Abstract
In order to promote traffic safety at freeway off-ramps, this paper designed a hybrid model to identify a lane-changing with vision technology. The unmanned aerial vehicle was used to collect video stream data at five off-ramps for Xi'an Raocheng freeway during weekdays. The positional information-of-an individual vehicle is recorded at a frequency of 5 Hz. Each trajectory is composed of 30 positional records and all trajectories are divided into lane-changing and lane-keeping units. Features such as lateral driving speed, lane departure, and the lane deviation angle extracted from trajectory records are related to the lane-changing behaviors. We develop a hybrid model of the Gaussian Mixture Model and the Continuous Hidden Markov Model to identify lane-changing behaviors at off-ramps with these features. Basing on test set, we conduct a test for the hybrid model and the result shows that the prediction accuracy of the proposed model is as high as 94.4% for lane-changing behavior and 93.6% for lane-keeping behavior.
Highlights
Numerous traffic accidents caused by improper driving behaviors, resulting in casualties and extensive property losses
More than 70% of road traffic accidents are caused by unsafe driving behaviors according to the annual road accidents report in China 2016 [1]. 4% to 7% of road traffic accidents in China are caused by improper lane-changing behavior [2]
The paper presents a hybrid model for the lane-changing prediction at freeway off-ramps
Summary
Numerous traffic accidents caused by improper driving behaviors, resulting in casualties and extensive property losses. 4% to 7% of road traffic accidents in China are caused by improper lane-changing behavior [2]. More than 70% of road traffic accidents are caused by unsafe driving behaviors according to the annual road accidents report in China 2016 [1]. This situation is more exiguous in the US, with 27% of accidents being the result of faulty lane-changing [3]. The arrangement of off-ramps affects driving behaviors including the number of lanes, length of the speed-change lane, geometry design, signs placement, gaps acceptance and so on [6]–[9].
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