Approach to objective evaluation of driving behavior with ESC-interventions demonstrated by a lane change maneuver

Lane change (LC) is one of the main maneuvers in traffic flow. Many studies have estimated LC duration directly by using lane-based data. The current research presents an estimate of LC duration for overtaking maneuver in nonlane-based traffic flow. In this paper, the LC duration is estimated implicitly by modeling lateral speed and applying the length of required lateral movement to complete the LC maneuver. In lateral speed modeling, the local linear model tree is applied which consists of three variables: the initial lateral distance, longitudinal speed, and time to collision (TTC), which itself is a function of the relative speed of follower and the distance between the two vehicles. The initial lateral distance is the relative transverse distance from which the following vehicle initializes the LC. The range of lateral speed was estimated between 0.5 and 5 km/h, which resulted in the LC duration between 2.5 and 24 sec. The results indicate that the lateral and longitudinal speed would be inversely related, while the lateral speed and the initial transverse distance as well as TTC would be directly related. The findings also indicate that TTC can be assumed as the most important factor affecting lateral speed. TTC at 8 sec can be considered as the threshold for its effect on the LC duration since at longer TTCs, and the lateral speed has remained almost constant. When TTC is longer than 8 sec, it would not affect the LC duration.

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Winter Tires: Operating Conditions, Tire Characteristics and Vehicle Driving Behavior

Tire Science and Technology ◽

10.2346/1.3428961 ◽

2010 ◽

Vol 38 (2) ◽

pp. 119-136 ◽

Cited By ~ 6

Author(s):

Helge Dörrie ◽

Carsten Schröder ◽

Burkhard Wies

Keyword(s):

Vehicle Dynamics ◽

High Performance ◽

Development Process ◽

Objective Evaluation ◽

Driving Behavior ◽

Operating Conditions ◽

Dynamics Simulation ◽

Ambient Conditions ◽

Modern Development ◽

Track Surface

Abstract The modern development process of winter tires not only requires intense subjective and objective evaluation of the tire properties on the vehicle, but also requires knowledge about the influence of relevant tire characteristics on vehicle driving behavior. It is important to understand the influences of ambient conditions, such as temperature, track surface (asphalt vs corundum) and tire inflation pressure on tire behavior. Tire characteristic results of a parametric study, using a fully climate-controlled interior drum test stand will be presented. The effect on tire characteristics and the resulting vehicle behavior will be discussed using vehicle dynamics simulation. Furthermore the consequences for an optimal design of modern high performance winter tires will be presented.

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Effects of Marking Automated Vehicles on Human Drivers on Highways

Information ◽

10.3390/info11060286 ◽

2020 ◽

Vol 11 (6) ◽

pp. 286 ◽

Cited By ~ 2

Author(s):

Tanja Fuest ◽

Alexander Feierle ◽

Elisabeth Schmidt ◽

Klaus Bengler

Keyword(s):

Road Traffic ◽

Driving Behavior ◽

Sensor Technology ◽

Lane Change ◽

Objective Data ◽

Automated Vehicles ◽

Traffic Jam ◽

Automated Vehicle ◽

Time Headway ◽

First Time

Due to the short range of the sensor technology used in automated vehicles, we assume that the implemented driving strategies may initially differ from those of human drivers. Nevertheless, automated vehicles must be able to move safely through manual road traffic. Initially, they will behave as carefully as human learners do. In the same way that driving-school vehicles tend to be marked in Germany, markings for automated vehicles could also prove advantageous. To this end, a simulation study with 40 participants was conducted. All participants experienced three different highway scenarios, each with and without a marked automated vehicle. One scenario was based around some roadworks, the next scenario was a traffic jam, and the last scenario involved a lane change. Common to all scenarios was that the automated vehicles strictly adhered to German highway regulations, and therefore moved in road traffic somewhat differently to human drivers. After each trial, we asked participants to rate how appropriate and disturbing the automated vehicle’s driving behavior was. We also measured objective data, such as the time of a lane change and the time headway. The results show no differences for the subjective and objective data regarding the marking of an automated vehicle. Reasons for this might be that the driving behavior itself is sufficiently informative for humans to recognize an automated vehicle. In addition, participants experienced the automated vehicle’s driving behavior for the first time, and it is reasonable to assume that an adjustment of the humans’ driving behavior would take place in the event of repeated encounters.

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