User experience test method for intelligent network connection heavy truck

Abstract

The invention discloses a user experience test method for an intelligent network connection heavy truck, and aims to comprehensively evaluate user interaction and performance of the intelligent network connection heavy truck in actual use. The experience, including availability, performance and safety of the system, of a heavy truck driver using the intelligent networking function is comprehensively evaluated and improved. In consideration of long-time driving and special operation requirements of a heavy truck driver, the method integrates static and dynamic use case analysis, dynamic driver distraction evaluation, system function and performance testing, system scoring and comprehensive evaluation performed by using a customized system availability scale. According to the invention, a manufacturer can more deeply understand the user experience of the intelligent network connection heavy truck in a real driving environment, so that valuable data support is provided for product design and function improvement. In addition, the method can help to improve the overall safety performance of the vehicle and the satisfaction degree of a driver, and has remarkable market and social values.

Description

Technical Field

[0001] The present invention belongs to the field of vehicle testing technology, and in particular relates to a user experience testing method for an intelligent connected heavy-duty truck. Background Art

[0002] With the convergence of information technology and the automotive industry, intelligent connected vehicles (ICVs) have become a significant development trend in the automotive sector. By integrating advanced information and communication technologies, artificial intelligence, and internet services, these vehicles offer capabilities beyond traditional driving, such as automated driving assistance, intelligent navigation systems, remote monitoring, and vehicle management. However, with this increased functionality comes increased complexity in the user experience (UX), particularly in the field of intelligent connected heavy-duty trucks. The quality of UX directly impacts driving safety, efficiency, and driver satisfaction. Currently, UX testing for ICVs primarily focuses on sedans and small vehicles, while relatively few testing methods exist for heavy-duty trucks.

[0003] Intelligent connected heavy-duty trucks differ significantly from sedans and compact cars in terms of functionality and usage scenarios. For example, heavy-duty trucks are often used for long-distance transport and commercial activities, which requires onboard systems to have higher reliability and continuous operation capabilities. Furthermore, driver comfort and user-friendly interfaces during extended driving periods are crucial to reducing fatigue and improving safety.

[0004] Testing methods for related technologies often focus on a single aspect, such as user-friendliness or system performance. Furthermore, many rely on subjective feedback and user surveys. While valuable for capturing intuitive user experiences, these methods are limited in terms of quantitative analysis and objectivity. There is a lack of more comprehensive and systematic testing methods to evaluate the user experience of connected heavy-duty trucks, particularly those focused on ensuring safety and improving operational efficiency. Summary of the Invention

[0005] The purpose of the present invention is to propose a user experience testing method for intelligent connected heavy-duty trucks to solve the problems in the prior art.

[0006] To this end, the present invention provides a user experience testing method for an intelligent connected heavy-duty truck, comprising:

[0007] S100, based on preset cases, analyzes and evaluates the user experience in multiple dimensions under static and dynamic conditions;

[0008] S200, in dynamic driving scenarios, assesses the user's ability to cope with visual distractions, manual distractions, and cognitive distractions, obtains distraction level assessment data, and generates a score based on the combined assessment data;

[0009] S300: Evaluate the vehicle's hardware performance, software system, and application functions, obtain evaluation data, and assign a score based on the evaluation data;

[0010] S400: Evaluate the vehicle's navigation system, Bluetooth performance, network performance, and the quality and reliability of various services, obtain evaluation data, and assign a score based on the evaluation data;

[0011] S500 evaluates the appearance, feel, and system response speed of key vehicle components, obtains evaluation data, and assigns a score based on the evaluation data;

[0012] S600: quantify the vehicle usage experience based on the scores of steps S100-S500 and in combination with the SUS scale.

[0013] In some embodiments, in step S100, the step of analyzing and evaluating the user's usage experience in multiple dimensions under static and dynamic conditions includes:

[0014] S110, selecting a preset case, wherein the preset case includes interactive operations of navigation, communication, entertainment system, and driving assistance system;

[0015] S120, evaluating the logic of the interface layout, the clarity of the menu structure, the simplicity of user command input, and the visual effect of information presentation based on predefined interface evaluation criteria, wherein the interface evaluation criteria include visual clarity, ease of operation, and speed of information access;

[0016] S130, in a real vehicle or high-fidelity simulation environment, evaluating the user's perception of system response time, the real-time nature of system feedback, and cognitive load during complex driving tasks based on quantitative indicators, wherein the quantitative indicators include system response time, error rate, and user satisfaction;

[0017] S140 is scored based on comprehensive evaluation criteria and the evaluation data of S110-S130. The comprehensive evaluation criteria include the intuitiveness of the interface, the ease of users getting help and feedback, the ability of users to customize and select functions, the consistency of the interface and functions, the simplicity and directness of the interface and operations, and the depth and diversity of information presented.

[0018] In some embodiments, in step S200, the steps of evaluating the user's state of coping with visual distraction, manual distraction, and cognitive distraction, obtaining evaluation data, and scoring based on the multiple evaluation data include:

[0019] S210, presetting an evaluation plan, wherein the evaluation plan includes standardized driving tasks performed in a real vehicle or a high-simulation driving simulator environment to simulate a variety of typical driving scenarios;

[0020] S220, using an eye tracking device to quantify data of the driver when performing a standardized driving task, the data including the frequency and duration of gaze deviation, and comparing the data with baseline data in a no-operation state;

[0021] S230, quantifying data of the driver's physical interactions with the intelligent connected system when performing a standardized driving task, the data including the number and duration of physical interactions;

[0022] S240 uses a tool to test and obtain cognitive load data of drivers when using intelligent connected systems. The test items include memory and reaction tasks presented to the driver at specific time intervals;

[0023] S250 , combining the data obtained in steps S220 - S240 , and scoring the degree of driver distraction caused by the system.

[0024] In some embodiments, in step S210 , the driving scenarios simulated by the preset evaluation scheme include at least urban driving scenarios, highway scenarios, and emergency scenarios.

[0025] In some embodiments, in step S300, the step of evaluating the vehicle's hardware performance, software system, and application program functions and obtaining evaluation data includes:

[0026] S310, evaluating the performance of connected services in the intelligent connected vehicle based on evaluation criteria, including real-time traffic information updates, remote control functions, and vehicle status monitoring; the evaluation criteria include service response time, data update frequency, accuracy, and reliability;

[0027] S320, performing a performance evaluation of hardware components within the vehicle, including sensors, cameras, and processors, based on evaluation criteria, including hardware response speed, accuracy, durability, and compatibility;

[0028] S330 evaluates the in-vehicle software system, including the operating system, user interface, and applications, assessing software stability, user interface usability, and software update and maintenance capabilities;

[0029] S340, evaluating the functionality of mobile applications associated with the intelligent connected vehicle based on evaluation criteria, wherein the evaluation criteria include application compatibility, user interface design, functional diversity, and operational fluency;

[0030] S350: Based on the evaluation results obtained in steps S310-S340, a comprehensive score is given to the overall functions and performance of the intelligent connected vehicle.

[0031] In some embodiments, in step S400, the steps of evaluating the vehicle's navigation system, Bluetooth performance, network performance, and the quality and reliability of various services and obtaining evaluation data include:

[0032] S410, evaluating the speech recognition capability of the intelligent connected vehicle system based on evaluation criteria, wherein the speech recognition capability includes recognition rate, response time, and adaptability to different accents or speaking styles, wherein the evaluation criteria are based on recognition accuracy and error rate, and performance under various noise conditions;

[0033] S420, evaluating the connection stability and data transmission rate between the vehicle and the external network based on evaluation criteria, wherein the evaluation criteria include connection establishment time, stability, and connectivity performance in different environments;

[0034] S430, evaluating the accuracy, user-friendliness, and route planning efficiency of the in-vehicle navigation system based on evaluation criteria, wherein the evaluation criteria include route calculation time, update frequency, and user satisfaction survey results;

[0035] S440, evaluating the availability, accuracy, and timeliness of various services provided by the intelligent connected vehicle based on evaluation criteria, wherein the evaluation criteria include reliability and coverage of the services;

[0036] S450, evaluating the overall reliability of the system, including the failure rate, maintenance requirements, and long-term stability of the system, based on evaluation criteria, including the frequency of failures and maintenance records;

[0037] S460, evaluating the stability of the Bluetooth connection, the ease of the connection process, and the data transmission rate based on evaluation criteria, wherein the evaluation criteria include connection success rate, connection time, and cross-device compatibility;

[0038] S470 , based on the evaluation results obtained in steps S410 - S460 , comprehensively score the above functions of the intelligent connected vehicle.

[0039] In some embodiments, in step S500, the step of evaluating the appearance, tactile feel, and system response speed of key components of the vehicle and obtaining evaluation data includes:

[0040] S510: Evaluate the exterior design of key system components of intelligent connected vehicles based on the evaluation criteria. Evaluation items include the visual presentation of the user interface, the design of physical buttons and control panels. The evaluation criteria include the design's aesthetics, modernity, and coordination with the overall vehicle design.

[0041] S520 evaluates the tactile elements of the vehicle interior, including the physical interfaces of touchscreens, buttons, and knobs. The scoring criteria include material texture, quality of tactile feedback, and user comfort.

[0042] S530, evaluating the responsiveness of the intelligent connected vehicle system based on evaluation criteria, including user interface responsiveness, voice command responsiveness, and the response time of any remote control function. The scoring criteria include the system's average response time, response consistency, and stability under different operating conditions.

[0043] S540 , based on the evaluation results obtained in steps S510 - S530 , comprehensively score the above functions of the intelligent connected vehicle.

[0044] In some embodiments, in step S600, including S610, evaluation is performed based on multiple evaluation dimensions, and the SUS scale includes multiple evaluation dimensions, and the evaluation dimensions include system usability, user interface intuitiveness, ease of operation, system response time, functional integrity, and user satisfaction.

[0045] In some embodiments, step S600 includes S620, where each question in the SUS scale is scored using a five-point Likert scale with a score range from 1 to 5. After obtaining the score of the question, all scores are weighted averaged, and the weight coefficient is adjusted based on the usage scenario to obtain a comprehensive score, and the user experience is judged based on the comprehensive score.

[0046] In some embodiments, in step S620, the steps of calculating the comprehensive score using the SUS scale and providing a conclusion are:

[0047] Subtract 1 from the score of all odd-numbered questions;

[0048] For all even-numbered questions, the score is subtracted from 5;

[0049] Add the adjusted scores and multiply by 2.5 to get an overall score from 0 to 100;

[0050] The overall score is compared with the preset target. If the overall score is greater than the preset score, it is judged to be an above-average user experience. If the overall score is less than the preset score, it is judged that the user experience needs improvement.

[0051] Beneficial effects:

[0052] 1. The present invention provides a user experience testing method for intelligent connected heavy-duty trucks, which provides a more comprehensive testing framework compared to the single or one-sided evaluation methods in the prior art. This method covers everything from static and dynamic use case analysis to system performance and functional testing. It uses multi-dimensional evaluation combined with the SUS scale for quantitative analysis to provide a comprehensive and objective evaluation of the user experience. It focuses on the special usage scenarios of heavy-duty trucks, filling the gaps in existing testing in the heavy-duty truck field, effectively improving the pertinence and practicality of the evaluation, and providing key data to vehicle manufacturers to help them better understand user needs and guide future product design and function optimization. It is of great significance to improving driving safety, efficiency and user satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0054] Figure 1 This is a flowchart of the user experience testing method for intelligent connected heavy-duty trucks provided by the present invention.

[0055] Figure 2 This is a diagram of user experience evaluation dimensions in the user experience testing method for intelligent connected heavy-duty trucks provided by the present invention. DETAILED DESCRIPTION

[0056] The present invention may be more readily understood by referring to the following detailed description of preferred embodiments of the present invention and the included Examples. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention pertains. In the event of a conflict, the definitions in this specification shall prevail.

[0057] Example 1:

[0058] like Figure 1-2 As shown, a user experience testing method for an intelligent connected heavy-duty truck includes:

[0059] S100 analyzes and evaluates the user experience in multiple dimensions under static and dynamic conditions based on preset use cases. Specifically, a set of predefined use cases are used to conduct static and dynamic analysis of the user experience, with multiple evaluation dimensions including intuitiveness, support, flexibility, consistency, simplicity, depth, and presentation.

[0060] S200 assesses the user's ability to handle visual, manual, and cognitive distractions in dynamic driving scenarios, obtains distraction data, and then generates a score based on this data. Specifically, using specific assessment tools and methods, it quantitatively analyzes the driver's visual, manual, and cognitive distractions when using the intelligent connected system, including the frequency and duration of deviations from the road.

[0061] S300 evaluates the vehicle's hardware performance, software system, and application functions and obtains evaluation data, and scores based on the evaluation data to meet predetermined user experience standards.

[0062] S400: Evaluate the vehicle's navigation system, Bluetooth performance, network performance, and the quality and reliability of various services, obtain evaluation data, and assign a score based on the evaluation data;

[0063] S500 evaluates the appearance, feel, and system response speed of key vehicle components, obtains evaluation data, and assigns a score based on the evaluation data;

[0064] S600: quantify the vehicle usage experience based on the scores of steps S100-S500 and in combination with the SUS scale.

[0065] Through the above technical solution, compared with the single or one-sided evaluation method in the prior art, the present invention provides a more comprehensive testing framework, covering everything from static and dynamic use case analysis to system performance and functional testing, providing a comprehensive evaluation of user experience and providing key data to vehicle manufacturers, which can help vehicle manufacturers better understand user needs and guide future product design and functional testing.

[0066] In one embodiment, in step S100, the steps of analyzing and evaluating the user's usage experience in multiple dimensions under static and dynamic conditions include:

[0067] S110: Select a preset use case, wherein the preset use case includes interactive operations of navigation, communication, entertainment systems, and driver assistance systems. Specifically, select representative use cases that cover the core functions of an intelligent connected heavy-duty truck, namely, the interactive operations of the navigation, communication, entertainment systems, and driver assistance systems.

[0068] S120: Based on predefined interface evaluation criteria, evaluate the logic of the interface layout, the clarity of the menu structure, the simplicity of user command input, and the visual effect of information presentation. The interface evaluation criteria include visual clarity, ease of operation, and information access speed, which is a static analysis of the heavy-duty truck intelligent network system.

[0069] S130: In a real vehicle or high-fidelity simulation environment, the user's perception of system reaction time, the real-time nature of system feedback, and the cognitive load under complex driving tasks are evaluated based on quantitative indicators. The quantitative indicators include system response time, error rate, and user satisfaction, which is a dynamic analysis of the heavy-duty truck intelligent network system.

[0070] S140 is scored based on comprehensive evaluation criteria, including the intuitiveness of the interface, ease of getting help and feedback, the ability to customize and select features, consistency of interface and functionality, simplicity and directness of interface and operation, and the depth and diversity of information presented. This comprehensive analysis of both static and dynamic data, combined with scoring, helps capture the user experience more accurately and comprehensively.

[0071] In one embodiment, in step S200, the steps of evaluating the user's state of coping with visual interference, manual interference, and cognitive interference, obtaining evaluation data, and scoring based on the multiple evaluation data include:

[0072] S210, by setting a preset evaluation scheme to evaluate the user's various interference scenarios during dynamic driving, the evaluation scheme includes standardized driving tasks performed in a real car or a high-simulation driving simulator environment to simulate a variety of typical driving scenarios. Typical driving scenarios include urban driving scenarios, highway scenarios, and emergency scenarios. Furthermore, the evaluation scheme includes three independent but related evaluation tasks, specifically including visual attention evaluation, manual operation evaluation, and cognitive load evaluation. The specific evaluation steps are as follows:

[0073] S220: When conducting a visual attention assessment, an eye-tracking device is used to quantify data on the driver's performance of a standardized driving task. This data includes the frequency and duration of gaze deviations, particularly when operating the intelligent connected system. This data allows for greater focus on the use of the intelligent connected system and its impact on user distraction. This data is then compared with baseline data when the system is not in use. Evaluation criteria include the average increase in gaze deviation frequency and the average duration of gaze deviation from the road ahead compared to normal driving.

[0074] S230: During the manual operation assessment, the driver's specific actions in operating the intelligent connected system are recorded during the same driving simulation task, and data on the driver's physical interactions with the intelligent connected system while performing the standardized driving task is quantified. This data includes the number and duration of physical interactions, such as the impact on user distraction when operating a touch screen or pressing a button. Furthermore, a motion recognition system can be used for recording and analysis.

[0075] S240: When conducting a cognitive load assessment, a tool is used to test and obtain cognitive load data for the driver while using the intelligent connected system. The test items include memory and reaction tasks presented to the driver at specific time intervals. Specifically, the memory and reaction tasks, or cognitive tasks, implemented include a continuous digit memory test, which requires the driver to recall and respond to a series of digits displayed on a screen during a driving simulation. The evaluation criteria include the driver's error rate and response time when performing this task, which are compared with the baseline performance in a non-driving state.

[0076] S250 , combining the data obtained in steps S220 - S240 , and scoring the degree of driver distraction caused by the system.

[0077] Through the above technical solutions, the present invention focuses on the problem of driver distraction in dynamic environments, which is often overlooked in existing technologies. By evaluating visual, manual, and cognitive distractions, the present invention can more accurately assess the safety and efficiency of intelligent connected vehicles in actual use.

[0078] In one embodiment, in step S300, the steps of evaluating the vehicle's hardware performance, software system, and application functions, i.e., the functions and performance of the intelligent connected system, and obtaining evaluation data include:

[0079] S310, evaluating connected services: evaluating the performance of connected services in the intelligent connected vehicle based on evaluation criteria, including real-time traffic information updates, remote control functions, and vehicle status monitoring; the evaluation criteria include service response time, data update frequency, accuracy, and reliability;

[0080] S320, evaluating hardware performance: performing a performance evaluation on hardware components in the vehicle, including sensors, cameras, and processors, based on evaluation criteria, including hardware response speed, accuracy, durability, and compatibility;

[0081] S330, Software System Assessment: Evaluate the vehicle's software system, including the operating system, user interface, and applications, assessing software stability, user interface usability, and software update and maintenance capabilities;

[0082] S340, evaluating APP functions: evaluating the functions of mobile applications associated with the intelligent connected vehicle based on evaluation criteria, including application compatibility, user interface design, functional diversity, and operational fluency;

[0083] S350: Based on the evaluation results obtained in steps S310-S340, a comprehensive score is given to the overall functions and performance of the intelligent connected vehicle. The scoring criteria include user experience, system stability, and performance efficiency.

[0084] In one embodiment, in step S400, the steps of evaluating the vehicle's navigation system, Bluetooth performance, network performance, and the quality and reliability of various services and obtaining evaluation data include:

[0085] S410, evaluating speech recognition: evaluating the speech recognition capability of the intelligent connected vehicle system based on evaluation criteria, wherein the speech recognition capability includes recognition rate, response time, and adaptability to different accents or speaking styles. The evaluation criteria are based on recognition accuracy and error rate, as well as performance under various noise conditions.

[0086] S420 , evaluating network connectivity: evaluating the connection stability and data transmission rate between the vehicle and the external network based on evaluation criteria, wherein the evaluation criteria include connection establishment time, stability, and connectivity performance in different environments;

[0087] S430, evaluating the navigation system: evaluating the accuracy, user-friendliness, and route planning efficiency of the in-vehicle navigation system based on evaluation criteria, including route calculation time, update frequency, and user satisfaction survey results;

[0088] S440, evaluating service quality: evaluating the availability, accuracy, and timeliness of various services provided by the intelligent connected vehicle based on evaluation criteria, wherein the evaluation criteria include reliability and coverage of the services;

[0089] S450, evaluating reliability: evaluating the overall reliability of the system, including the failure rate, maintenance requirements, and long-term stability of the system, based on evaluation criteria, including failure frequency and maintenance records;

[0090] S460, evaluating the Bluetooth connection: evaluating the stability of the Bluetooth connection, the simplicity of the connection process, and the data transmission rate based on evaluation criteria, wherein the evaluation criteria include connection success rate, connection time, and cross-device compatibility;

[0091] S470 , based on the evaluation results obtained in steps S410 - S460 , comprehensively score the above functions of the intelligent connected vehicle.

[0092] In one embodiment, in step S500, the steps of evaluating the appearance, tactile feel, and system response speed of key components of the vehicle and obtaining evaluation data include:

[0093] S510, Appearance Evaluation: Evaluate the appearance design of key system components of intelligent connected vehicles based on evaluation criteria. Evaluation items include the visual presentation of the user interface, the design of physical buttons and control panels. The evaluation criteria include the aesthetics, modernity, and coordination with the overall vehicle design.

[0094] S520, tactile evaluation: Evaluates the tactile elements of the vehicle interior, including the physical interfaces of touchscreens, buttons, and knobs. Scoring criteria include material texture, quality of tactile feedback, and user comfort.

[0095] S530, evaluating response speed: Based on evaluation criteria, evaluating the response speed of the intelligent connected vehicle system, including user interface response, voice command response, and response time of any remote control function. The scoring criteria include the system's average response time, response consistency, and stability under different operating conditions.

[0096] S540, based on the evaluation results obtained in steps S510-S530, comprehensively score the above functions of the intelligent connected vehicle. Combined with the scores of the above aspects, a weighted calculation is adopted, in which appearance, touch and response speed include custom weights. The comprehensive score reflects the overall user experience quality of the system and its competitiveness in the market.

[0097] In one embodiment, step S600 includes:

[0098] S610 , performing evaluation based on multiple evaluation dimensions, wherein the SUS scale includes multiple evaluation dimensions, and the evaluation dimensions include system usability, user interface intuitiveness, ease of operation, system response time, functional integrity, and user satisfaction.

[0099] S620: Score each question in the SUS scale. Each question in the SUS scale is scored using a five-point Likert scale with a score range from 1 to 5. After obtaining the score of the question, perform a weighted average on all scores and adjust the weight coefficient based on the usage scenario to obtain a comprehensive score. Judge the user experience based on the comprehensive score.

[0100] Specifically, a customized System Usability (SUS) scale, designed specifically for the user experience of connected vehicles (ICVs), was used. This SUS scale includes a series of questions specific to the functions and services of ICVs. This customized SUS scale covers multiple evaluation dimensions, including system usability, user interface intuitiveness, ease of operation, system response time, functional completeness, and user satisfaction. Each question in the customized SUS scale is scored using a five-point Likert scale (a Likert scale typically consists of a set of statements, each representing a viewpoint or attitude description on a topic. Respondents are asked to select from several rating options based on their actual feelings or degree of agreement with each statement). The score ranges from 1 (strongly disagree) to 5 (strongly agree). Each question is designed to capture users' intuitive reactions and satisfaction with specific ICV features. The overall SUS score is calculated by taking a weighted average of the scores for all questions and adjusting the weighting coefficient based on the specific usage scenario of the ICV. For example, subtract 1 from the scores of all odd-numbered questions and subtract 5 from the scores of all even-numbered questions. Then, add these adjusted scores and multiply by 2.5 to obtain an overall score from 0 to 100. Based on the overall score obtained, the user experience is judged. For example, a score over 68 is considered an above-average user experience, while a score below 68 indicates that the user experience needs improvement. In addition, pay special attention to scores between 75 and 85, which generally indicate an excellent user experience, and scores above 85 indicate excellent system usability and user satisfaction.

[0101] Through the above technical solutions, the present invention provides specific and operational evaluation methods and standards, which not only have significant innovations compared to existing technologies in theory, but also have high practicality and operability in actual applications.

[0102] Example 2:

[0103] The simulation data assumed in this embodiment is that in a simulated driving test, the driver interacted with the intelligent connected system multiple times during a one-hour driving process.

[0104] Through the eye tracking device, the present invention collected the following data: the average frequency of the eyes leaving the road: 20 times per hour; the average duration of each time the eyes leave the road: 4 seconds.

[0105] Gaze deviation frequency score: Set a baseline frequency of 10 times per hour and compare the actual frequency to this.

[0106] Calculation method:

[0107] Example calculation:

[0108] Gaze deviation duration scoring: The baseline average duration was set at 2 seconds.

[0109] Calculation method:

[0110] Example calculation:

[0111] Evaluation criteria: A score above 0% indicates better performance than the baseline, and a score below 0% indicates worse performance than the baseline. For driving safety, the scores for the frequency and duration of gaze deviation should be as close to or above 0% as possible.

[0112] Interpretation of Results: In this example, both the frequency and duration scores were -100%, significantly lower than baseline levels. This indicates that the driver frequently took their eyes off the road while using the connected car system, and each time they did so, the duration was significant. This suggests that the connected car system may be excessively distracting the driver, increasing driving risk. Based on the above analysis, the present inventors conclude that improvements are needed in terms of visual distraction to reduce driver gaze deviation during use, thereby improving driving safety.

[0113] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A user experience testing method for intelligent connected heavy-duty trucks, characterized in that: include: S100, based on preset cases, analyzes and evaluates the user experience in multiple dimensions under static and dynamic conditions; S200, in dynamic driving scenarios, assesses the user's ability to cope with visual distractions, manual distractions, and cognitive distractions, obtains distraction level assessment data, and generates a score based on the combined assessment data; S300: Evaluate the vehicle's hardware performance, software system, and application functions, obtain evaluation data, and assign a score based on the evaluation data; S400: Evaluate the vehicle's navigation system, Bluetooth performance, network performance, and the quality and reliability of various services, obtain evaluation data, and assign a score based on the evaluation data; S500 evaluates the appearance, feel, and system response speed of key vehicle components, obtains evaluation data, and assigns a score based on the evaluation data; S600: quantify the vehicle usage experience based on the scores of steps S100-S500 and in combination with the SUS scale.

2. The user experience testing method for intelligent connected heavy trucks according to claim 1, characterized in that: In step S100, the steps of analyzing and evaluating the user's usage experience in multiple dimensions under static and dynamic conditions include: S110, selecting a preset case, wherein the preset case includes interactive operations of navigation, communication, entertainment system, and driving assistance system; S120, evaluating the logic of the interface layout, the clarity of the menu structure, the simplicity of user command input, and the visual effect of information presentation based on predefined interface evaluation criteria, wherein the interface evaluation criteria include visual clarity, ease of operation, and speed of information access; S130, in a real vehicle or high-fidelity simulation environment, evaluating the user's perception of system response time, the real-time nature of system feedback, and cognitive load during complex driving tasks based on quantitative indicators, wherein the quantitative indicators include system response time, error rate, and user satisfaction; S140 is scored based on comprehensive evaluation criteria and the evaluation data of S110-S130. The comprehensive evaluation criteria include the intuitiveness of the interface, the ease of users getting help and feedback, the ability of users to customize and select functions, the consistency of the interface and functions, the simplicity and directness of the interface and operations, and the depth and diversity of information presented.

3. The user experience testing method for intelligent connected heavy-duty trucks according to claim 1, characterized in that: In step S200, the steps of evaluating the user's state of coping with visual interference, manual interference, and cognitive interference, obtaining evaluation data, and scoring based on the multiple evaluation data include: S210, presetting an evaluation plan, wherein the evaluation plan includes standardized driving tasks performed in a real vehicle or a high-simulation driving simulator environment to simulate a variety of typical driving scenarios; S220, using an eye tracking device to quantify data of the driver when performing a standardized driving task, the data including the frequency and duration of gaze deviation, and comparing the data with baseline data in a no-operation state; S230, quantifying data of the driver's physical interactions with the intelligent connected system when performing a standardized driving task, the data including the number and duration of physical interactions; S240 uses a tool to test and obtain cognitive load data of drivers when using intelligent connected systems. The test items include memory and reaction tasks presented to the driver at specific time intervals; S250 , combining the data obtained in steps S220 - S240 , and scoring the degree of driver distraction caused by the system.

4. The user experience testing method for intelligent connected heavy trucks according to claim 3, characterized in that: In step S210 , the driving scenarios simulated by the preset evaluation scheme include at least urban driving scenarios, highway scenarios, and emergency scenarios.

5. The user experience testing method for intelligent connected heavy trucks according to claim 1, characterized in that: In step S300, the steps of evaluating the vehicle's hardware performance, software system, and application program functions and obtaining evaluation data include: S310, evaluating the performance of connected services in the intelligent connected vehicle based on evaluation criteria, including real-time traffic information updates, remote control functions, and vehicle status monitoring; the evaluation criteria include service response time, data update frequency, accuracy, and reliability; S320, performing a performance evaluation of hardware components within the vehicle, including sensors, cameras, and processors, based on evaluation criteria, including hardware response speed, accuracy, durability, and compatibility; S330 evaluates the in-vehicle software system, including the operating system, user interface, and applications, assessing software stability, user interface usability, and software update and maintenance capabilities; S340, evaluating the functionality of mobile applications associated with the intelligent connected vehicle based on evaluation criteria, wherein the evaluation criteria include application compatibility, user interface design, functional diversity, and operational fluency; S350: Based on the evaluation results obtained in steps S310-S340, a comprehensive score is given to the overall functions and performance of the intelligent connected vehicle.

6. The user experience testing method for intelligent connected heavy trucks according to claim 1, characterized in that: In step S400, the steps of evaluating the vehicle's navigation system, Bluetooth performance, network performance, and the quality and reliability of various services and obtaining evaluation data include: S410, evaluating the speech recognition capability of the intelligent connected vehicle system based on evaluation criteria, wherein the speech recognition capability includes recognition rate, response time, and adaptability to different accents or speaking styles, wherein the evaluation criteria are based on recognition accuracy and error rate, and performance under various noise conditions; S420, evaluating the connection stability and data transmission rate between the vehicle and the external network based on evaluation criteria, wherein the evaluation criteria include connection establishment time, stability, and connectivity performance in different environments; S430, evaluating the accuracy, user-friendliness, and route planning efficiency of the in-vehicle navigation system based on evaluation criteria, wherein the evaluation criteria include route calculation time, update frequency, and user satisfaction survey results; S440, evaluating the availability, accuracy, and timeliness of various services provided by the intelligent connected vehicle based on evaluation criteria, wherein the evaluation criteria include reliability and coverage of the services; S450, evaluating the overall reliability of the system, including the failure rate, maintenance requirements, and long-term stability of the system, based on evaluation criteria, including the frequency of failures and maintenance records; S460, evaluating the stability of the Bluetooth connection, the ease of the connection process, and the data transmission rate based on evaluation criteria, wherein the evaluation criteria include connection success rate, connection time, and cross-device compatibility; S470 , based on the evaluation results obtained in steps S410 - S460 , comprehensively score the above functions of the intelligent connected vehicle.

7. The user experience testing method for intelligent connected heavy trucks according to claim 1, characterized in that: In step S500, the steps of evaluating the appearance, tactile feel, and system response speed of key components of the vehicle and obtaining evaluation data include: S510: Evaluate the exterior design of key system components of intelligent connected vehicles based on the evaluation criteria. Evaluation items include the visual presentation of the user interface, the design of physical buttons and control panels. The evaluation criteria include the design's aesthetics, modernity, and coordination with the overall vehicle design. S520 evaluates the tactile elements of the vehicle interior, including the physical interfaces of touchscreens, buttons, and knobs. The scoring criteria include material texture, quality of tactile feedback, and user comfort. S530, evaluating the responsiveness of the intelligent connected vehicle system based on evaluation criteria, including user interface responsiveness, voice command responsiveness, and the response time of any remote control function. The scoring criteria include the system's average response time, response consistency, and stability under different operating conditions. S540 , based on the evaluation results obtained in steps S510 - S530 , comprehensively score the above functions of the intelligent connected vehicle.

8. The user experience testing method for an intelligent connected heavy truck according to claim 1, characterized in that: In step S600 , including S610 , evaluation is performed based on multiple evaluation dimensions, and the SUS scale includes multiple evaluation dimensions, and the evaluation dimensions include system usability, user interface intuitiveness, ease of operation, system response time, functional integrity, and user satisfaction.

9. The user experience testing method for intelligent connected heavy trucks according to claim 1, characterized in that: In step S600, including S620, each question in the SUS scale is scored using a five-point Likert scale with a score range from 1 to 5. After obtaining the score of the question, all scores are weighted averaged, and the weight coefficient is adjusted based on the usage scenario to obtain a comprehensive score, and the user experience is judged based on the comprehensive score.

10. The user experience testing method for an intelligent connected heavy truck according to claim 9, characterized in that: In step S620, the steps of calculating the comprehensive score using the SUS scale and making a conclusion are as follows: Subtract 1 from the score of all odd-numbered questions; For all even-numbered questions, the score is subtracted from 5; Add the adjusted scores and multiply by 2.5 to get an overall score from 0 to 100; The overall score is compared with the preset target. If the overall score is greater than the preset score, it is judged to be an above-average user experience. If the overall score is less than the preset score, it is judged that the user experience needs improvement.

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