AS
A.L.A. Sevenster
info
Please Note
<p>This page displays the records of the person named above and is not linked to a unique person identifier. This record may need to be merged to a profile.</p>
2 records found
1
Overtaking on two-lane roads can lead to increased collision risks due to drivers' errors in evaluating whether or not to accept the gap to the vehicle in the opposite lane. Understanding these gap acceptance decisions can help mitigate the risks associated with overtaking. Previous research on overtaking has focused on the factors influencing gap acceptance decisions. However, the cognitive processes underlying gap acceptance decisions remain poorly understood. Previous studies have shown that response time (i.e. the time it takes the driver to evaluate the gap and make a decision) can provide valuable insights into the cognitive processes during gap acceptance decisions, in particular in pedestrian crossing and left turn decisions. However, the more complex nature of the overtaking maneuver renders it difficult to measure response times in overtaking. As a result, response times in overtaking have not been investigated, thereby limiting our understanding of overtaking behavior. To address this gap, in this paper we propose a method to measure response time in drivers' overtaking decisions and demonstrate this method in a driving simulator experiment (N=25). Specifically, we analyzed the effect of distance to the oncoming vehicle and speed of the ego vehicle on response time in accepted and rejected gaps. We found that response times for rejected gaps were on average longer than for accepted gaps. The response times increased with the distance gap and decreased with the initial velocity of the ego vehicle. We conclude that using the proposed method for measuring response time can give insight in the way drivers make gap acceptance decisions during overtaking. These results provide basis for cognitive process models that can help further understand overtaking decisions.
...
Overtaking on two-lane roads can lead to increased collision risks due to drivers' errors in evaluating whether or not to accept the gap to the vehicle in the opposite lane. Understanding these gap acceptance decisions can help mitigate the risks associated with overtaking. Previous research on overtaking has focused on the factors influencing gap acceptance decisions. However, the cognitive processes underlying gap acceptance decisions remain poorly understood. Previous studies have shown that response time (i.e. the time it takes the driver to evaluate the gap and make a decision) can provide valuable insights into the cognitive processes during gap acceptance decisions, in particular in pedestrian crossing and left turn decisions. However, the more complex nature of the overtaking maneuver renders it difficult to measure response times in overtaking. As a result, response times in overtaking have not been investigated, thereby limiting our understanding of overtaking behavior. To address this gap, in this paper we propose a method to measure response time in drivers' overtaking decisions and demonstrate this method in a driving simulator experiment (N=25). Specifically, we analyzed the effect of distance to the oncoming vehicle and speed of the ego vehicle on response time in accepted and rejected gaps. We found that response times for rejected gaps were on average longer than for accepted gaps. The response times increased with the distance gap and decreased with the initial velocity of the ego vehicle. We conclude that using the proposed method for measuring response time can give insight in the way drivers make gap acceptance decisions during overtaking. These results provide basis for cognitive process models that can help further understand overtaking decisions.
Overtaking on two-lane roads can cause dangerous situations, due to drivers’ errors during the gap acceptance decision. Understanding gap acceptance decisions can help mitigate these situations. Response time (i.e. the time it takes the driver to evaluate the gap and make a decision) has been shown to provide valuable insights into the cognitive processes during gap acceptance decisions in pedestrian crossing and left turn decisions. However, for overtaking, previous studies have not investigated the response time.
I investigated how factors that play a role in gap acceptance decisions during overtaking (namely, size of the gap and the drivers’ velocity) influence the response time. I also studied the change of the drivers' velocity during the decision process. I proposed a novel method to measure the response time in drivers' overtaking decisions, and conducted an experiment to demonstrate the usefulness of the method. 25 participants were presented with multiple overtaking situations in a driving simulator experiment, with varying distance gaps. I analyzed how the probability of gap acceptance varied with the distance gap and participants’ velocity at the start of the overtaking situation using a generalized logistic mixed model. I also analyzed how the response time varied with the distance gap, participants’ velocity and the decision outcome using a linear mixed model. Lastly, I analyzed if the velocity changed between the start and the end of the decision process and whether there was a relation between the decision outcome and the distance gap and the velocity change, using a linear mixed model.
The probability of accepting a gap increased significantly with the distance gap and the velocity of the participant. The response times for rejected gaps were on average 0.7s longer than accepted gaps. The response time increased with the distance gap (42ms per 10m), but decreased with the velocity (-92ms per 1m/s). The velocity changed differently between the decision processes leading to either decisions, with an average difference of 4 m/s.
Using the proposed method, I found that the factors which influence the outcome of the decision, also influence the response time. The dependence of response time on the distance gap and participants’ velocity could be explained by the speed-accuracy tradeoff or the difficulty of the decision. Furthermore, it was shown that the drivers already adapt their velocity during the decision process, instead of after they have made their decision. So, I can conclude that using the proposed method for measuring response time can give insight in the way drivers make gap acceptance decisions during overtaking. My results provide basis for cognitive process models that can help further understand the results and are capable of predicting decision outcomes and response times. ...
I investigated how factors that play a role in gap acceptance decisions during overtaking (namely, size of the gap and the drivers’ velocity) influence the response time. I also studied the change of the drivers' velocity during the decision process. I proposed a novel method to measure the response time in drivers' overtaking decisions, and conducted an experiment to demonstrate the usefulness of the method. 25 participants were presented with multiple overtaking situations in a driving simulator experiment, with varying distance gaps. I analyzed how the probability of gap acceptance varied with the distance gap and participants’ velocity at the start of the overtaking situation using a generalized logistic mixed model. I also analyzed how the response time varied with the distance gap, participants’ velocity and the decision outcome using a linear mixed model. Lastly, I analyzed if the velocity changed between the start and the end of the decision process and whether there was a relation between the decision outcome and the distance gap and the velocity change, using a linear mixed model.
The probability of accepting a gap increased significantly with the distance gap and the velocity of the participant. The response times for rejected gaps were on average 0.7s longer than accepted gaps. The response time increased with the distance gap (42ms per 10m), but decreased with the velocity (-92ms per 1m/s). The velocity changed differently between the decision processes leading to either decisions, with an average difference of 4 m/s.
Using the proposed method, I found that the factors which influence the outcome of the decision, also influence the response time. The dependence of response time on the distance gap and participants’ velocity could be explained by the speed-accuracy tradeoff or the difficulty of the decision. Furthermore, it was shown that the drivers already adapt their velocity during the decision process, instead of after they have made their decision. So, I can conclude that using the proposed method for measuring response time can give insight in the way drivers make gap acceptance decisions during overtaking. My results provide basis for cognitive process models that can help further understand the results and are capable of predicting decision outcomes and response times. ...
Overtaking on two-lane roads can cause dangerous situations, due to drivers’ errors during the gap acceptance decision. Understanding gap acceptance decisions can help mitigate these situations. Response time (i.e. the time it takes the driver to evaluate the gap and make a decision) has been shown to provide valuable insights into the cognitive processes during gap acceptance decisions in pedestrian crossing and left turn decisions. However, for overtaking, previous studies have not investigated the response time.
I investigated how factors that play a role in gap acceptance decisions during overtaking (namely, size of the gap and the drivers’ velocity) influence the response time. I also studied the change of the drivers' velocity during the decision process. I proposed a novel method to measure the response time in drivers' overtaking decisions, and conducted an experiment to demonstrate the usefulness of the method. 25 participants were presented with multiple overtaking situations in a driving simulator experiment, with varying distance gaps. I analyzed how the probability of gap acceptance varied with the distance gap and participants’ velocity at the start of the overtaking situation using a generalized logistic mixed model. I also analyzed how the response time varied with the distance gap, participants’ velocity and the decision outcome using a linear mixed model. Lastly, I analyzed if the velocity changed between the start and the end of the decision process and whether there was a relation between the decision outcome and the distance gap and the velocity change, using a linear mixed model.
The probability of accepting a gap increased significantly with the distance gap and the velocity of the participant. The response times for rejected gaps were on average 0.7s longer than accepted gaps. The response time increased with the distance gap (42ms per 10m), but decreased with the velocity (-92ms per 1m/s). The velocity changed differently between the decision processes leading to either decisions, with an average difference of 4 m/s.
Using the proposed method, I found that the factors which influence the outcome of the decision, also influence the response time. The dependence of response time on the distance gap and participants’ velocity could be explained by the speed-accuracy tradeoff or the difficulty of the decision. Furthermore, it was shown that the drivers already adapt their velocity during the decision process, instead of after they have made their decision. So, I can conclude that using the proposed method for measuring response time can give insight in the way drivers make gap acceptance decisions during overtaking. My results provide basis for cognitive process models that can help further understand the results and are capable of predicting decision outcomes and response times.
I investigated how factors that play a role in gap acceptance decisions during overtaking (namely, size of the gap and the drivers’ velocity) influence the response time. I also studied the change of the drivers' velocity during the decision process. I proposed a novel method to measure the response time in drivers' overtaking decisions, and conducted an experiment to demonstrate the usefulness of the method. 25 participants were presented with multiple overtaking situations in a driving simulator experiment, with varying distance gaps. I analyzed how the probability of gap acceptance varied with the distance gap and participants’ velocity at the start of the overtaking situation using a generalized logistic mixed model. I also analyzed how the response time varied with the distance gap, participants’ velocity and the decision outcome using a linear mixed model. Lastly, I analyzed if the velocity changed between the start and the end of the decision process and whether there was a relation between the decision outcome and the distance gap and the velocity change, using a linear mixed model.
The probability of accepting a gap increased significantly with the distance gap and the velocity of the participant. The response times for rejected gaps were on average 0.7s longer than accepted gaps. The response time increased with the distance gap (42ms per 10m), but decreased with the velocity (-92ms per 1m/s). The velocity changed differently between the decision processes leading to either decisions, with an average difference of 4 m/s.
Using the proposed method, I found that the factors which influence the outcome of the decision, also influence the response time. The dependence of response time on the distance gap and participants’ velocity could be explained by the speed-accuracy tradeoff or the difficulty of the decision. Furthermore, it was shown that the drivers already adapt their velocity during the decision process, instead of after they have made their decision. So, I can conclude that using the proposed method for measuring response time can give insight in the way drivers make gap acceptance decisions during overtaking. My results provide basis for cognitive process models that can help further understand the results and are capable of predicting decision outcomes and response times.