Bicycle riding risk perception test method based on immersive virtual reality interaction platform

Abstract

The present application relates to a kind of riding risk perception test methods based on immersive virtual reality interactive platform, the method is by constructing virtual reality traffic scene, simulation builds immersive virtual reality interactive test platform, let rider simulate real riding behavior in virtual scene, by recording the speed, acceleration and other riding data of rider, jointly use the objective data of riding behavior in virtual reality and risk perception subjective data to carry out risk assessment, construct dynamic risk assessment model applicable to immersive virtual reality interactive platform, and study the reaction behavior of rider under traffic conflict scene, test the perception and response ability of rider to riding risk.The present application can provide theoretical basis for slow traffic safety analysis, and the test results can be targeted to propose safety suggestions, so as to improve the traffic safety consciousness of rider and reduce the occurrence of traffic accident.

Description

Technical Field

[0001] This invention relates to the fields of virtual reality technology and cycling risk perception, and in particular to a cycling risk perception testing method based on an immersive virtual reality interactive platform. Background Technology

[0002] In today's urban traffic environment, cycling, as a low-carbon and healthy mode of slow transportation, is gaining popularity. However, as a slow-moving mode of travel, the traffic safety issues associated with bicycles cannot be ignored. Therefore, conducting bicycle risk assessments is particularly important.

[0003] Traditional bicycle risk assessment research suffers from a lack of dynamic data and difficulty in capturing risk perception. It typically employs static data and SP (Special Perception) surveys to infer risk experience levels; however, this approach often fails to meet the needs of real-world bicycle risk assessment. Furthermore, real-world scenario experiments involve hazardous situations and procedures, resulting in lower safety levels, higher costs, and more complex processes, making real-time risk testing and assessment difficult. Summary of the Invention

[0004] Purpose of the Invention: This invention provides a method for testing cycling risk perception based on an immersive virtual reality interactive platform, aiming to address the problems of lacking dynamic data and difficulty in capturing risk perception in traditional bicycle risk assessment research. This invention combines the high immersion, strong interactivity, and ease of design of virtual reality technology to design and develop an immersive virtual reality interactive platform for conducting bicycle risk assessment and studying its impact on cyclist behavior. Based on the Unity3D virtual reality development platform, the system realizes semi-physical cycling simulation in an immersive virtual reality environment, supporting first-person perspective cycling and 3D traffic simulation.

[0005] Technical solution: The present invention provides a method for testing cycling risk perception based on an immersive virtual reality interactive platform, comprising the following steps:

[0006] Step 1: Install bicycles and VR equipment to build an immersive virtual reality interactive platform;

[0007] Step 2: Based on the immersive virtual reality interactive platform, construct a virtual cycling scene using 3D modeling software. In the virtual cycling scene, the static elements are the 3D model and truck parameters, and the dynamic elements are the bicycle parameters.

[0008] Step 3: Collect cycling data from cyclists in a virtual cycling scenario;

[0009] Step 4: Based on the cyclist's cycling data, static elements, and dynamic elements in the virtual cycling scenario, construct a risk assessment model to evaluate the cyclist's cycling behavior, analyze the cyclist's perception of and ability to cope with cycling risks, and provide targeted cycling safety recommendations based on the analysis results.

[0010] Furthermore, in step 1, the VR device includes a virtual reality headset, controllers, and trackers.

[0011] Furthermore, step 1 specifically includes:

[0012] Step 1.1: Secure the bicycle to the stationary riding platform, install resistance units, and simulate the effect of riding a bicycle on the ground;

[0013] Step 1.2: Set up the VR equipment by attaching the controller to the bicycle handlebars. The rider controls the bicycle to turn left by pressing the trigger button on the left handlebar and to turn right by pressing the trigger button on the right handlebar. The rider brakes by pressing the bicycle brake button and the pad button on the controller at the same time.

[0014] The tracker is attached to the cyclist's ankle, and the coordinate position information of the tracker is obtained through a script, which is then converted into the required data to control the bicycle speed; a virtual reality headset is worn on the cyclist's head.

[0015] Step 1.3: Connect the VR device to the Unity software using the SteamVR tool.

[0016] Furthermore, in step 2, the virtual cycling scenario selects an intersection with potential collisions. The experiment is conducted in two scenarios: a scenario with vehicle conflict and a scenario without vehicle conflict.

[0017] Furthermore, in step 4, a risk assessment model is constructed, where the formulas for potential risk variables are as follows:

[0018] θ real-risk =δ real-feel +γ dist ·x dist +γ car-present ·x car-present +ε α

[0019] In the formula: x dist x represents the distance (m) from the cyclist to the point of collision; car-present ε is a dummy variable; it takes the value 1 if a car is present at the intersection at the current time, and 0 otherwise. α It is an error term; γ dist The impact of the cyclist's distance from the point of collision on risk perception; γ car-presentThis is an additional change in risk perception if a car appears at the intersection; δ real-feel It is a collection of more complex perceived risk factors that cyclists face in reality. This parameter needs to be calibrated by conducting multiple virtual experiments and comparing it with real data.

[0020] The risk assessment model is as follows:

[0021]

[0022] Where the subscript i represents acceleration, deceleration, braking, constant speed, and waiting behavior; δ i ε represents the constant term for each action; ε is an error term that follows a Gumbel distribution. and The parameters represent the impact of the distance to the collision point on the utility of each action, categorized as Level 1, Level 2, and Level 3. and The effects of the cyclist's speed on the utility of each action are categorized into three levels: Level 1, Level 2, and Level 3. This indicates whether the vehicle's position at the intersection affects the utility of each action; This indicates the impact of potential risks on different actions; This indicates whether a collision will occur given the presence of a vehicle and the current speed and remaining distance. A value of 1 indicates a collision, and a value of 0 indicates no collision. Indicates the remaining time until collision; This indicates the effect of the remaining time before each action causes a collision.

[0023] Beneficial effects: Compared with the prior art, the present invention, using the above technical solution, has the following technical effects:

[0024] (1) This invention constructs a VR cycling semi-physical simulation system, which, through actual measurement and simulation, more accurately acquires cyclist behavior data, thereby more accurately assessing risks. Simultaneously, the system can record cyclist behavior data in real time, facilitating subsequent research;

[0025] (2) This invention constructs a risk assessment model and considers potential perceived risk factors. Traditional risk assessment methods usually use static data and SP surveys, while this paper considers dynamic data and potential perceived risk factors, thus assessing risks more accurately;

[0026] (3) This invention constructs a cycling risk perception test method based on an immersive virtual reality interactive platform. Based on the Unity3D virtual reality development platform, UnityVR is developed to design a semi-physical cycling simulation system that supports an immersive virtual reality environment. Dynamic data of cycling behavior in virtual reality is obtained, a risk assessment model is constructed, and the rider's perception and coping ability of cycling risks are analyzed, which effectively improves the awareness of bicycle traffic safety and minimizes the occurrence of traffic accidents. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the workflow of the present invention;

[0028] Figure 2 This is a design diagram of the immersive virtual reality interactive platform built according to the present invention;

[0029] Figure 3 A graph showing the relationship between speed and time in conflicting experiments;

[0030] Figure 4 A graph showing the correlation between velocity and distance to the collision point in a collision experiment;

[0031] Figure 5 A graph showing the relationship between speed and time in a conflict-free experiment;

[0032] Figure 6 A graph showing the correlation between velocity and distance to the collision point in a collision-free experiment. Detailed Implementation

[0033] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0034] In one embodiment, a method for testing cycling risk perception based on an immersive virtual reality interactive platform is provided, such as... Figure 1 As shown, this includes building an immersive virtual reality interactive platform, creating virtual reality scenes, establishing a risk assessment model, and conducting risk assessment analysis:

[0035] S1. Building an immersive virtual reality interactive platform

[0036] Using virtual reality headsets, controllers, and trackers, cyclists are placed in a virtual reality environment to achieve a realistic cycling experience. Trackers are attached to the cyclist's ankles, and scripts obtain their coordinates, converting them into the necessary data to control the bicycle's speed. Controllers are attached to the bicycle handlebars to control left and right turns and braking.

[0037] S2. Establish a virtual reality scene

[0038] Based on actual cycling scenarios, a virtual cycling scene is constructed using 3D modeling software to simulate road conditions, traffic, and other factors. The static elements of the scene are the 3D model and truck parameters, while the dynamic elements are the bicycle parameters.

[0039] S3, Records cycling data

[0040] Virtual reality headsets use built-in cameras and other devices to record cyclists' behavior in virtual environments. Trackers and controllers also record cyclists' riding data within these virtual environments.

[0041] S4. Establish a risk assessment model

[0042] By utilizing dynamic data of cycling behavior in virtual reality, a risk assessment model is constructed to conduct risk assessments, study how it affects cyclists' behavior, analyze cyclists' perception of and coping abilities regarding cycling risks, and provide targeted cycling safety recommendations based on the analysis results.

[0043] Further: In step S1, an immersive virtual reality interaction platform was built, such as... Figure 2 As shown, the setup steps are as follows:

[0044] Step 1: Secure the bicycle to the stationary bike bench and install the resistance unit. This resistance unit simulates the effect of riding a bicycle on the ground.

[0045] Step 2: Set up the VR equipment, specifically as follows:

[0046] The handlebars are attached to the bicycle handlebars. The rider controls the bicycle to turn left by pressing the trigger button on the left handlebar and to turn right by pressing the trigger button on the right handlebar. The brake is applied by pressing the bicycle brake button and the pad button on the handlebars simultaneously.

[0047] The tracker is attached to the cyclist's ankle, and the coordinate position information of the tracker is obtained through a script, which is then converted into the required data to control the bicycle speed.

[0048] Step 3: Connect the VR device to the Unity software using the SteamVR tool.

[0049] Further: In step S2, the location is selected as an intersection with potential collisions. The experiment is conducted in two scenarios: one with vehicle conflict and one without.

[0050] Further, in step S3, a risk assessment model is constructed using dynamic data of cycling behavior in virtual reality to conduct a risk assessment. The cyclist's perception of and ability to cope with cycling risks are analyzed, and targeted cycling safety recommendations are provided based on the analysis results.

[0051] Four sets of experiments were conducted in both conflict-prone and conflict-free scenarios to demonstrate the feasibility of the invention. Some data relationships recorded in the conflict-prone experiments are shown below. Figure 3 , 4 As shown, the relationships between some data recorded in the conflict-free experiment are as follows: Figure 5 , 6 As shown.

[0052] It can be seen that, compared to situations without conflict, when a conflict occurs, the closer the cyclist is to the point of collision, the more likely they are to slow down or brake. This also reflects that the closer the cyclist is to the point of collision, the greater their perceived risk and the more aggressive their reaction. Therefore, it is recommended that cyclists maintain a safe distance, ride cautiously, and control their speed to reduce the risk of collision.

[0053] Further: In step S4, the formula for the potential risk variable is as follows:

[0054] θ real-risk =δ real-feel +γ dist ·x dist +γcar-present·x car-present +ε α

[0055] In the formula:

[0056] x dist Indicates the distance from the cyclist to the point of collision (in meters);

[0057] x car-present It is a dummy variable; if a car appears at the intersection at the current time, it takes the value 1; otherwise...

[0058] =0;

[0059] ε α It is an error term;

[0060] γ dist The impact of the cyclist's distance from the point of collision on risk perception;

[0061] γ car-present This is an additional change in risk perception if a car appears at the intersection;

[0062] δ real-feel It represents a more complex set of perceived risk factors that cyclists face in reality. This parameter requires multiple virtual experiments and comparison with real data for calibration.

[0063] The risk assessment model is as follows:

[0064]

[0065] The subscript 'i' can represent acceleration, deceleration, braking, constant speed, and waiting behavior.

[0066] δ i Represents the constant term for each action;

[0067] ε is an error term that follows a Gumbel distribution;

[0068] and The parameters represent the impact of the distance to the collision point on the utility of each action, for levels one, two, and three.

[0069] and The effects of the cyclist's speed on the utility of each action are categorized into three levels: Level 1, Level 2, and Level 3.

[0070] This indicates whether the vehicle's position at the intersection affects the utility of each action;

[0071] This indicates the impact of potential risks on different actions;

[0072] This indicates whether a collision will occur given the presence of a vehicle and the current speed and remaining distance. A value of 1 indicates a collision, and a value of 0 indicates no collision.

[0073] Indicates the remaining time until collision;

[0074] This indicates the effect of the remaining time before each action causes a collision.

[0075] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any transformations or substitutions that can be conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for testing cycling risk perception based on an immersive virtual reality interactive platform, characterized in that, Includes the following steps: Step 1: Install the bicycle and VR equipment to build an immersive virtual reality interactive platform; the VR equipment includes a virtual reality headset, controllers, and trackers; Step 1 specifically includes: Step 1.1: Secure the bicycle to the stationary riding platform, install resistance units, and simulate the effect of riding a bicycle on the ground; Step 1.2: Set up the VR equipment by attaching the controller to the bicycle handlebars. The rider controls the bicycle to turn left by pressing the trigger button on the left handlebar and to turn right by pressing the trigger button on the right handlebar. The rider brakes by pressing the bicycle brake button and the pad button on the controller at the same time. The tracker is attached to the cyclist's ankle, and the coordinate position information of the tracker is obtained through a script, which is then converted into the required data to control the bicycle speed; a virtual reality headset is worn on the cyclist's head. Step 1.3: Connect the VR device to the Unity software using the SteamVR tool; Step 2: Based on the immersive virtual reality interactive platform, construct a virtual cycling scene using 3D modeling software. In the virtual cycling scene, the static elements are the 3D model and truck parameters, and the dynamic elements are the bicycle parameters. Step 3: Collect cycling data from cyclists in a virtual cycling scenario; Step 4: Based on the cyclist's cycling data, static elements, and dynamic elements in the virtual cycling scenario, construct a risk assessment model to evaluate the cyclist's cycling behavior, analyze the cyclist's perception of and ability to cope with cycling risks, and provide targeted cycling safety recommendations based on the analysis results.

2. The cycling risk perception testing method based on an immersive virtual reality interactive platform according to claim 1, characterized in that, In step 2, the virtual cycling scenario is selected at an intersection with potential collisions. The experiment is conducted in two scenarios: one with vehicle conflict and one without.

3. The cycling risk perception testing method based on an immersive virtual reality interactive platform according to claim 1, characterized in that, In step 4, a risk assessment model is constructed, where the formulas for potential risk variables are as follows: ； In the formula: Indicates the distance (m) from the cyclist to the point of collision; It is a dummy variable; if a car appears at the intersection at the current time, it takes the value 1, otherwise it takes the value 0. It is an error term; The impact of the cyclist's distance from the point of collision on risk perception; This is an additional change in risk perception if a car appears at the intersection; It is a set of more complex perceived risk factors that cyclists face in reality. This parameter needs to be calibrated by conducting multiple virtual experiments and comparing it with real data. The risk assessment model is as follows: ； ； ； The subscript i represents acceleration, deceleration, braking, constant speed, and waiting behavior; Represents the constant term for each action; It is an error term that follows a Gumbel distribution; , ,and The parameters represent the impact of the distance to the collision point on the utility of each action, categorized as Level 1, Level 2, and Level 3. , and The effects of the cyclist's speed on the utility of each action are categorized into three levels: Level 1, Level 2, and Level 3. This indicates whether the vehicle's position at the intersection affects the utility of each action; This indicates the impact of potential risks on different actions; This indicates whether a collision will occur given the presence of a vehicle and the current speed and remaining distance. A value of 1 indicates a collision, and a value of 0 indicates no collision. Indicates the remaining time until collision; This indicates the effect of the remaining time before each action causes a collision.

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