Driver Behavior Analysis and Prediction Models: A Survey
نویسندگان
چکیده
In today's life, every human is in hurry to reach their destination like home, office, college, shopping mall, restaurant, etc as quickly as possible. To reach their destination quickly people use vehicles on road use and drive them in faster mode which results in road accidents. Driver behavior is a major cause for the road accidents. To address this problem, drive behavior analysis and prediction models need to be developed. In this paper we have discussed some of existing driver behavior models. These models are classified as two types: Driver behavior analysis and driver behavior prediction models. In this paper we have carried out a detailed survey about the driver behavior analysis models and the driver behavior prediction models. Keywords-CA=Collision Avoidance, OBD= On Board Diagnostic, ANFIS= adaptive neuro fuzzy inference system, NHTSA=National Highway Traffic Safety Administration
منابع مشابه
MANFIS Based Modeling and Prediction of the Driver-Vehicle Unit Behavior in Overtaking Scenarios
Overtaking a slow lead vehicle is a complex maneuver because of the variety of overtaking conditions and driver behavior. In this study, two novel prediction models for overtaking behavior are proposed. These models are derived based on multi-input multi-output adaptive neuro-fuzzy inference system (MANFIS). They are validated at microscopic level and are able to simulate and predict the fut...
متن کاملUsing the Reaction Delay as the Driver Effects in the Development of Car-Following Models
Car-following models, as the most popular microscopic traffic flow modeling, is increasingly being used by transportation experts to evaluate new Intelligent Transportation System (ITS) applications. A number of factors including individual differences of age, gender, and risk-taking behavior, have been found to influence car-following behavior. This paper presents a novel idea to calculate ...
متن کاملFunctional-Coefficient Autoregressive Model and its Application for Prediction of the Iranian Heavy Crude Oil Price
Time series and their methods of analysis are important subjects in statistics. Most of time series have a linear behavior and can be modelled by linear ARIMA models. However, some of realized time series have a nonlinear behavior and for modelling them one needs nonlinear models. For this, many good parametric nonlinear models such as bilinear model, exponential autoregressive model, threshold...
متن کاملLane Change Trajectory Model Considering the Driver Effects Based on MANFIS
The lane change maneuver is among the most popular driving behaviors. It is also the basic element of important maneuvers like overtaking maneuver. Therefore, it is chosen as the focus of this study and novel multi-input multi-output adaptive neuro-fuzzy inference system models (MANFIS) are proposed for this behavior. These models are able to simulate and predict the future behavior of a Dri...
متن کاملPrediction of Driver’s Accelerating Behavior in the Stop and Go Maneuvers Using Genetic Algorithm-Artificial Neural Network Hybrid Intelligence
Research on vehicle longitudinal control with a stop and go system is presently one of the most important topics in the field of intelligent transportation systems. The purpose of stop and go systems is to assist drivers for repeatedly accelerate and stop their vehicles in traffic jams. This system can improve the driving comfort, safety and reduce the danger of collisions and fuel consumption....
متن کامل