Riding performance quantification method for motorcycles in terms of collision probability using the logit model

Abstract

In recent years, many Advanced Driver Assistance Systems (ADAS) have been proposed and introduced under the development of sensing technology and the issue of driving safety. But many kinds of ADASs have a specific threshold to control the alarm or some support. This is decided based on the experimental or mathematical calculations in terms of the optimization of the human-machine interface of each system. But almost all of the systems (especially warning systems) have just a single threshold value to issue the warning, and the driving performance of drivers fluctuating in real time is not considered. In this study, we proposed a quantification method of riding performance and performed the logistic regression analysis for the collision prediction model based on riding performance to optimize the warning threshold of ADAS. For this study, 64 test subjects (Mean age = 22.14, S.D. = 3.71) participated in the experiments using simulator. Experiments were conducted for three risk events (left-angle collision when a rider was driving on priority road or driving on non-priority road, and right turning collision) and dummy events with the same road environment without risky situations. We proposed a quantification method of riding performance through the total sum of a product of the generalized value of riding behaviours. We also proposed the logit model, which can be constructed in terms of the collision probabilities and riding performance, which is quantified using our proposed method. In the logit model, collision occurrence was used as the dependent variable and riding performance was used as the independent variable for logistic regression analysis to clarify the condition where the probability of collision increases. Finally, we proposed a concept of the setting method of threshold value for the warning timing of ADAS according to the rider's performance level based on collision probabilities during each riding performance.

The Development of Motorcycle Accident Models Based on Riders’ Characters

“…Much research has been carried out on driving performance for the development of four-wheeled vehicles, but the driving performance of two-wheeled vehicle drivers, who require higher driving performance when driving than four-wheeled vehicle drivers, has yet to be studied in detail. One study that tried to quantify motorbike driving performance concerning the possibility of a collision was conducted by researchers from the Japan Automobile Research Institute [25]. In their research, riding simulators were used to investigate riding behavior.…”

“…The HRT simulator is the tool chosen to represent the actual situation on the highway. Research has shown that driving simulators have proven to be excellent practical educational tools and are effective in training all motorists in safe driving techniques [25,26,36]. As shown in Figure 1, this motorcycle simulator is like a computer game, consisting of a computer with software, motorcycle handlebars, transmission pedals, seats, and a video monitor.…”

Prediction of Collision Avoidance Ability of Two-wheeled Vehicle Riders Using Driving Behaviors and Emotional States

“…These make the safety system for the four-wheeled vehicle easy to construct. In the previous study, the rider's driving performance was defined as an index then the defined index was applied to the four-wheel vehicle driving characteristic algorithm to propose an algorithm which is suitable for the characteristics of two-wheeled vehicles (6) . However, in order to apply this algorithm to the safety systems, problems such as the selection of an index suitable for the characteristics of the two-wheeled vehicles, real-time measurement, and low measurement cost are still remaining.…”