Difference between revisions of "Projects:2019s1-124 Development of a Tool for Naturalistic Measurement of Vehicle-Cyclist Passing Distances"
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Braden Phillips | Braden Phillips | ||
Jamie Mackenzie (CASR) | Jamie Mackenzie (CASR) | ||
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| + | [[File:Bike fitted.png|thumb]] | ||
== Motivation == | == Motivation == | ||
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== Sensor Choice == | == Sensor Choice == | ||
<br> | <br> | ||
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| + | [[File:Sys Diagram.png|thumb]] | ||
'''Existing Limitations:'''<br> Measurement Frequency and Size<br> | '''Existing Limitations:'''<br> Measurement Frequency and Size<br> | ||
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'''Available technologies and sensors:'''<br> | '''Available technologies and sensors:'''<br> | ||
Ultrasonic and LiDAR | Ultrasonic and LiDAR | ||
| − | + | [[File:Selected Sensors.png|thumb]] | |
| − | + | '''Conclusion: ''' | |
<br> | <br> | ||
| − | + | The data from the on-road trial and follow up experiments indicates that the current ultrasonic sensor choice, while suitable in most regards and providing exceptionally low power consumption, is handicapped by its low frequency which makes it unable to detect many overtake instances. Of the two infrared time-of-flight sensors evaluated, while both resolve the frequency limitation only the TFmini Plus maintains the required distance accuracy in all ambient lighting conditions. The TF mini Plus is thus a more suitable sensor for a bicycle mounted passing distance measurement device, allowing it to accurately detect more overtakes in a more discreet package. | |
| Line 52: | Line 56: | ||
* Analyse the video and accuracy of the sensors<br> | * Analyse the video and accuracy of the sensors<br> | ||
* Build and implement a detection algorithm<br> | * Build and implement a detection algorithm<br> | ||
| + | |||
'''Conclusion:'''<br> Testing revealed video recordings as costly and time consuming method, but allowed for more efficient sensor detection algorithms to be developed. | '''Conclusion:'''<br> Testing revealed video recordings as costly and time consuming method, but allowed for more efficient sensor detection algorithms to be developed. | ||
| + | |||
| + | |||
| + | == Device Design == | ||
| + | A waterproof 3D-printed housing was designed to contain the onboard electronics including the data logger module, GPS module and a custom Printed Circuit Board (PCB). | ||
| + | The device was designed with the following considerations:<br> | ||
| + | * Intuitive Useability | ||
| + | * Weather Conditions | ||
| + | * Size and Shape | ||
| + | * Attachment to Bicycle | ||
| + | * Data Retrieval | ||
| + | * Cost | ||
| + | * Manufacturability | ||
| + | * Battery Life | ||
| + | * Maximum of 100 Units Produced | ||
| + | The PCB was designed to manage the connection of the modules to:<br> | ||
| + | * Sensors | ||
| + | * Micro USB Charging Port | ||
| + | * Battery | ||
| + | * Pushbutton Switch | ||
| + | * Red/Green LED | ||
| + | <br> | ||
| + | '''Conclusion:''' <br>A device was successfully developed that met the requirements of the project. It is weatherproof and�easier to use. | ||
Latest revision as of 15:48, 30 October 2019
Members: Scott Adamson Robert Broadhead Max Telford
Supervisors: Braden Phillips Jamie Mackenzie (CASR)
Motivation
While cycling is a mode of transport to be encouraged, cyclists are far more likely to be killed or hospitalised from road accidents than other commuters [1]. Having accurate data on where, how often, and how close cars overtake cyclists is an important step towards improving the laws and infrastructure that keep cyclists safe.
Aim
This project is sponsored by the Centre for Automotive Safety Research (CASR) and seeks to improve and validate the capabilities of an existing bicycle mounted device for measuring vehicle-cyclist passing distances. The three areas of focus are the sensor choice, device design and verification.
Sensor Choice
Existing Limitations:
Measurement Frequency and Size
Sensor considerations:
Measurement Frequency
Resolution/Accuracy
Cost
Durability
Power Consumption
Size
Weight
Communication
Interference
Other Output Data
Available technologies and sensors:
Ultrasonic and LiDAR
Conclusion:
The data from the on-road trial and follow up experiments indicates that the current ultrasonic sensor choice, while suitable in most regards and providing exceptionally low power consumption, is handicapped by its low frequency which makes it unable to detect many overtake instances. Of the two infrared time-of-flight sensors evaluated, while both resolve the frequency limitation only the TFmini Plus maintains the required distance accuracy in all ambient lighting conditions. The TF mini Plus is thus a more suitable sensor for a bicycle mounted passing distance measurement device, allowing it to accurately detect more overtakes in a more discreet package.
Verification
Verifying the accuracy of the data collected adds value to existing and all future trial results.
The steps taken to verify the device are as follows:
- Mount a Raspberry Pi camera to the bicycle
- Sync the camera with the sensor data
- Analyse the video and accuracy of the sensors
- Build and implement a detection algorithm
Conclusion:
Testing revealed video recordings as costly and time consuming method, but allowed for more efficient sensor detection algorithms to be developed.
Device Design
A waterproof 3D-printed housing was designed to contain the onboard electronics including the data logger module, GPS module and a custom Printed Circuit Board (PCB).
The device was designed with the following considerations:
- Intuitive Useability
- Weather Conditions
- Size and Shape
- Attachment to Bicycle
- Data Retrieval
- Cost
- Manufacturability
- Battery Life
- Maximum of 100 Units Produced
The PCB was designed to manage the connection of the modules to:
- Sensors
- Micro USB Charging Port
- Battery
- Pushbutton Switch
- Red/Green LED
Conclusion:
A device was successfully developed that met the requirements of the project. It is weatherproof and�easier to use.
