scholarly journals MODIFIED HAMILTONIAN ALGORITHM FOR OPTIMAL LANE CHANGE WITH APPLICATION TO COLLISION AVOIDANCE

2015 ◽  
Vol 2015 (01) ◽  
pp. 576-584 ◽  
Author(s):  
Yangyan Gao ◽  
Mathias Lidberg ◽  
Timothy Gordon
Author(s):  
Husam Muslim ◽  
Makoto Itoh

In order to improve road traffic safety, increasingly sophisticated and robust collision avoidance systems are being developed. When employed in safety-critical situations, however, the interaction between the human factors and these systems may increase the complexity of the task of driving. Due to these human factors, the ability of the driver to respond to various traffic dangers is considered to be a function of the level of automation, balance of control authority, and the innate ability of the driver. For the purpose of this study, a driving experiment was designed using two types of lane change collision avoidance systems. One was a haptic warning system that provides a steering force feedback to avoid hazardous lane change, and the other, a semi-autonomous system that provides an automatic action to prevent hazardous lane change. While drivers had the final authority over the haptic system, they were unable to override the automatic action. Both systems were examined in three conditions: i) hazard that can be detected only by the system, ii) hazard that can be detected only by the driver, and iii) combined hazards. The different support systems were applied to the different hazards resulting in significant differences in drivers’ reaction time and steering behavior. The drivers’ subjective post-hazard assessments were significantly affected by the type of encountered hazard.


Author(s):  
Erik C. B. Olsen ◽  
Suzanne E. Lee ◽  
Walter W. Wierwille

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.


Author(s):  
Mohsen Rafat ◽  
Shahram Azadi

Trajectory planning with consideration of surrounding vehicles and decision-making in the middle of complicated manoeuvres are some of the most important challenges regarding the implementation of automated driving. Since transient dynamic traffic conditions was limited to the start of the manoeuvre in previous research, no solution was provided for the surrounding vehicles’ transient changes during the manoeuvre. The algorithm presented in this paper is able to adapt to unstable variable traffic conditions and it is robust to changes in the surrounding vehicles’ conditions, even during the lane change manoeuvre. The Adaptive Lane Change algorithm provides all possible safe trajectories for any moment of manoeuvre via applying DE optimization method on a fifth-order polynomial equation. In this way, it is able to make a new decision and plan safe trajectories according to the new conditions of surrounding vehicles during the manoeuvre. Also, it guarantees collision avoidance at all-time via simultaneous longitudinal and lateral vehicle control. Improving the trajectory during a lane change manoeuvre regarding the surrounding vehicles’ conditions is considered as one of the main contributions of the presented algorithm. A second main contribution is the collision avoidance considering the vehicle’s dynamic via returning to the initial lane when there is no safe trajectory in the target lane, even during the lane change manoeuvre. The decision-making unit is evaluated by real driving tests. Then, the whole structure is simulated with MATLAB in complex transient dynamic traffic conditions via various scenarios and its performance is tested with IPG CarMaker in the presence of simulated surrounding vehicles.


Author(s):  
Zhiqiang Zhang ◽  
Lei Zhang ◽  
Junjun Deng ◽  
Mingqiang Wang ◽  
Zhenpo Wang ◽  
...  

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