For autonomous vehicles (AVs) to receive general acceptance, society must have a positive perception about their safety impact on vulnerable road users. Using data from a statewide random-digit-dialing telephone surve...For autonomous vehicles (AVs) to receive general acceptance, society must have a positive perception about their safety impact on vulnerable road users. Using data from a statewide random-digit-dialing telephone survey of 1001 adults, this paper examines how New Jersey residents perceive the safety impact of AVs on pedestrians, bicyclists, and people with ambulatory disability. </span><span style="font-family:Verdana;">It uses a combination of confirmatory factor analysis and ordered probit</span><span style="font-family:Verdana;"> models. Confirmatory factor analysis is used to create latent variables on socioeconomic status and built environment. Three ordered probit models are used to examine people’s perception of AV safety impact on each of the three pop</span><span style="font-family:Verdana;">ulation groups. The models also examine how frequent walkers, bicyclists, </span><span style="font-family:Verdana;">and people with ambulatory disability perceive their own safety as well as the safety of the other two groups. All three models examine the effect of familiarity with AV, gender, age, income, education, race, ethnicity, number of vehicles in household, political party affiliation, as well as built environment and socioeconomic status of the municipalities where the survey respondents live. The analysis showed that men, people with familiarity with the AV concept, Democrats, bicyclists, and people with high household income generally have a positive perception about the safety impact of AVs. While frequent walkers are ambivalent about their own safety as pedestrians, bicyclists have a positive perception about their own safety and the safety of pedestrians, whereas people with ambulatory disability have a strong negative perception about their own safety. The models did not show statistically significant effects of socioeconomic status or built environment of municipalities on AV safety perception.展开更多
Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada...Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.展开更多
Purpose–To support the standardized evaluation of bicyclist automatic emergency braking(AEB)systems,test scenarios,test procedures and test system hardware and software tools have been investigated and developed by t...Purpose–To support the standardized evaluation of bicyclist automatic emergency braking(AEB)systems,test scenarios,test procedures and test system hardware and software tools have been investigated and developed by the Transportation Active Safety Institute(TASI)at Indiana University-Purdue University Indianapolis.This paper aims to focus on the development of test scenarios and bicyclist surrogate for evaluating vehicle–bicyclist AEB systems.Design/methodology/approach–The harmonized general estimates system(GES)/FARS 2010-2011 crash data and TASI 110-car naturalistic driving data(NDD)are used to determine the crash geometries and environmental factors of crash scenarios including lighting conditions,vehicle speeds,bicyclist speeds,etc.A surrogate bicyclist including a bicycle rider and a bicycle surrogate is designed to match the visual and radar characteristics of bicyclists in the USA.A bicycle target is designed with both leg pedaling and wheel rotation to produce proper micro-Doppler features and generate realistic motion for camera-based AEB systems.Findings–Based on the analysis of the harmonized GES/FARS crash data,five crash scenarios are recommended for performance testing of bicyclist AEB systems.Combined with TASI 110-car naturalistic driving data,the crash environmental factors including lighting conditions,obscuring objects,vehicle speed and bicyclist speed are determined.The surrogate bicyclist was designed to represent the visual and radar characteristics of the real bicyclists in the USA.The height of the bicycle rider mannequin is 173 cm,representing the weighted height of 50th percentile US male and female adults.The size and shape of the surrogate bicycle were determined as 26-inch wheel and mountain/road bicycle frame,respectively.Both leg pedaling motion and wheel rotation are suggested to produce proper micro-Doppler features and support the camera-based AEB systems.Originality/value–The results have demonstrated that the developed scenarios,test procedures and bicyclist surrogate will provide effective objective methods and necessary hardware and software tools for the evaluation and validation of bicyclist AEB systems.This is crucial for the development of advanced driver assistance systems.展开更多
文摘For autonomous vehicles (AVs) to receive general acceptance, society must have a positive perception about their safety impact on vulnerable road users. Using data from a statewide random-digit-dialing telephone survey of 1001 adults, this paper examines how New Jersey residents perceive the safety impact of AVs on pedestrians, bicyclists, and people with ambulatory disability. </span><span style="font-family:Verdana;">It uses a combination of confirmatory factor analysis and ordered probit</span><span style="font-family:Verdana;"> models. Confirmatory factor analysis is used to create latent variables on socioeconomic status and built environment. Three ordered probit models are used to examine people’s perception of AV safety impact on each of the three pop</span><span style="font-family:Verdana;">ulation groups. The models also examine how frequent walkers, bicyclists, </span><span style="font-family:Verdana;">and people with ambulatory disability perceive their own safety as well as the safety of the other two groups. All three models examine the effect of familiarity with AV, gender, age, income, education, race, ethnicity, number of vehicles in household, political party affiliation, as well as built environment and socioeconomic status of the municipalities where the survey respondents live. The analysis showed that men, people with familiarity with the AV concept, Democrats, bicyclists, and people with high household income generally have a positive perception about the safety impact of AVs. While frequent walkers are ambivalent about their own safety as pedestrians, bicyclists have a positive perception about their own safety and the safety of pedestrians, whereas people with ambulatory disability have a strong negative perception about their own safety. The models did not show statistically significant effects of socioeconomic status or built environment of municipalities on AV safety perception.
文摘Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.
文摘Purpose–To support the standardized evaluation of bicyclist automatic emergency braking(AEB)systems,test scenarios,test procedures and test system hardware and software tools have been investigated and developed by the Transportation Active Safety Institute(TASI)at Indiana University-Purdue University Indianapolis.This paper aims to focus on the development of test scenarios and bicyclist surrogate for evaluating vehicle–bicyclist AEB systems.Design/methodology/approach–The harmonized general estimates system(GES)/FARS 2010-2011 crash data and TASI 110-car naturalistic driving data(NDD)are used to determine the crash geometries and environmental factors of crash scenarios including lighting conditions,vehicle speeds,bicyclist speeds,etc.A surrogate bicyclist including a bicycle rider and a bicycle surrogate is designed to match the visual and radar characteristics of bicyclists in the USA.A bicycle target is designed with both leg pedaling and wheel rotation to produce proper micro-Doppler features and generate realistic motion for camera-based AEB systems.Findings–Based on the analysis of the harmonized GES/FARS crash data,five crash scenarios are recommended for performance testing of bicyclist AEB systems.Combined with TASI 110-car naturalistic driving data,the crash environmental factors including lighting conditions,obscuring objects,vehicle speed and bicyclist speed are determined.The surrogate bicyclist was designed to represent the visual and radar characteristics of the real bicyclists in the USA.The height of the bicycle rider mannequin is 173 cm,representing the weighted height of 50th percentile US male and female adults.The size and shape of the surrogate bicycle were determined as 26-inch wheel and mountain/road bicycle frame,respectively.Both leg pedaling motion and wheel rotation are suggested to produce proper micro-Doppler features and support the camera-based AEB systems.Originality/value–The results have demonstrated that the developed scenarios,test procedures and bicyclist surrogate will provide effective objective methods and necessary hardware and software tools for the evaluation and validation of bicyclist AEB systems.This is crucial for the development of advanced driver assistance systems.
