Analysis of Stopping Behavior at Rural T-Intersections Using Naturalistic Driving Study Data

Rural intersections account for around 30% of crashes in rural areas and 6% of all fatal crashes, representing a significant but poorly understood safety problem. Crashes at rural intersections are also problematic since high speeds on intersection approaches are present which can exacerbate the impact of a crash. Additionally, rural areas are often underserved with EMS services which can further contribute to negative crash outcomes. This paper describes an analysis of driver stopping behavior at rural T-intersections using the SHRP 2 Naturalistic Driving Study data. Type of stop was used as a safety surrogate measure using full/rolling stops compared to non-stops. Time series traces were obtained for 157 drivers at 87 unique intersections resulting in 1277 samples at the stop controlled approach for T-intersections. Roadway (i.e. number of lanes, presence of skew, speed limit, presence of stop bar or other traffic control devices), driver (age, gender, speeding), and environmental characteristics (time of day, presence of rain) were reduced and included as independent variables. Results of a logistic regression model indicated drivers were less likely to stop during the nighttime. However presence of intersection lighting increased the likelihood of full/rolling stops. Presence of intersection skew was shown to negatively impact stopping behavior. Additionally drivers who were traveling over the posted speed limit upstream of the intersection approach were less likely to stop at the approach stop sign.

An investigation on the link between driver demographic characteristics and distracted driving by using the SHRP 2 naturalistic driving data

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.

Review and assessment of different perspectives of vehicle-pedestrian conflicts and crashes:Passive and active analysis approaches

The importance of investigating pedestrian safety has been evaluated repeatedly in safety studies.The present study attempts to evaluate the various methods used by previous researchers in a hierarchical process,to determine the characteristics,advantages,and limitations of each method.Two general analysis approaches(passive and active) were taken into account to categorize 169 previous types of research.In the passive approach,the studied methods were those based on crash databases,questionnaires,and post-crash field observation data;while,in the active approach,the studied methods were those based on driving simulations and videography.The result of the passive approach reveals that road users’ features and road characteristics(crash database studies),and error,lapses,intentional and unintentional violations(questionnaire studies) by them were among the most important causes of crashes and conflicts.Furthermore,road users’ distractions also reported a set of factors affecting the possibility of conflicts and crashes based on postcrash field observation studies.Also,results of the active approach showed that risky behaviors are the most important factor in threatening pedestrian safety such as unauthorized speeding,non-compliance with traffic law,unauthorized overtaking by drivers,and illegal crossing.Furthermore,risk perception and decision-making processes are the mostimportant bond between the attitude and behavior of road users in dangerous driving situations.Examining studies through passive approach would lead to identifying the causes of crashes,recognizing the attitude of road users towards safety,and determining road users’ behavioral patterns in certain situations,while the active approach has led to a more detailed understanding of behaviors and attitudes of road users.The inference of the findings obtained in this study will lead to a better understanding of the behavior of road users for studies on advanced driving assistance systems(ADAS).