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Article

Research on Vibration Comfort of Non-Motorized Lane Riding Based on Three-Axis Acceleration

by
Yuecheng Li
1,
Liangjie Xu
1,2,
Xi Huang
1,* and
Hao Xiao
1
1
School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China
2
School of Automotive and Traffic Engineering, Hubei University of Arts and Science, Xiangyang 441053, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2024, 14(1), 441; https://doi.org/10.3390/app14010441
Submission received: 20 November 2023 / Revised: 30 December 2023 / Accepted: 30 December 2023 / Published: 3 January 2024
(This article belongs to the Section Transportation and Future Mobility)
Browse Figures
Versions Notes

Abstract

:
To enhance cycling comfort, a critical investigation of vibration effects in non-motorized bicycle riding is essential, focusing on road characteristics and traffic features. The analysis of how these elements influence cycling vibrations identified 13 key factors. This study utilized non-motorized bicycle lanes in Wuhan City for empirical research. Three-axis accelerometers were attached to riders’ torsos to measure vibration comfort levels. The observed road segments ranged from slightly to relatively uncomfortable. This study employed the random forest algorithm and logistic regression to analyze the influencing factors further. Six factors emerged as significant in affecting cycling comfort: the existence of dedicated non-motorized bicycle lanes, the lack of a physical barrier between non-motorized and motorized traffic, cycling speed, road surface irregularities, parking areas within non-motorized lanes, and bicycle type. This research offers valuable insights into non-motorized bicycle lane usage and contributes to the development of urban non-motorized bicycle infrastructure, supporting sustainable urban transportation.

1. Introduction

The interdependence between walking and bicycling transportation systems and public transportation is a crucial component of the green, low-carbon travel ecosystem. These systems significantly influence residents’ travel choices. Enhancing public transportation necessitates the bolstering of a robust walking and cycling infrastructure. The development of a high-quality walking and bicycling system is essential for encouraging residents to shift towards more sustainable travel modes. Therefore, the construction and improvement of these systems warrant significant attention to foster a green, low-carbon, and sustainable transportation future [1,2,3,4].
The quality and service level of urban non-motorized paths are critical not only for safety but also for the comfort of non-motorized riding. Presently, research on non-motorized paths primarily concentrates on ensuring uninterrupted space, addressing safety concerns, and evaluating service levels. However, there is a notable paucity of research focusing on the comfort experienced during non-motorized riding. This gap highlights the need for more comprehensive studies that incorporate the comfort dimension into the evaluation of non-motorized transportation infrastructure [5,6,7,8].
Enhancing non-motorized comfort on urban roads can significantly increase the use of non-motorized vehicles, yielding social and environmental benefits like improved air quality, reduced traffic congestion, and lower carbon emissions. Non-motorized riders often consider vibration as a key indicator of bicycle comfort, which markedly influences their vehicle choice. The concept of non-motorized lane comfort is multifaceted. Scholars have investigated its main influencing factors through field studies and surveys [9,10]. Some research posits that the condition of bicycle infrastructure predominantly determines comfort. Others argue that road surface type, smoothness, and overall conditions are crucial for bicycle comfort. Further, Rybarczyk et al. [11,12,13,14] delved into the impact of road surface on bicycle comfort as perceived through vibration intensity by cyclists. They developed a dynamic bicycle comfort measurement system, quantifying bicycle vibration on various road sections. This system involved volunteers providing feedback on each road section via questionnaires, leading to the establishment of thresholds for acceptable rates, comfort, and vibration perception. The Dynamic Comfort Index (DCI), a novel and effective metric, was introduced to characterize the vibration features of bicycle lanes using acceleration data from bicycles. This suggests that cyclists’ route choices are often influenced by road surface quality. Additionally, Mekuria et al. [15] examined the relationship between bicycle road characteristics and vehicular collisions by developing collision models.
Teixeira et al. [16,17] explored the influence of the road environment on cycling. Ni Ying [18] developed a non-motorized cycling quality assessment model for urban roads, incorporating evaluation indices like facility attributes and cycling behavior characteristic parameters, derived from natural cycling experiments. Mi Mingxuan [19] crafted a situational simulation questionnaire using the narrative preference method. For the survey data, a discrete choice model was applied to examine the riding preferences of commuters as well as to assess and suggest improvements for the riding environment.
In summary, the acceleration experienced during non-motorized riding is closely linked to road environment and traffic factors. However, existing studies have not comprehensively delineated this relationship, which hinders practical applications aimed at enhancing riding comfort on non-motorized roads [20,21,22,23,24,25,26]. In this study, we assessed and analyzed the vibration comfort of non-motorized road riding by collecting triaxial acceleration data from the human torso under riding conditions, thereby confirming the impact of road and traffic factors on vibration comfort.

2. Analysis of Factors Affecting Riding Vibration Comfort

Slow-walking spaces encompass sidewalks, non-motorized roads, intersections, and green facility belts. These spaces are characterized by various elements such as roads (including road surfaces and slopes), ancillary facilities (like signage, crossing aids, bus stops, streetlights, and manhole covers), greening (green belts, tree pools, etc.), and the natural environment. The comfort of non-motorized vehicle riding is primarily affected by several factors: firstly, the deterioration and collapse of non-motorized vehicle lanes; secondly, significant gaps between bricks causing uneven surfaces; thirdly, the depressions around manhole covers; and fourthly, the presence of obstacles on the road surface. Prior research suggests that the factors influencing the vibration comfort of non-motorized lane riding can be broadly categorized into two main aspects.

2.1. Road Characteristics

2.1.1. Impact of Route Alignment on Riding Vibration Comfort

Non-motorized roadways encompass bus stops, intersections, adjacent side accesses, and continuous travel sections. Conflict with bus passenger flow and signalized intersection stops, involving braking and restarting during cycling, induce changes in cycling acceleration. Vehicle and pedestrian convergence on non-motorized pathways can disrupt riding, causing acceleration fluctuations. In continuous sections, straight roads typically maintain stable riding with minimal acceleration change. Conversely, curved roads can cause discomfort due to centrifugal force, despite curves being a minor proportion of the route. Therefore, this study considers bus stops, intersections, the number of district entries, and turn counts as potential factors influencing riding vibration comfort.

2.1.2. Influence of Roadway Cross Section on Cycling Vibration Comfort

The non-motorized roadway cross section usually includes lanes, sidewalks, and medians. The presence or absence of dedicated lanes significantly impacts riding smoothness; dedicated lanes facilitate stable travel, reducing acceleration fluctuations. On-street parking also affects riding conditions, as non-motorized vehicles often navigate alongside motorized traffic or sidewalks. The interaction of these elements creates four cross-section types [27]: (A) shared lanes without sidewalks or dedicated non-motorized lanes; (B) non-motorized lanes without sidewalks, separating motorized and non-motorized traffic; (C) sidewalks without non-motorized lanes, using elevation differences for separation; and (D) both sidewalks and non-motorized lanes, using physical barriers for segregation. With increasing urban road service levels, types C and D are more prevalent. Hence, this study identifies the presence of non-motorized lanes, segregation, and on-street parking as potential factors affecting riding vibration comfort.

2.1.3. Influence of Road Longitudinal Section on Riding Vibration Comfort

The road longitudinal section mainly impacts riding vibration comfort through the gradient of non-motorized roadways. However, measuring this gradient is challenging. With urban road gradients generally controlled at between 1.5% and 2.5% and a maximum set at 5% (the design speed of 15 km/h) [28], the slope’s influence on non-motorized riding vibration is relatively minor. Therefore, this article excludes the impact of road longitudinal section dimensions on riding vibration comfort.

2.1.4. Influence of Road Surface on Ride Vibration Comfort

The riding state on non-motorized roadways is primarily affected by the surface levelness. Potholes, manhole covers, and pavement-joint height differences can significantly alter longitudinal acceleration. Although urban road surfaces are generally level, manhole covers and joint differences have a substantial impact [29]. Consequently, this paper selects the number of manhole covers and pavement articulation protrusions as potential factors influencing riding vibration comfort.

2.2. Non-Motorized Transportation Characteristics

2.2.1. Effect of Vehicle Type on Riding Vibration Comfort

Non-motorized vehicles, characterized by their smaller size and greater maneuverability compared to motorized vehicles, are predominantly two-wheeled and lack balance and protective features. Their movement patterns are often spontaneous and tend to cluster, especially at signal crossings, requiring minimal driving space. Electric bicycles, differing from traditional bicycles, exhibit higher speeds and greater mass, leading to reduced stability and heightened safety concerns due to their erratic motion. Consequently, this paper identifies two vehicle types, bicycles and electric non-motorized vehicles, as potential factors influencing riding vibration comfort [30].

2.2.2. Influence of Traffic Flow Composition on Riding Vibration Comfort

In urban areas, the confluence of electric bicycles, bicycles, and pedestrians in non-motorized lanes is common. Non-motorized vehicles are characterized by irregular travel paths, frequent lane changes, and instability [31,32]. Pedestrians often walk in groups with unpredictable paths and may stop or change direction abruptly. Given the speed disparity among electric bicycles, bicycles, and pedestrians, increased pedestrian traffic heightens the likelihood of braking in non-motorized vehicles, leading to operational fluctuations. This paper, therefore, selects the proportion of electric bicycles (high or low) as a factor potentially affecting riding vibration comfort.

2.2.3. Influence of Speed on Riding Vibration Comfort

On non-motorized roadways, the rider’s speed is intricately linked to braking behavior. Traveling at higher speeds over uneven surfaces can result in jolting [33]. Accordingly, this study considers different speed categories—low (5–12 km/h), medium (12–17 km/h), and high (17–25 km/h)—as potential factors influencing riding vibration comfort.
In summary, this article focuses on two main areas: road and traffic characteristics. Road characteristics are segmented into four dimensions: route alignment, cross section, longitudinal section, and road surface. Traffic characteristics are categorized into three dimensions: vehicle type, traffic flow composition, and speed. A total of thirteen factors are analyzed, including the number of bus stops, intersections, entrances, and number of turns; the existence of non-motorized lanes; the absence of physical segregation; with or without on-street parking area; and the number of manhole covers and surface protrusions. Additionally, the types of non-motorized vehicles, proportion of electric bicycles, and riding speeds are considered as potential factors affecting riding vibration comfort.

3. Experimental Data Collection and Processing

3.1. Experimental Program

(1)
Experimental Tool
In this study, smartphones serve as the data acquisition terminals, utilizing their built-in global positioning system (GPS) modules and acceleration sensor modules to gather GPS positional coordinates and triaxial acceleration data. As per the Android developer’s official documentation, the sensor module’s accuracy is at 1 in 10,000, satisfying the data accuracy requirements for this research. During data collection, the smartphones were vertically attached to the torsos of experimenters seated on two different types of vehicles: electric bicycles and bicycles. This study mainly used electric vehicles for experiments and compared and analyzed non-motorized vehicle types using bicycles.
(2)
Experimental Subject
The study focused on a segment of Youyi Avenue in Wuchang District, Wuhan City, as shown in Figure 1. Data such as the locations of stations, intersections, access points, and the presence of segregated or non-segregated non-motorized traffic lanes along the route were acquired through Baidu Live Map.
(3)
Experimental Program
Data collection was conducted from 11:00 to 13:00 on weekdays. The methodology involved spatially dividing the non-motorized paths into segments, each 100 m in length, for analytical purposes. The moments of stopping and starting at stations and intersections were meticulously recorded. To minimize the impact of extraneous variables on the results, each experiment utilized vehicles of the same model with consistent seat heights.

3.2. Calculation of ISO 2631 [34] Comfort Indicators

Mechanical vibration significantly impacts human health and comfort, and vehicle smoothness reflects the extent of bumps experienced, as per the international standard (ISO 2631-1:1997). During riding, it is assumed that the rider is seated, and lateral swaying of the vehicle body is disregarded. Additionally, considering the rider’s strong self-regulatory ability, hand-transferred vibration is also overlooked [35,36,37,38]. Consequently, rider vibration is influenced by acceleration in three dimensions: x (forward direction), y (lateral direction perpendicular to forward), and z (vertical direction). Due to varying human sensitivity to acceleration in different directions, the contribution of acceleration in each direction to comfort differs. Thus, calculating total weighted acceleration requires considering the influence of three-axis acceleration on comfort [39,40,41]. Accordingly, when computing total weighted acceleration, different weights are assigned based on the impact of three-axis acceleration on comfort [42]:
a v = ( k x 2 a x 2 + k y 2 a y 2 + k z 2 a z 2 ) 1 2
where a x , a y , a z correspond to the acceleration on the coordinate axes x, y, z, respectively. k x , k y , k z are the direction factors, according to the standard sitting state, where k x = 1.4 , k y = 1.4 , k z = 1 . The correlation between the calculated total vibration and comfort is shown in Table 1.
The data collected during the experiment were processed to determine the weighted acceleration using Equation (1). Subsequently, the average of these weighted accelerations over the course of the running interval was employed as the characteristic parameter for assessing riding vibration comfort [43,44,45].

4. Experimental Results Analysis

EpiData 3.1 software facilitated the double-entry verification of all survey data [46]. Subsequently, SPSS 24.0 was employed to eliminate anomalous values and impute missing data. The average weighted acceleration of riding was calculated for specified intervals, revealing a value distribution range of 0.32 to 0.95 m/s2. In aligning comfort level gradations with acceleration value ranges (refer to Table 1), it was determined that values between 0.315 and 0.63 m/s2 correspond to a slightly uncomfortable level, while values from 0.5 to 1.0 m/s2 fall within the relatively uncomfortable level. Consequently, the vibration comfort levels observed in the experimental route were confined to two categories: slightly uncomfortable and relatively uncomfortable. For statistical analysis, R-4.0.2 was used. A random forest model was developed, and the dataset was divided into a training set and a test set in a 3:1 ratio. Variables were prioritized based on their importance, and multifactorial logistic regression was applied to examine the impact and magnitude of the optimal variables on riding vibration comfort. The significance level was set at α = 0.05.

4.1. Assignment of Variables

Using the comfort level as the dependent variable, this study assigned values to variables pertaining to road characteristics and traffic features, as detailed in Table 2.

4.2. Ranking of Importance of Random Forest Variables

(1)
Order of importance
The variables were ranked based on their significance, in descending order: with or without non-motorized lanes, with or without human non-isolation, riding speed, the number of roadway articulated protrusions, with or without on-street parking area, type of non-motorized vehicle, number of manhole covers, with or without machine non-isolated, number of intersections, percentage of e-bikes, number of bus stops, number of access points, and number of turns (see Figure 2 for details).
(2)
Out-of-Bag Estimation Error Rate
Employing a stepwise random forest approach, beginning with the highest-ranked variable based on the importance score, this study observed that the out-of-bag estimation error rate remained low and stable when limited to six variables. The top six variables, according to their importance scores, were absence of non-motorized lanes, lack of non-motorized segregation, cycling speed, the number of articulated protrusions on the roadway, the division of non-motorized lanes into parking zones, and the type of non-motorized vehicles (refer to Figure 3 for more details). Consequently, this paper infers that with or without non-motorized lanes, with or without human non-isolation, riding speed, the number of roadway articulation protrusions, with or without on-street parking area, and the type of non-motorized vehicles significantly impact riding vibration comfort. In contrast, the influence of the number of manhole covers, with or without machine non-isolated, the number of intersections, the percentage of e-bikes, the number of bus stops, the number of intersections, and the number of turns on riding vibration comfort is not substantial. Among the first six significant influences, in terms of road characteristics, road cross section and road surface are mostly significant factors, while road alignment and longitudinal section are in a non-significant position; in terms of traffic flow characteristics, speed and non-motorized vehicle models are a significant influence, while other influences are significant. In conclusion, it can be seen that the factors of road cross section and road surface as well as the speed of traffic flow and non-motorized vehicle models have a significant effect on riding vibration, while the route alignment and the percentage of different traffic flows have little effect on riding vibration.

4.3. Multifactor Logistic Regression Analysis

Building on the variable importance rankings derived from the random forest analysis, we selected the presence of non-motorized lanes, unmanned non-motorized segregation, riding speed, the count of roadway articulation protrusions, the division of non-motorized lanes into parking zones, and the type of non-motorized vehicles as independent variables, with comfort level as the dependent variable. The analysis revealed that all six factors significantly correlate with non-motorized riding vibration comfort (all p < 0.05). The detailed results are presented in Table 3.
(1)
Correlation Analysis of Dedicated Non-Motorized Lanes
At a relatively uncomfortable level, the likelihood of discomfort in the absence of dedicated non-motorized lanes is 1.276 times higher compared to their presence. Establishing dedicated lanes for non-motorized vehicles can significantly enhance riding vibration comfort. For routes lacking these lanes, improving road surface smoothness is vital to ensure cyclist comfort.
(2)
Correlation Analysis of Non-Segregated Human Forms
The discomfort level in unsegregated, non-segregated areas is 1.196 times greater than in segregated areas. Therefore, the increase in pedestrian traffic under mixed conditions leads to decreased riding vibration comfort, underscoring the importance of installing sidewalks.
(3)
Correlation Analysis of Cycling Speed
For medium- and high-speed riding, the discomfort level is 1.347 and 1.397 times greater, respectively, than for low-speed cycling. Higher speeds reduce the smoothness of vehicle operation. Urban road sections should have speed-limiting signage to encourage slower cycling speeds, ideally around 15 km/h, to ensure traffic safety.
(4)
Correlation Analysis of Road Surface Protrusions
Groups with 1–5 and 6–10 road surface protrusions experience discomfort levels 1.105 and 1.260 times higher, respectively, than groups with no protrusions. Implementing sloping transitions at protrusion points to smooth out height differences is recommended. Additionally, transforming curbside ramps at intersections into sloping or full-width types and positioning manhole covers on the left side of non-motorized lanes can reduce rolling discomfort.
(5)
Correlation Analysis of Roadside Parking Areas
Areas with curb parking are 1.107 times more uncomfortable than those without. Implementing “embedded” parking, which positions spaces between non-motorized and motor vehicle lanes close to the motor vehicle side, could meet parking needs while ensuring safe non-motorized traffic flow.
(6)
Vehicle Type Correlation Analysis
The level of discomfort for electric bicycles is 1.397 times that of traditional bicycles. Electric bicycles, often used for short-distance travel, frequently exceed safe speed limits due to low modification thresholds and regulatory non-compliance. The speed differential between electric and traditional bicycles on non-motorized pathways can reach up to 35 km/h. Moreover, the prevalent use of electric bicycles for urban delivery services leads to speeds as high as 40 km/h. Therefore, stricter traffic control of non-motorized vehicles and a prohibition on the riding of illegally modified electric bicycles are essential.

5. Conclusions

This study delves into the external factors influencing cycling vibration comfort from the perspective of non-motorized cycling. Utilizing the average weighted acceleration of non-motorized riders’ bodies, this research evaluates vibration comfort levels based on characteristics of non-motorized roads and traffic. Employing the random forest algorithm and multifactor logistic regression, this study analyzes factors potentially impacting the level of riding vibration comfort across different sections. Key findings include the following: the experimental route predominantly exhibited levels of slight discomfort and relative comfort in riding vibration; factors like the presence of non-motorized lanes, with or without human non-isolation, riding speed, the number of roadway articulated protrusions, with or without on-street parking area, and the type of non-motorized vehicles significantly affected the comfort level of riding vibration; conversely, the number of manhole covers, with or without machine non-isolated, the number of intersections, the percentage of e-bikes, the number of bus stops, the number of access points, and the number of turns were found to have minimal impact on cycling vibration comfort. It can be seen that road cross section and road surface and speed have a great impact on riding vibration, so riding comfort can be improved by improving or reconstructing the road cross section, maintaining the smoothness of the road surface, and controlling the speed of the vehicle. This research enhances our understanding of the factors affecting non-motorized road cycling, aiding in the refined design of urban non-motorized roads and better supporting people and non-motorized slow traffic.
Owing to experimental constraints, this study was limited to a small number of experimental routes, suggesting the need for a more extensive dataset in future studies, possibly involving other cities. Additionally, as comfort is subjective, non-motorized riders’ personal tolerance to vibration varies. Therefore, further research is warranted to explore how variables like age, gender, and income of the riders may differentially impact their perception of vibration comfort.

Author Contributions

Conceptualization, Y.L.; methodology, Y.L.; software, Y.L.; validation, Y.L. and L.X.; formal analysis, Y.L. and H.X.; investigation, Y.L. and H.X.; resources, Y.L.; data curation, Y.L.; writing—original draft preparation, Y.L.; writing—review and editing, X.H.; visualization, Y.L.; supervision, L.X.; project administration, Y.L.; funding acquisition, Y.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author (The data are not publicly available due to their containing information that could compromise the privacy of research participants).

Acknowledgments

The authors would like to thank the anonymous reviewers and editors for their constructive comments, which were very helpful in improving the paper.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Applsci 14 00441 g001
Figure 1. Schematic diagram of the experimental section.
Figure 1. Schematic diagram of the experimental section.
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Figure 2. Order of importance of variables.
Figure 2. Order of importance of variables.
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Figure 3. Out-of-bag estimation error rate.
Figure 3. Out-of-bag estimation error rate.
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Table 1. Relationship between total acceleration vibration and subjective perception.
Table 1. Relationship between total acceleration vibration and subjective perception.
Acceleration Vibration TotalsSubjective Perception
<0.315No discomfort
0.315~0.63Slightly uncomfortable
0.5~1.0Quite uncomfortable
0.8~1.6Uncomfortable
1.25~2.5Very uncomfortable
>2Extremely uncomfortable
Table 2. Variable assignments.
Table 2. Variable assignments.
Variable NameValue Type Variable TypeVariable Type
Comfort level1 = slightly uncomfortable, 2 = very uncomfortableDependent variable
Number of bus stops1 = 0~5, 2 = 6~10, 3 = >10 Independent variable
Number of intersections1 = 0, 2 = 1, 3 = >1Independent variable
Number of access points1 = 0~5, 2 = 6~10, 3 = >10Independent variable
Number of turns1 = 0, 2 = 1~3, 3 = >4Independent variable
With or without non-motorized lanes1 = no, 2 = yesIndependent variable
With or without machine non-isolated1 = no, 2 = yesIndependent variable
With or without human non-isolation1 = no, 2 = yesIndependent variable
With or without on-street parking area1 = yes, 2 = noIndependent variable
Number of manhole covers1 = 0, 2 = 1~4, 3 = >4Independent variable
Number of roadway articulation protrusions1 = 0, 2 = 1~5, 3 = 6~10Independent variable
Type of non-motorized vehicle1 = bicycle, 2 = electric bicycleIndependent variable
Percentage of e-bikes1 = low, 2 = medium, 3 = highIndependent variable
rRding speed1 = low, 2 = medium, 3 = highIndependent variable
Table 3. Multifactor logistic regression analysis of factors affecting riding vibration comfort.
Table 3. Multifactor logistic regression analysis of factors affecting riding vibration comfort.
VariableBS.E.WaldX2OR (95%CI)p
With or without non-motorized lanes
Yes (control) 1.000
No0.2440.1224.0001.276 (1.005~1.621)0.046
With or without human non-isolation
Yes (control) 1.000
No0.1790.0814.8841.196 (1.020~1.402)0.027
Riding speed
Low (control) 1.000
Medium0.2980.1474.1101.347 (1.010~1.797)0.043
High0.3340.1674.0001.397 (1.007~1.937)0.046
Number of roadway articulated protrusions
0 (control) 1.000
1~50.1000.0474.5271.105 (1.008~1.212)0.033
6~100.2310.1134.1791.260 (1.010~1.572)0.041
With or without on-street parking area
No (control) 1.000
Yes0.1020.0484.5161.107 (1.008~1.217)0.034
Type of non-motorized vehicle
Bicycle (control) 1.000
Electric bicycle0.3340.10110.9361.397 (1.146~1.702)0.001
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Li, Y.; Xu, L.; Huang, X.; Xiao, H. Research on Vibration Comfort of Non-Motorized Lane Riding Based on Three-Axis Acceleration. Appl. Sci. 2024, 14, 441. https://doi.org/10.3390/app14010441

AMA Style

Li Y, Xu L, Huang X, Xiao H. Research on Vibration Comfort of Non-Motorized Lane Riding Based on Three-Axis Acceleration. Applied Sciences. 2024; 14(1):441. https://doi.org/10.3390/app14010441

Chicago/Turabian Style

Li, Yuecheng, Liangjie Xu, Xi Huang, and Hao Xiao. 2024. "Research on Vibration Comfort of Non-Motorized Lane Riding Based on Three-Axis Acceleration" Applied Sciences 14, no. 1: 441. https://doi.org/10.3390/app14010441

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