人、老年驾驶人、新手驾驶人及职业驾驶人的角度进行切入,重点围绕酒驾、药驾、分心驾驶及疲劳驾驶等主题开展研究。与国外研究相比,中国在分心驾驶、疲劳驾驶领域的研究相对丰富,而针对酒驾、药驾的研究试验手段较为单一,研究不够全面;在研究对象的选取上,有必要进一步增加老年驾驶人及新手驾驶人的深入研究,包括老年驾驶人适驾性评估与教育培训,以及新手驾驶人驾照分级制度的可行性探索。在研究方法方面,国外常见研究方法包括问卷调查、驾驶模拟器试验、实车试验以及自然驾驶研究等,而中国在自然驾驶研究领域尚未充分开发利用;未来应考虑多种方法相结合并从不同角度促进对驾驶行为及驾驶风险的全面理解。
