The Dynamic Path Planning of Autonomous Vehicles on Icy and Snowy Roads Based on an Improved Artificial Potential Field

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Page 2, line 69 "The above research" - does not indicate which research, so need to justify.

Page 2, line 82: "Figure 1. Research flow chart" figure caption is not clear, so need to be specific

Page 2, line 88: '2.1. Traditional APF algorithm' had explained but not explain about 'Improved APF algorithm'; how traditional APF algorithm is different then improved APF algorithm.

'4. Conclusions' need to rewrite.

 

Comments on the Quality of English Language

authors should be improved to write as per scientific research article. they should full fill all the comments as mentioned.

Author Response

Page 2, line 69 "The above research" - does not indicate which research, so need to justify.

The Response: The authors give thanks to you for your helps to this manuscript. This paragraph should be a summary of the literature, so we have revised it in the revised draft. Specific modifications are as follows:” The researchers improved the artificial potential field algorithm from three aspects: potential field function, path smoothing and obstacle avoidance in different scenarios. However, vehicle dynamics and APF potential field functions in special environments such as ice and snow need to be redesigned. At the same time, different types of obstacle vehicles also have a significant impact on the dynamic obstacle avoidance path planning of vehicles.”

 

Page 2, line 82: "Figure 1. Research flow chart" figure caption is not clear, so need to be specific.

The Response: Sincerely thanks for your insightful comment. Figure.1 is the logic diagram of the paper. The author adds a detailed description of Figure 1 in lines 121-131.

“The research contents of this paper are as follows : Section 2 introduces the im-proved algorithm proposed in this paper in detail. Firstly, the principle of traditional APF algo-rithm is introduced. According to the influence of the driving characteristics of the vehicle in ISR environment, the gravitational potential field and the repulsive potential field are improved. Finally, the dynamic processing and trajectory smoothing of the planning path results are carried out, and the dynamic planning path of the autonomous vehicle in ISR environment based on the improved artificial potential field algorithm is obtained. Section 3 introduces the simulation platform for testing the effectiveness of the improved APF al-gorithm. The comparative experiments of vehicle performance parameters under different algorithms and different models are designed and discussed. Section 4 summarizes the full paper.”

 

Page 2, line 88: '2.1. Traditional APF algorithm' had explained but not explain about 'Improved APF algorithm'; how traditional APF algorithm is different then improved APF algorithm.

The Response: We feel sorry for our carelessness. Section 2.3 introduces the improvement of APF. In this paper, according to the driving characteristics of the vehicle on the ISR, the traditional APF algorithm is improved.

'4. Conclusions' need to rewrite.

The Response: Thank you for your instructive suggestion. We rewrite the conclusion of the paper.

“In this paper, we propose an improved artificial potential field algorithm to improve the efficiency and accuracy of autonomous vehicle path planning in ISR environment. The reliability of the model is verified by comparing the vehicle planning trajectories at different speeds and different obstacle avoidance conditions.

  Considering the driving characteristics of vehicles in ISR, the gravitational field and repulsive field models of the traditional APF algorithm are improved by adding adjustment factors and judgment coefficients. The improved APF algorithm proposed can plan a smooth lane change and overtaking path, effectively avoid obstacle vehicles, and guide autonomous vehicles to drive safely and stably in this paper.

  The effectiveness of the improved APF algorithm is verified by comparing with the traditional APF algorithm in dynamic planning path and vehicle condition. The results show that compared with the static obstacle avoidance and dynamic obstacle avoidance of the traditional APF algorithm, the trajectory of the dynamic obstacle avoidance path planned by the improved APF algorithm is smoother and there is no mutation.

 The obstacle avoidance accuracy and efficiency of autonomous vehicles for different obstacle models are analyzed. The results show that the improved APF algorithm can generate different planning paths for different types of obstacle vehicles, and can safely and effectively guide the autonomous vehicle to complete obstacle avoidance and lane change.”

Reviewer 2 Report

Comments and Suggestions for Authors

After reviewing the manuscript “Dynamic Path Planning of Autonomous Vehicles on Ice and Snow Roads Based on Improved Artificial Potential Field,” my comments are the following.

 

The manuscript presents An algorithm using artificial potential fields developed for autonomous vehicle path planning on  Ice and Snow Roads (ISR) to prevent collisions.

 

My comments are the following.

1. Small, medium and long vehicles have been used in the simulation. The basis (Weight/Length) of categorisation needs to be clarified.

2.     The Axis of the graph must be visible. Check fig. 6

 

My decision for the manuscript is to accept it.

Comments on the Quality of English Language

Minor proofreading is required.

 

Author Response

After reviewing the manuscript “Dynamic Path Planning of Autonomous Vehicles on Ice and Snow Roads Based on Improved Artificial Potential Field,” my comments are the following. The manuscript presents An algorithm using artificial potential fields developed for autonomous vehicle path planning on  Ice and Snow Roads (ISR) to prevent collisions.

My comments are the following.

1. Small, medium and long vehicles have been used in the simulation. The basis (Weight/Length) of categorisation needs to be clarified.

The Response: The authors give thanks to you for your helps to this manuscript. The author added the classification criteria and type criteria for obstacle vehicles in 3.3. The length and width of the vehicle are given in Table 4.

 

2. The Axis of the graph must be visible. Check fig. 6

The Response: We apologize for our errors. We have added the horizontal and vertical coordinate interpretations of Figure 7 to the submitted manuscript. Figure 7 shows the visualization of the dynamic trajectory of the vehicle. The horizontal coordinate is the lane length and the vertical coordinate is the lane width.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript provides an overview of the research on dynamic path planning for autonomous vehicles on ice and snow roads using an improved artificial potential field (APF) algorithm. In general, the manuscript;

·         Addresses an important issue in autonomous vehicle technology.

·         Thorough methodology but needs better organization and clarity.

·         Emphasize the novelty of the improved APF algorithm and its implications for practical scenarios.

The Abstract section;

·         Clear summary but lacks conciseness and specific results.

·         Needs more direct wording to convey key contributions.

·         Briefly mention the novelty of the improved APF algorithm.

The Introduction Section:

·         Informative but needs better organization and conciseness.

·         Stronger emphasis on the novelty of proposed improvements and clearer connection to prior research.

·         Summarize and highlight the specific research gap.

·         Remove redundant repetition of APF algorithm basics.

·         Improve paragraph relationships for a logical and smooth narrative.

·         Explicitly connect previous studies to proposed improvements.

The Methods section:

·         In-depth but complex explanation of APF algorithm, ISR driving characteristics, improvements, path smoothing, and dynamic planning.

·         Make it more accessible with clearer explanations and better organization.

·         Clarify the rationale for considering specific models and factors in the APF algorithm.

·         Include quantitative results to support method's effectiveness.

Simulation and Results Section:

·         Detailed but needs enhanced clarity and result interpretation.

·         Reduce repetition.

·         Discuss the implications of results on the improved APF algorithm's effectiveness in different scenarios.

Conclusion Section:

·         Clear and concise summary of research with future research avenues.

·         Remove repetitive statements.

·         Lack of specific details on performance improvements and practical applications.

·         Future Work is valuable for addressing limitations and potential extensions. But could be more concise and focused on key areas of future research.

Comments on the Quality of English Language

Basic English correction is required. There are some minor grammatical errors which can be corrected via used word processor easily.

Author Response

The manuscript provides an overview of the research on dynamic path planning for autonomous vehicles on ice and snow roads using an improved artificial potential field (APF) algorithm. In general, the manuscript;

• Addresses an important issue in autonomous vehicle technology.
• Thorough methodology but needs better organization and clarity.
• Emphasize the novelty of the improved APF algorithm and its implications for practical scenarios.

The Abstract section;

• Clear summary but lacks conciseness and specific results.
• Needs more direct wording to convey key contributions.
• Briefly mention the novelty of the improved APF algorithm.

The Response: The authors give thanks to you for your helps to this manuscript. In the submitted revision, we added the advantages of the improved APF algorithm.” the driving characteristics of vehicles on ISR are established, and the artificial potential field function is introduced to avoid the collision risk when planning the path.” And specific simulation results are added. “The results shows that the improved APF algorithm has obvious effect on the smoothness of the path and the reduction of the curvature mutation, and can generate a safe and efficient path on the ice and snow roads.”

The Introduction Section:

• Informative but needs better organization and conciseness.
• Stronger emphasis on the novelty of proposed improvements and clearer connection to prior research.
• Summarize and highlight the specific research gap.
• ·Remove redundant repetition of APF algorithm basics.
• Improve paragraph relationships for a logical and smooth narrative.
• Explicitly connect previous studies to proposed improvements.

The Response: Thank you for your valuable suggestions We modified the structure of the ”induction” to make it clearer and added the corresponding analysis results. And we refined the contribution of this study based on the comments made. Finally, the novelty of the APF algorithm proposed in this paper is analyzed by comparing it with related studies, and removes redundancy from the APF algorithm

 

The Methods section:

• In-depth but complex explanation of APF algorithm, ISR driving characteristics, improvements, path smoothing, and dynamic planning.
• Make it more accessible with clearer explanations and better organization.
• Clarify the rationale for considering specific models and factors in the APF algorithm.
• Include quantitative results to support method's effectiveness.

The Response: Thank you for your instructive suggestion. The quantitative analysis results we give the results in the simulation section in Section 3. The research object of this paper is the path planning problem of self-driving vehicles under snow and ice, in 2.2 we describe the applicability conditions of the improved APF algorithm for the path planning problem on snow and ice, and in induction we elaborate the rationale for APF to consider the characteristic models and factors. To explain the whole process of the method more clearly, we give the whole steps of the path planning algorithm in 2.5 and modify the algorithm process in 3.1.

 

Simulation and Results Section:

• Detailed but needs enhanced clarity and result interpretation.
• Reduce repetition.
• Discuss the implications of results on the improved APF algorithm's effectiveness in different scenarios.

The Response: Sincerely thanks for your insightful comment. We removed duplicates from the results. Improvements with the dynamic RRT algorithm were added, and in each of the different scenarios simulated under Section 3, we compared the advantages and disadvantages of the different algorithms and explained the results. We rewrote some of the results to make the results section clearer.

 

Conclusion Section:

• Clear and concise summary of research with future research avenues.
• Remove repetitive statements.
• Lack of specific details on performance improvements and practical applications.
• Future Work is valuable for addressing limitations and potential extensions. But could be more concise and focused on key areas of future research.

The Response: Sincerely thanks for your insightful comment. We have rewritten the general statement in the first part of the conclusion, and in the discussion section we have separately elaborated the improved part of the APF algorithm for ice and snow roads, and compared the effectiveness of the dynamic and static obstacle avoidance paths in different scenarios. In discussing the application prospects of our research, we recognize the problems and challenges that may be faced in practical applications. For this reason, we have added some discussion in the article on how to apply our research results to real-world scenarios. This includes a discussion of possible solutions as well as future research directions.

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

In this work, an improved artificial potential field algorithm is proposed to increase the efficiency and accuracy of autonomous vehicle trajectory planning in ISR environments. The authors verify model reliability by comparing vehicle planning trajectories at different speeds and different obstacle avoidance conditions.  It is also proposed that the gravity field and repulsive field models of the traditional APF algorithm are improved by adding adjustment factors and judgment coefficients. And according to the results shown, the improved APF algorithm proposed in this research work can plan a smooth lane change and overtaking trajectory, effectively avoid vehicles with obstacles, and guide autonomous vehicles to drive safely and stably.

This work can be improved and a new literature review should be carried out. My considerations are the following:

 

1.-The work only compares the APF and DOA-IAPF algorithms. The authors should indicate if there are other obstacle avoidance algorithms (not necessarily based on potential field) and if possible make a comparison.

2.-The authors consider a very idealized scenario. Where the obstacle vehicle travels in a straight line at a constant speed. Could the authors consider lateral displacement of the obstacle vehicle? (lane change case)

3.- Please perform a new literature review.

Author Response

In this work, an improved artificial potential field algorithm is proposed to increase the efficiency and accuracy of autonomous vehicle trajectory planning in ISR environments. The authors verify model reliability by comparing vehicle planning trajectories at different speeds and different obstacle avoidance conditions.  It is also proposed that the gravity field and repulsive field models of the traditional APF algorithm are improved by adding adjustment factors and judgment coefficients. And according to the results shown, the improved APF algorithm proposed in this research work can plan a smooth lane change and overtaking trajectory, effectively avoid vehicles with obstacles, and guide autonomous vehicles to drive safely and stably.

This work can be improved and a new literature review should be carried out. My considerations are the following:

1.-The work only compares the APF and DOA-IAPF algorithms. The authors should indicate if there are other obstacle avoidance algorithms (not necessarily based on potential field) and if possible make a comparison.

The Response: The authors give thanks to you for your helps to this manuscript. In the submitted revised manuscript, we added other studies on path planning algorithms in the literature review. And we added the comparison between the dynamic RRT path planning algorithm and the improved APF algorithm in the simulation experiments.

 

2.-The authors consider a very idealized scenario. Where the obstacle vehicle travels in a straight line at a constant speed. Could the authors consider lateral displacement of the obstacle vehicle? (lane change case)

The Response: Thank you for your instructive suggestion. When the target vehicle encounters an obstacle, the improved APF algorithm proposed in this paper is to prioritize the lane change and perform quadratic planning using a fifth degree polynomial based on the derived trajectory points. And the lateral movement of the obstacle vehicle will only affect the traverse angle and the front wheel turning angle of the target vehicle, and will not affect the parameters of the target vehicle to make an abrupt change.

 

3.- Please perform a new literature review.

The Response: Sincerely thanks for your insightful comment. We rewrote the literature review section of the article. To make the logic clearer, we reorganized the literature and added a background introduction to make the connection between each section stronger.

Author Response File: Author Response.pdf