StreetLogic Raises $2.1M for AI E-Bike Collision Warning System

Enhancing E-Bike Safety with Streetlogic's New Technology

Streetlogic is dedicated to improving the safety of e-bike commuters. The company recently announced a $2.1 million pre-seed funding round and the introduction of its primary product: a comprehensive surround-view camera system designed to anticipate potential collisions from the front, sides, and rear, thereby alerting riders and helping to prevent accidents.

Pre-Orders and Availability

Beginning Tuesday, prospective customers in the United States, Canada, and Europe can secure Streetlogic’s advanced driver assistance system (ADAS) for e-bikes with a $30 deposit. The anticipated retail price will range from $300 to $400, with initial mass-produced units slated for delivery by the close of 2022, as stated by Jonathan Denby, Streetlogic’s CEO and founder.

Residents of San Francisco, where Streetlogic is headquartered, will have the opportunity to participate in a limited, invitation-only beta program starting early next year, allowing for early system testing.

ADAS Systems for Micromobility: A Growing Trend

Streetlogic is not the pioneer in developing ADAS for micromobility solutions. Last year, Ride Vision, an Israeli startup, unveiled a comparable AI-driven system. This system analyzes surrounding traffic in real-time, providing alerts for potential forward collisions, blind-spot monitoring, and warnings regarding following too closely.

Similar to Streetlogic, Ride Vision’s technology also functions as a dashcam, recording rides and preserving safety incident data for later review.

Distinguishing Streetlogic’s Approach

Computer vision firms such as Luna and Drover AI have also created comparable technology for e-scooters, utilized by shared micromobility services like Voi and Spin. While the underlying technology is similar, the intended markets differ.

“Our focus is on providing riders with intelligent safety features, whereas others are employing vision systems to ensure scooter riders adhere to city regulations,” explained Denby to TechCrunch. “Their features include sidewalk detection and parking compliance, essential for scooter operators. Our priority is solely the rider’s safety, offering early warnings of potential collisions with vehicles.”

Key Differences in Functionality

Luna and Drover AI systems can interface with a scooter’s operating system and intervene, slowing or stopping the rider if they venture onto sidewalks or engage in inappropriate behavior. Streetlogic’s product is exclusively a collision warning system, but remains a valuable tool, particularly in urban environments.

Real-World Rider Experience

“It’s difficult to maintain awareness of your surroundings at all times – you simply can’t. When commuting, it’s often a time for reflection, and I find myself not actively thinking about safety. I’m focused on reaching work and managing my daily tasks,” shared Taylor, an early Streetlogic beta tester who regularly commutes by e-bike, in a testimonial featured on the company’s website.

The Increasing Need for Cyclist Safety

The number of preventable cyclist fatalities in the U.S. rose by 6% between 2010 and 2019, increasing from 793 to 1,089. Of these, 843 deaths resulted from collisions with motor vehicles. As e-bike sales continue to climb, automobiles remain a significant hazard to the widespread adoption of micromobility in cities, accounting for 78% of fatal cycling accidents.

Consumers considering e-bikes as alternatives to cars may prioritize models equipped with enhanced safety features, such as an ADAS system.

A Vision for the Future of Urban Transportation

“I envision a future where cities are populated with more e-bikes than cars,” Denby stated to TechCrunch. “While some cars will always be necessary, the majority of transportation could be handled by bicycles. Enhancing the dependability of e-bikes as a primary mode of transportation is crucial to realizing this vision.”

System Details and Functionality

Streetlogic’s system, mounted on both the front and rear of the bike, utilizes computer vision processing performed entirely on the device itself. It monitors the behavior and movements of surrounding vehicles, providing an early warning if the rider is on a potential collision course.

The processing and alerts operate on a closed-loop onboard system, eliminating the need for cloud connectivity and ensuring functionality even in areas with limited or no service.

POV of Streetlogic computer vision product that warns e-bike riders of potential car collisions. Image Credits: Streetlogic

Riders will initially receive an audio warning from the hardware, such as “car back” if a vehicle is approaching rapidly from behind. A corresponding visual alert on the rider’s smartphone will indicate the direction of the potential hazard, requiring only a brief glance, provided the phone is mounted to the handlebars.

Comparison with Competitor Systems

Drover AI and Luna systems can detect objects like pedestrians and lane markings, but do not currently provide active collision warnings for e-scooter riders, although their technology could potentially be adapted to include this feature.

Alex Nesic, CEO of Drover AI, indicated to TechCrunch that e-bike warning systems are suitable as a “next level” feature for the high-end market, but “are unlikely to be affordable enough for shared applications, which is our current focus.”

Early Testing and Future Development

While still in its early stages, Denby reports that the technology has performed “surprisingly well” during alpha testing. Currently, the system tracks only cars, as collisions or near-misses with automobiles represent the most common safety concerns for cyclists.

“However, the advantage of vision technology is its adaptability over time,” he explained. “It could potentially track cyclists, pedestrians, potholes, road cracks, and animals entering the street. These are all features we can integrate in the future. Even focusing solely on cars, we address the majority of incidents.”

Funding and Team Expansion

Streetlogic will leverage the newly acquired funding to gather more data for training its machine learning models and expanding its detection capabilities. The pre-seed round, backed by LDV Capital, Trucks Venture Capital, and angel investors including Luc Vincent, Lyft’s former EVP of autonomous driving, will be used to grow the team, according to the company. The startup currently employs six full-time staff members, having added two new team members recently, and aims to expand its workforce to fulfill pre-orders and enhance system maturity.

“We have assembled a highly skilled team with expertise from Apple and Uber in hardware, and from Cruise in software,” said Denby.

Denby himself brings experience from Uber, where he advised on computer vision systems for the company’s Jump scooters (later acquired by Lime), and he also led the team responsible for developing the Rylo 360-degree action camera.

Future Plans and Integrations

While Streetlogic is initially launching as a direct-to-consumer product to accelerate market entry, the company intends to explore integrations with bicycle manufacturers in the future.