2021Unpublished venueRequires access

Lane Change Decision Making for Automated Driving

Tabea Blenk, Stephanie Cramer

Open publisher page 6 citations

Abstract

For the success of automated vehicles, in addition to legal, safety, and technical aspects, user acceptance and trust in automation systems are considered to have a significant impact. The driving style can decisively influence these factors. Besides driving dynamics, such as velocity and accelerations, tactical decisions (e.g. for lane changes) also define the driving style on highways. In order to get a better understanding of lane change behavior expected by passengers during automated driving, participants (N=35) determined and initiated the desired point in time to perform lane changes in a study under real highway driving conditions. Subsequently, a logistic regression analysis could determine the probability of a lane change considering different environmental variables as predictors. Thus, the most important factors influencing lane change decisions could be identified. The results indicate that for lane changes from the right to the middle lane as well as from the middle to the right lane, the preceding and approaching vehicle on the target lane as well as the preceding vehicle on the current lane have a significant influence on the lane change decision. In addition, vehicles entering the highway and presence of more than one preceding vehicle on the right lane were revealed as significant predictors for the lane change decision to the right. Contrarily, for the lane change decision to the left, the relative velocity to the preceding vehicle as well as a speed limit equal to the target velocity have decisive influence. The results give a first important insight for a user-centered automated lane change behavior. Following, individual aspects of these results can be considered to be evaluated more specifically.

About this research paper

What this paper is about

For the success of automated vehicles, in addition to legal, safety, and technical aspects, user acceptance and trust in automation systems are considered to have a significant impact. The driving style can decisively influence these factors. Besides driving dynamics, such as velocity and accelerations, tactical decisions (e.g. for lane changes) also define the driving style on highways. In order to get a better understanding of lane change behavior expected by passengers during automated driving, participants (N=35) determined and initiated the desired point in time to perform lane changes in a study under real highway driving conditions. Subsequently, a logistic regression analysis could determine the probability of a lane change considering different environmental variables as predictors. Thus, the most important factors influencing lane change decisions could be identified. The results indicate that for lane changes from the right to the middle lane as well as from the middle to the right lane, the preceding and approaching vehicle on the target lane as well as the preceding vehicle on the current lane have a significant influence on the lane change decision. In addition, vehicles entering the highway and presence of more than one preceding vehicle on the right lane were revealed as significant predictors for the lane change decision to the right. Contrarily, for the lane change decision to the left, the relative velocity to the preceding vehicle as well as a speed limit equal to the target velocity have decisive influence. The results give a first important insight for a user-centered automated lane change behavior. Following, individual aspects of these results can be considered to be evaluated more specifically.

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Available abstract

For the success of automated vehicles, in addition to legal, safety, and technical aspects, user acceptance and trust in automation systems are considered to have a significant impact. The driving style can decisively influence these factors. Besides driving dynamics, such as velocity and accelerations, tactical decisions (e.g. for lane changes) also define the driving style on highways. In order to get a better understanding of lane change behavior expected by passengers during automated driving, participants (N=35) determined and initiated the desired point in time to perform lane changes in a study under real highway driving conditions. Subsequently, a logistic regression analysis could determine the probability of a lane change considering different environmental variables as predictors. Thus, the most important factors influencing lane change decisions could be identified. The results indicate that for lane changes from the right to the middle lane as well as from the middle to the right lane, the preceding and approaching vehicle on the target lane as well as the preceding vehicle on the current lane have a significant influence on the lane change decision. In addition, vehicles entering the highway and presence of more than one preceding vehicle on the right lane were revealed as significant predictors for the lane change decision to the right. Contrarily, for the lane change decision to the left, the relative velocity to the preceding vehicle as well as a speed limit equal to the target velocity have decisive influence. The results give a first important insight for a user-centered automated lane change behavior. Following, individual aspects of these results can be considered to be evaluated more specifically.

Key concepts: Automation, Computer science, Point (geometry), Transport engineering, Simulation, Engineering, Mathematics, Mechanical engineering

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