Wireless Bluetooth Low Energy Button
Wireless Button mounted on handlebars
Post-ride review of button press event
Review and conformation of event
Review, confirmation and additional event detail
Bike Hazard Dashboard Map
Bike Hazard Dashboard List
Bike Hazard Prioritized Overview
As bicyclists, we're frustrated with the unnecessary level of risk riding on our city streets - whether for commuting, exercise, or pleasure. We bring this focused perspective to provide much needed improvements in this area, contributing to the city's overall Vision Zero goals.
What it does
Bike Hazard allows bicyclists, from their unique vantage point, to identify and capture road and vehicle hazards in a frictionless, distraction-free, and real-time manner. This data can then be used by the city to provide prioritized and timely road maintenance and enforcement efforts.
Bicyclists interact with Bike Hazard through a wireless, Bluetooth Low Energy button mounted on a the handlebars of a bicycle. This wireless button is paired to a corresponding mobile application. When a bicyclist encounters any situation they view as hazardous - ranging from potholes to distracted drivers - they simply press the handlebar mounted button to record the time and location of the event. Once their ride is complete, the bicyclist is prompted by the Bike Hazard app to supply supporting information for each event. This is nominally performed by selecting the category of each event, but the Bike Hazard app also allows for the entry of free-form text for additional detail or clarification.
The data collected from the Bike Hazard app is stored in the cloud and made available to city personnel through a browser-based dashboard. This dashboard provides the ability to search, filter, and visualize specific hazard types in designated areas and/or timeframes. City maintenance personnel can be tasked to address physical road hazards, while police can use reported negative vehicle interactions to understand hotspots where enforcement efforts can be prioritized and focused.
We envision fusing the Bike Hazard data with existing open data to assist in the process of prioritization and deduplication of issue reporting through other channels.
How we built it
The overall design intent is to specifically allow bicyclists to report issues they recognize as hazardous during their riding activity. We like the basic idea of the Get It Done app, but believe this concept must be refined further to specifically support the bicyclist use case.
Our primary requirement is the ability for the bicyclist to safely capture real-time hazard locations, without requiring interaction with a mobile application at or near the hazard itself. This requirement keeps the bicyclist safe and focused on the road, while at the same time allowing for more accurate and complete data capture - in terms of time, location and fewer missed opportunities. Missed opportunities are key, since we anecdotally believe any existing data which may be useful for solving bicyclist-safety issues under-represents the reality encountered by bicyclists on city streets.
Implementation of the solution uses off-the-shelf, well known capabilities. These include basic mobile application development, web development, integration, and supporting analytics. The team behind this concept have built many products in these areas and have the experience to create the necessary design, product, and engineering plans and carry them through final execution.
Impact to the community
With the risks of bicycling reduced, more people are more likely to leave their cars behind in favor of their bikes, helpful in achieving climate change and traffic congestion goals. With the reduction of cars on the road there will be a decrease in bicycling related injuries which will cause more bicyclists, fulfilling part of the Vision Zero objectives.
Challenges we ran into
Initially, our intent was to use existing open data as a the sole source of providing insight into bicyclist-focused Vision Zero safety concerns. However, after examination of the data available, it was apparent that existing data alone can not provide useful insight into the safety issues that specifically impact bicyclists.
As such, we pivoted to a model where we would provide a mechanism for collection for much of this missing data. With the Bike Hazard data filling this gap, it can then be fused with existing datasets to provide a more accurate and holistic view into Vision Zero solutions that specifically impact bicyclist safety.
Accomplishments that we're proud of
Identifying that existing, available data was insufficient to solve the problem. Creatively using off-the-shelf, simple, and low cost technology to elegantly support the safe collection of relevant and missing data.
By identifying an underserved data category, our intent is that the data collected through Bike Hazard would be made available as open data, further serving the community and those with future ideas for its positive exploitation.
What we learned
Large amounts of open data in itself does not always provide a solution. Sometimes, additional data must be captured and incorporated to provide the missing pieces that make existing datasets useful for specific end goals.
The introduction of a hardware device, despite its low cost, makes universal distribution prohibitive. To address this issue, our intent is to use a sampling approach, leveraging bicycle advocacy groups and other outreach mechanisms to identify and recruit frequent bicycles users in the city to employ Bike Hazard our on city streets. We believe there are a sufficient number of highly motivated bicycle commuters and enthusiasts who have a vested interest in our shared goals, and if presented with a system such as Bike Hazard, would be willing and eager to be active participants.
What's next for Bike Hazard
Obtain feedback and support for taking Bike Hazard from concept to pilot in order to validate our design, assumptions and delivered end utility.
Other items to explore
- Access to Strava Metro data to enhance bicyclist traffic pattern data
- Get It Done API access
- City IQ cyclist and road hazard identification through machine learning
- Incorporate collected data and analysis into city Open Data repository