In-vehicle Safety Warning System to Facilitate Driver’s Lane Change Decisions

2021 ◽  
Author(s):  
Siti Fatimah Abdul Razak ◽  
Tai Jia Wei ◽  
Sumendra Yogarayan ◽  
Mohd Fikri Azli Abdullah ◽  
Nur Ezzati Yunus
Keyword(s):  
Warning System ◽  
Vehicle Safety ◽  
Lane Change ◽  
Safety Warning

scholarly journals Research on the Influence of Vehicle Speed on Safety Warning Algorithm: A Lane Change Warning System Case Study

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2683
Author(s):  
Rui Fu ◽  
Yali Zhang ◽  
Chang Wang ◽  
Wei Yuan ◽  
Yingshi Guo ◽  
...  
Keyword(s):  
Warning System ◽  
Relative Distance ◽  
Driving Safety ◽  
Lane Change ◽  
Vehicle Speed ◽  
Accuracy Rate ◽  
Safety Warning ◽  
Change Characteristics ◽  
Speed Level

Speed has an important impact on driving safety, however, this factor is not included in existing safety warning algorithms. This study uses lane change systems to study the influence of vehicle speed on safety warning algorithms, aiming to determine lane change warning rules for different speeds (DS-LCW). Thirty-five drivers are recruited to carry out an extreme trial and naturalistic driving experiment. The vehicle speed, relative speed, relative distance, and minimum safety deceleration (MSD) related to lane change characteristics are then analyzed and calculated as warning rule characterization parameters. Lane change warning rules for a rear vehicle in the target lane under four-speed levels of 60 ≤ v < 70 km/h, 70 ≤ v < 80 km/h, 80 ≤ v < 90 km/h, and v ≥ 90 km/h are established. The accuracy of lane change warning rules not considering speed level (NDS-LCW) and ISO 17387 are found to be 87.5% and 79.8%, respectively. Comparatively, the accuracy rate of DS-LCW under four-speed levels is 94.6%, 93.8%, 90.0%, and 92.6%, respectively, which is significantly superior. The algorithm proposed in this paper provides warning in the lane change process with a smaller relative distance, and the accuracy rate of DS-LCW is significantly superior to NDS-LCW and ISO 17387.

scholarly journals Automatic Lane-Changing Decision Based on Single-Step Dynamic Game with Incomplete Information and Collision-Free Path Planning

Actuators ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 173
Author(s):  
Hongbo Wang ◽  
Shihan Xu ◽  
Longze Deng
Keyword(s):  
Path Planning ◽  
Dynamic Game ◽  
Single Step ◽  
Bézier Curve ◽  
Vehicle Safety ◽  
Bezier Curve ◽  
Lane Change ◽  
Hardware In The Loop ◽  
Power Performance ◽  
Lane Changing

Traffic accidents are often caused by improper lane changes. Although the safety of lane-changing has attracted extensive attention in the vehicle and traffic fields, there are few studies considering the lateral comfort of vehicle users in lane-changing decision-making. Lane-changing decision-making by single-step dynamic game with incomplete information and path planning based on Bézier curve are proposed in this paper to coordinate vehicle lane-changing performance from safety payoff, velocity payoff, and comfort payoff. First, the lane-changing safety distance which is improved by collecting lane-changing data through simulated driving, and lane-changing time obtained by Bézier curve path planning are introduced into the game payoff, so that the selection of the lane-changing start time considers the vehicle safety, power performance and passenger comfort of the lane-changing process. Second, the lane-changing path without collision to the forward vehicle is obtained through the constrained Bézier curve, and the Bézier curve is further constrained to obtain a smoother lane-changing path. The path tracking sliding mode controller of front wheel angle compensation by radical basis function neural network is designed. Finally, the model in the loop simulation and the hardware in the loop experiment are carried out to verify the advantages of the proposed method. The results of three lane-changing conditions designed in the hardware in the loop experiment show that the vehicle safety, power performance, and passenger comfort of the vehicle controlled by the proposed method are better than that of human drivers in discretionary lane change and mandatory lane change scenarios.

Application of Vision-based Safety Warning System to Haeundae Beach, Korea

2019 ◽  
Vol 91 (sp1) ◽  
pp. 216 ◽  
Author(s):  
Jooyong Lee ◽  
Jisoo Park ◽  
Inchul Kim ◽  
Dae Young Kang
Keyword(s):  
Warning System ◽  
Safety Warning

scholarly journals ADAS Acceptability Improvement Based on Self-Learning of Individual Driving Characteristics: A Case Study of Lane Change Warning System

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 81370-81381 ◽  
Author(s):  
Qinyu Sun ◽  
Hongjia Zhang ◽  
Zhen Li ◽  
Chang Wang ◽  
Kang Du
Keyword(s):  
Warning System ◽  
Lane Change ◽  
Self Learning

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.

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