- #Vehicle accident simulation drivers#
- #Vehicle accident simulation driver#
- #Vehicle accident simulation series#
#Vehicle accident simulation driver#
įuzzy relevant models have been proposed to simulate real-world traffic situations considering varied driver types and thus provide optimal traffic control strategies for the purpose of ensuring traffic safety and efficiency (i.e., with minimal waiting time, short queue length, etc.). Some scholars analyzed the relationship between other influencing factors and car safety, such as the speed relation among adjacent vehicles. proposed a rear-end collision behavior model considering the individual differences of drivers. established a car-following model with minimum safety distance for three typical traffic states. By considering influence of driver individual differences, vehicle braking performance, and driving states, Zhang et al. Tang and Xia analyzed a variety of factors that affect the driver reaction time by using fuzzy mathematics theory and then proposed a novel model to estimate driver reaction time.
#Vehicle accident simulation series#
Tang and Xia implemented a series of experiments to measure the reaction time of four different driver types and further studied its impact on the minimal safety distance of preventing rear-end collision.
#Vehicle accident simulation drivers#
Many studies have been conducted to analyze the relationship between traffic safety and drivers characteristic, including driver personality, physical fitness, driver distraction, etc. Similar research studies can be found in. firstly studied driver behavior differences and empirical judgment ratio distributions in an abnormal traffic scenario and then proposed a car-following model for estimating the minimum safety distance for the emergency evacuation vehicle. Spyropoulou proposed a novel vehicle safety distance model which considered the constraints of vehicle speed variation, minimal safety distance, etc. proposed a minimum safety car-following model under different driver states by considering the vehicle acceleration/deceleration in vehicle braking process. Zhang and Hao deeply analyzed the resistance influence on the minimum safety distance, which was involved with air resistance, road resistance, vehicle wheel rolling resistance, etc. Several studies have been conducted to establish minimum safety following distance model with vehicle kinematic data (i.e., driver types, vehicle acceleration/decelerations distributions, etc.). Note that quantifying such vehicle rear end displacement considering driver types is not easy, which is indeed a hot topic in the transportation safety research community. More specifically, the aggressive drivers require smaller displacement between neighboring vehicles when traveling on road, while the mild drivers are likely to keep sufficient vehicle headway for the purpose of avoiding potential traffic accidents. The driver response time for different driver types for taking actions against dangerous driving situations is varied, which has attracted a lot of research attentions. It is observed that varied driver characteristics (e.g., age, gender, experience, and speed of response) can impose different impact on individual vehicle maneuver procedure. Indeed, over 80% traffic accidents on roads can be ascribed to driver misconduct (e.g., answering cell phone, smoking, and taking naps). The previous studies have shown that drivers are assumed to the take the major responsibility for the traffic accidents (i.e., a few accidents are triggered by vehicle defects). An adverse effect of is increasing traffic accidents on roadways which greatly imperil traffic safety and efficiency. Private car has become affordable for public with the quick development of economic and promotion of manufacture technique. The findings can help traffic regulation departments issue early warnings to avoid potential traffic accidents on roads. The experimental results have shown that our proposed model obtained more accurate vehicle safety distance with varied traffic kinematic conditions (i.e., different traffic states, varied driver types, etc.). Finally, the improved car-following safety model is established based on different reaction time. Secondly, three main factors affecting driving safety are analyzed by using fuzzy theory, and the new calculation method of the reaction time is obtained. Then, on the basis of this, drivers are classified according to reaction time. Firstly, the factors affecting driving drivers’ characteristics, such as driver age, gender, and driving experience are analyzed. However, most of the existing rear-end collision models do not fully consider the subjective factor such as the driver. For different types of drivers or different driving environments, the required safety distance is different. The reasonable distance between adjacent cars is very crucial for roadway traffic safety.