Abstract
To make intelligent vehicles obtain human drivers’ steering characteristic, a new single point preview-based human-like driver model is proposed, which contains a preview decision module and a steering wheel angle calculation module. Enlightened by the visual gaze mechanism of human drivers when passing a curved road, the preview decision module is established using Takagi-Sugeno fuzzy inference system (T-S FIS) to adaptively adjust the preview point position in both longitudinal and lateral direction, and the steering angle calculation module would use the adjusted preview point to generate steering command based on pure pursuit algorithm. Ant colony optimization (ACO) method is used to optimize the fuzzy rules in the preview decision module according to the similarity of trajectories between the proposed driver model and human drivers. The proposed human-like driver model is verified on a two-lane urban curved road. Five experienced human drivers’ driving trajectories under different speeds are collected for the verification. After the preview decision module optimization done in the PreScan/Simulink simulation platform, the proposed human-like driver model shows higher similarity with experienced human drivers than the driver model with fixed preview distance or the driver model only with changeable longitudinal preview distance.
Highlights
With the developments in both artificial intelligence and sensor technology, vehicles with high-level driver assistance system or even automated vehicles (AVs) would become available in the near future, and there is no doubt that the vehicles manipulated by human drivers and AVs would share the road together [1]
Combined the new preview decision module with a steering angle calculation module based on pure pursuit algorithm, a new single point preview-based human-like driver model is proposed
Learning form the researches of human drivers’ visual gaze mechanism, a new single point preview based human-like driver model is proposed which contains a preview decision module based on Takagi-Sugeno fuzzy inference system (T-S fuzzy inference system (FIS)) and a steering angle calculation module based on pure pursuit algorithm
Summary
With the developments in both artificial intelligence and sensor technology, vehicles with high-level driver assistance system or even automated vehicles (AVs) would become available in the near future, and there is no doubt that the vehicles manipulated by human drivers and AVs would share the road together [1]. SINGLE POINT PREVIEW-BASED HUMAN-LIKE DRIVER MODEL Different settings of preview reference can greatly influence a driver model’s steering control characteristic and tracking performance. Learning form the researches of human drivers’ visual gaze mechanism, a new single point preview based human-like driver model is proposed which contains a preview decision module based on T-S FIS and a steering angle calculation module based on pure pursuit algorithm. Gaze mechanism researches of human drivers [24], [25], [28], we have made following assumptions of preview point position adjustment mechanism under constant vehicle speed: 1) Preview distance (D) should be adjusted according to current vehicle state (current tracking error ev and current heading error eα, the definition has been given in Figure 2), which represent the longitudinal direction adjustment of the preview point. 3) LD should be adjusted according to D, when the vehicle passing a curve road
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