Factors modifying the likelihood of speeding behaviors based on naturalistic driving data

Pérez, Miguel Á.; Sears, Edie; Valente, Jacob T.; Huang, Wenyan; Sudweeks, Jeremy

doi:10.1016/j.aap.2021.106267

Cited by 22 publications

(7 citation statements)

References 23 publications

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“…Based on speeding behaviors extracted from vehicles' GPS trajectory data, researchers in [41] classified drivers into three categories: restrained, moderate, and belligerent. Researchers also utilized existing datasets to investigate the effects of gender and age on speeding [42]. Moreover, in [43], researchers demonstrated a model that detects lane-changing maneuvers using the SHRP2 dataset.…”

Section: Introductionmentioning

confidence: 99%

Investigating the Effect of Social and Cultural Factors on Drivers in Malaysia: A Naturalistic Driving Study

Al-Hussein

Kiah

Por

et al. 2021

IJERPH

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Road accidents are increasing every year in Malaysia, and it is always challenging to collect reliable pre-crash data in the transportation community. Existing studies relied on simulators, police crash reports, questionnaires, and surveys to study Malaysia’s drivers’ behavior. Researchers previously criticized such methods for being biased and unreliable. To fill in the literature gap, this study presents the first naturalistic driving study in Malaysia. Thirty drivers were recruited to drive an instrumented vehicle for 750 km while collecting continuous driving data. The data acquisition system consists of various sensors such as OBDII, lidar, ultrasonic sensors, IMU, and GPS. Irrelevant data were filtered, and experts helped identify safety criteria regarding multiple driving metrics such as maximum acceptable speed limits, safe accelerations, safe decelerations, acceptable distances to vehicles ahead, and safe steering behavior. These thresholds were used to investigate the influence of social and cultural factors on driving in Malaysia. The findings show statistically significant differences between drivers based on gender, age, and cultural background. There are also significant differences in the results for those who drove on weekends rather than weekdays. The study presents several recommendations to various public and governmental sectors to help prevent future accidents and improve traffic safety.

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Section: Introductionmentioning

confidence: 99%

Investigating the Effect of Social and Cultural Factors on Drivers in Malaysia: A Naturalistic Driving Study

Al-Hussein

Kiah

Por

et al. 2021

IJERPH

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“…Similar to excessive acceleration, speeding may have been less influenced by the RoadCoach feedback because older drivers are less likely to engage in speeding behavior. Older drivers (i.e., aged 80+) tend to speed far less frequently than young drivers (i.e., aged 16 to 24) who have been shown to be 1.5 times more likely to speed than their older counterparts ( 31 ). An age difference of older drivers (i.e., aged 60 to 70) having fewer speeding events compared with younger drivers (i.e., aged 20 to 30) has also been shown to consistently hold even when controlling for driver sex ( 18 ).…”

Section: Discussionmentioning

confidence: 97%

Multistate Pilot Study Evaluating the Short-Term Efficacy of a Smartphone-Based Older Driver Support System on Modifying Risky Driving Behaviors

Morris

Tian

Libby

et al. 2022

Transportation Research Record: Journal of the Transportation R

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Older drivers are most at risk of serious and fatal injury in crashes per vehicle mile driven compared with other age groups owing to a combination of cognitive decline and increased fragility. A smartphone coaching application targeting risky driving behaviors (e.g., speeding, hard braking), was iteratively designed to ensure older driver acceptance and usability. A 12-week field operational test examined driving performance of 28 drivers aged 65 to 78 from Kansas and Minnesota using the RoadCoach app and an ABA reversal design. Participants’ baseline driving behaviors were recorded for 3 weeks, followed by a 6-week experimental phase of real-time app coaching, and concluded with a 3-week baseline phase with no feedback provided. Compared with the pretreatment phase, there was a significant reduction in the rates of hard braking and stop sign violations associated with system use. A protection effect was observed through the posttreatment phase. Excessive speeding violations were not significantly different across the phases; however, there were modest declines in the proportion of miles traveled 15 mph above the speed limit in the posttreatment phase compared with the prior two phases. No significant effect was found for excessive acceleration and aggressive turning measures posttreatment, despite an observed increase in both rates during the treatment phase compared with pretreatment. Overall, the results indicate that the RoachCoach app may be an effective intervention to reduce several risky driving behaviors while in use and may result in prolonged behavior changes (i.e., reduced hard braking and stop sign violations) after treatment cessation.

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“…Factors such as vehicle power were also analyzed, but no significant correlation was found between speed choice and power, and we could not find reliable research on the impact of vehicle brand [31].…”

Section: Of 18mentioning

confidence: 99%

Impact of Driver, Vehicle, and Environment on Rural Road Crash Rate

Tajnik

Luin

2022

Sustainability

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There is an abundance of research on road-crash-influencing factors; however, it often relies on a limited subset of variables. The aim of this work was to analyze the significance of road-crash-influencing variables on rural roads and to estimate the crash frequencies during different conditions by introducing a holistic approach and analyzing a wide range of driver–vehicle–road–environment variables. The input data comprised long-term vehicle speed data, obtained using inductive loop traffic counters, and short-term data, obtained using a calibrated police radar. A combination of both was augmented with driver traits and meteorological conditions, gender, age, years possessing a driver’s license, crashes, vehicle, and environmental data. The crash data used for the analysis was based on police records. The results indicate that crash frequencies and driving speed have strong daily and weekly seasonality. The average hourly crash frequencies per kilometer driven during the week varied between 0.2 and 2.2 crashes per million km; the major cause was speeding, which contributed to nearly 32% of fatal crashes. Speed choice could be affected by alcohol-consuming drivers involved in crashes, as the percentage of drivers with any level of alcohol detected expressed daily and weekly patterns similar to those of crash frequencies per kilometer. Contrary to the highest relative crash frequency, which occurred during nighttime, the majority of daily crashes occurred during the afternoon peak hours; thus, the societal impact of crashes is the highest during the day.

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Factors modifying the likelihood of speeding behaviors based on naturalistic driving data

Cited by 22 publications

References 23 publications

Investigating the Effect of Social and Cultural Factors on Drivers in Malaysia: A Naturalistic Driving Study

Investigating the Effect of Social and Cultural Factors on Drivers in Malaysia: A Naturalistic Driving Study

Multistate Pilot Study Evaluating the Short-Term Efficacy of a Smartphone-Based Older Driver Support System on Modifying Risky Driving Behaviors

Impact of Driver, Vehicle, and Environment on Rural Road Crash Rate

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