How Uber Beacon Helps Improve Safety for Riders and Drivers

How Uber Beacon Helps Improve Safety for Riders and Drivers

  • December 22, 2018
Table of Contents

How Uber Beacon Helps Improve Safety for Riders and Drivers

Globally, there are approximately 1.3 million collision-related fatalities on the road every year. Crash fatalities are still the leading cause of death for people between 15-29 years old, impacting families, communities, and cities. Governments around the world are working to reduce the risks, committing more resources towards improving road safety.

At Uber, we want to do our part by committing the power of our technology to help make travel safer for everyone. We have multiple teams at Uber working on road safety, reflecting a variety of disciplines, and we’re approaching this challenge from a number of angles. On the platform itself, we have many features to help improve road safety, such as driving hour limits to help curb drowsy driving, a partnership with the GHSA to raise awareness about seatbelts, and a 911 assistance feature to make it easier for riders and drivers to receive emergency assistance.

Uber Beacon, launched in 2016, is one of our more visible safety products. This device mounts on the driver’s windshield and uses color-pairing technology to help drivers and riders connect more quickly during pick-ups. Drivers have the option to add a Beacon to their vehicle and can unpair the device at anytime.

Beyond its visual signaling, the Beacon device also contains an accelerometer and gyroscope, similar to the sensors that currently exist in most smartphones. This sensor technology makes Beacon a perfect complement to our recently announced automatic crash detection feature, a solution that harnesses the power of GPS and other sensors in the smartphone to detect possible crashes. After a possible crash is detected, Uber initiates a Ride Check by reaching out to both the rider and the driver to offer quick assistance.

Source: uber.com

Share :
comments powered by Disqus

Related Posts

Cape Technical Deep Dive

Cape Technical Deep Dive

In this post, we’ll take a deep dive into the design of the Cape framework. First, we’ll discuss Cape’s architecture. Then we’ll look at the core scheduling component of the system.

Read More
Large Scale NoSQL Database Migration Under Fire

Large Scale NoSQL Database Migration Under Fire

The following post describes how we migrated a large NoSql database from one vendor to another in production without any downtime or data loss. The following methodology has worked for us and has been proven to be safe and simple. I am sure that there are several techniques for migrating NoSql databases, but here are some guidelines for doing so with minimal risk, while maintaining the ability to rollback at almost any point in the process.

Read More
Sessionizing Uber Trips in Real Time

Sessionizing Uber Trips in Real Time

Uber’s many data flows required modeling the data associated with a specific task, such as a rider trip, into a state machine. The state machine lets engineers focus on just the events needed to successfully accomplish a trip. In one sense, Uber’s challenge of efficiently matching riders and drivers in the real world comes down to the question of how to collect, store, and logically arrange data.

Read More