scholarly journals The Atlas of Lane Changes: Investigating Location-Dependent Lane Change Behaviors Using Measurement Data from a Customer Fleet

2021 ◽  
Author(s):  
Florian Wirthmuller ◽  
Jochen Hipp ◽  
Christian Reichenbacher ◽  
Manfred Reichert
Keyword(s):  
Measurement Data ◽  
Lane Change ◽  
Lane Changes ◽  
Change Behaviors

Simple Clothoid Paths for Autonomous Vehicle Lane Changes at the Limits of Handling

2013 ◽  
Author(s):  
Joseph Funke ◽  
J. Christian Gerdes
Keyword(s):  
Real Time ◽  
Autonomous Vehicle ◽  
Lane Change ◽  
Lane Changes ◽  
Entry Speed ◽  
Path Curvature

This paper demonstrates that an autonomous vehicle can perform emergency lane changes up to the limits of handling through real-time generation and evaluation of bi-elementary paths. Path curvature and friction limits determine the maximum possible speed along the path and, consequently, the feasibility of the path. This approach incorporates both steering inputs and changes in speed during the maneuver. As a result, varying path parameters and observing the maximum possible entry speed of resulting paths gives insight about when and to what extent a vehicle should brake and turn during emergency lane change maneuvers. Tests on an autonomous vehicle validate this approach for lane changes at the limits of handling.

New Results in Driver Steering Control Models

1977 ◽  
Vol 19 (4) ◽  
pp. 381-397 ◽  
Author(s):  
Duane T. McRuer ◽  
R. Wade Allen ◽  
David H. Weir ◽  
Richard H. Klein
Keyword(s):  
Dynamic Control ◽  
Short Review ◽  
Model Verification ◽  
System Structure ◽  
Lane Change ◽  
Vehicle Dynamic ◽  
Steering Control ◽  
Dynamic Changes ◽  
Lane Changes ◽  
Vehicle Systems

The dynamic control properties of drivers and driver/vehicle systems in steering operations have been widely investigated. This paper presents a short review of the combined compensatory, pursuit, and precognitive features needed to describe the total properties of the driver as a controller. Specific combinations of these features are associated with particular driving maneuvers. Some recent results are presented to confirm previous hypotheses and more completely quantify the models. The driver-organized system structure for regulation control is reviewed with emphasis on the loops closed and adjustments made by the driver in compensating for vehicle dynamic changes. Pursuit structures are given which describe steering control with preview and as one explanation for lane change maneuvers. Precognitive behavior is then presented as the most skilled mode utilized in rapid lane changes and other well-practiced maneuvers including obstacle avoidance. For all three categories of control, full-scale or simulator data are presented as indications of model verification.

scholarly journals Goal Estimation of Mandatory Lane Changes Based on Interaction between Drivers

2020 ◽  
Vol 10 (9) ◽  
pp. 3289
Author(s):  
Hanwool Woo ◽  
Mizuki Sugimoto ◽  
Hirokazu Madokoro ◽  
Kazuhito Sato ◽  
Yusuke Tamura ◽  
...  
Keyword(s):  
Warning System ◽  
Autonomous Driving ◽  
Field Method ◽  
Lane Change ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Lane Changing ◽  
Lane Changes ◽  
Dynamic Potential ◽  
Novel Method

In this paper, we propose a novel method to estimate a goal of surround vehicles to perform a lane change at a merging section. Recently, autonomous driving and advance driver-assistance systems are attracting great attention as a solution to substitute human drivers and to decrease accident rates. For example, a warning system to alert a lane change performed by surrounding vehicles to the front space of the host vehicle can be considered. If it is possible to forecast the intention of the interrupting vehicle in advance, the host driver can easily respond to the lane change with sufficient reaction time. This paper assumes a mandatory situation where two lanes are merged. The proposed method assesses the interaction between the lane-changing vehicle and the host vehicle on the mainstream lane. Then, the lane-change goal is estimated based on the interaction under the assumption that the lane-changing driver decides to minimize the collision risk. The proposed method applies the dynamic potential field method, which changes the distribution according to the relative speed and distance between two subject vehicles, to assess the interaction. The performance of goal estimation is evaluated using real traffic data, and it is demonstrated that the estimation can be successfully performed by the proposed method.

Characterizing Lane Changes via Digitized Infrastructure and Low-Cost GPS

2019 ◽  
Vol 2673 (8) ◽  
pp. 298-309 ◽  
Author(s):  
Ishtiak Ahmed ◽  
Alan Karr ◽  
Nagui M. Rouphail ◽  
Gyounghoon Chun ◽  
Shams Tanvir
Keyword(s):  
Autonomous Vehicles ◽  
Lateral Displacement ◽  
Low Cost ◽  
Detection Algorithm ◽  
Lane Change ◽  
Trajectory Data ◽  
Lane Changing ◽  
Lane Changes ◽  
Detection Systems ◽  
Level Information

With the expected increase in the availability of trajectory-level information from connected and autonomous vehicles, issues of lane changing behavior that were difficult to assess with traditional freeway detection systems can now begin to be addressed. This study presents the development and application of a lane change detection algorithm that uses trajectory data from a low-cost GPS-equipped fleet, supplemented with digitized lane markings. The proposed algorithm minimizes the effect of GPS errors by constraining the temporal duration and lateral displacement of a lane change detected using preliminary lane positioning. The algorithm was applied to 637 naturalistic trajectories traversing a long weaving segment and validated through a series of controlled lane change experiments. Analysis of naturalistic trajectory data revealed that ramp-to-freeway trips had the highest number of discretionary lane changes in excess of 1 lane change/vehicle. Overall, excessive lane change rates were highest between the two middle freeway lanes at 0.86 lane changes/vehicle. These results indicate that extreme lane changing behavior may significantly contribute to the peak-hour congestion at the site. The average lateral speed during lane change was 2.7 fps, consistent with the literature, with several freeway–freeway and ramp–ramp trajectories showing speeds up to 7.7 fps. All ramp-to-freeway vehicles executed their first mandatory lane change within 62.5% of the total weaving length, although other weaving lane changes were spread over the entire segment. These findings can be useful for implementing strategies to lessen abrupt and excessive lane changes through better lane pre-positioning.

scholarly journals Human-Like Lane Change Decision Model for Autonomous Vehicles that Considers the Risk Perception of Drivers in Mixed Traffic

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2259 ◽  
Author(s):  
Chang Wang ◽  
Qinyu Sun ◽  
Zhen Li ◽  
Hongjia Zhang
Keyword(s):  
Risk Perception ◽  
Autonomous Vehicles ◽  
Decision Model ◽  
Signal Detection Theory ◽  
Critical Issue ◽  
Lane Change ◽  
Mixed Traffic ◽  
Driving System ◽  
Lane Changes ◽  
The Subject

Determining an appropriate time to execute a lane change is a critical issue for the development of Autonomous Vehicles (AVs).However, few studies have considered the rear and the front vehicle-driver’s risk perception while developing a human-like lane-change decision model. This paper aims to develop a lane-change decision model for AVs and to identify a two level threshold that conforms to a driver’s perception of the ability to safely change lanes with a rear vehicle approaching fast. Based on the signal detection theory and extreme moment trials on a real highway, two thresholds of safe lane change were determined with consideration of risk perception of the rear and the subject vehicle drivers, respectively. The rear vehicle’s Minimum Safe Deceleration (MSD) during the lane change maneuver of the subject vehicle was selected as the lane change safety indicator, and was calculated using the proposed human-like lane-change decision model. The results showed that, compared with the driver in the front extreme moment trial, the driver in the rear extreme moment trial is more conservative during the lane change process. To meet the safety expectations of the subject and rear vehicle drivers, the primary and secondary safe thresholds were determined to be 0.85 m/s2 and 1.76 m/s2, respectively. The decision model can help make AVs safer and more polite during lane changes, as it not only improves acceptance of the intelligent driving system, but also further ensures the rear vehicle’s driver’s safety.

Eye Glance Behavior during Lane Changes and Straight-Ahead Driving

2005 ◽  
Vol 1937 (1) ◽  
pp. 44-50 ◽  
Author(s):  
Erik C. B. Olsen ◽  
Suzanne E. Lee ◽  
Walter W. Wierwille
Keyword(s):  
Collision Avoidance ◽  
Blind Spot ◽  
Development Effort ◽  
Lane Change ◽  
Lane Changing ◽  
Lane Changes ◽  
Visual Presence ◽  
Safety And Reliability ◽  
Rearview Mirror ◽  
Straight Ahead

Understanding drivers’ eye behavior before lane changing is an important aspect of designing usable, safe lane-change collision-avoidance systems (LCAS) that will fit well with drivers’ expectations. This understanding could lead to improvements for LCAS as well as for a variety of other collision avoidance systems. Findings regarding driver eye glance behaviors are presented in a comparison of lane change maneuvers with straight-ahead (baseline) driving events. Specific eye glance patterns before lane change initiation were observed. When preparing to make a lane change to the left as compared with driving straight ahead, drivers doubled the number of glances toward the rearview mirror and were much more likely to look at other locations associated with moving to the left, including the left mirror and blind spot. On the basis of the eye glance patterns observed and previous results, the following recommendations are made: ( a) visual presence detection indicator displays should be used to provide information about vehicles in the rear adjacent lane any time a vehicle is detected, ( b) a presence indicator should be presented in a visual format, and ( c) the left mirror and rearview mirror locations should be considered for providing lane change information to the driver. The process of acquiring and analyzing eye glance movements is well worth the investment in resources. However, prototype systems must be tested before implementation, and the exact location and format of warning systems warrant a separate research and development effort to ensure safety and reliability.

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