Las Vegas
Case Study

Deploying V2X Solutions
in the City That Never Sleeps

Published October 6, 2020

Project background

Las Vegas is a city with intense tourism, and visitors typically wander around the downtown by foot, being unfamiliar with local transport environment, with their attention divided. The City puts great emphasis on making its roads safe for the most vulnerable road users, and was looking for a future-proof solution to lay the basis of intelligent transport and preparing for the autonomous era.

In late 2017, Las Vegas also launched the very first driverless shuttle on a public street in America. Members of the public can take free rides on a 12-seater Navya self-driving shuttle along a 0.6 mile loop that includes the city’s iconic Fremont Street. Making sure it has a smooth ride was a key priority.

Commsignia contribution

Commsignia’s roadside units (RSU) were installed along the Las Vegas Strip and other critical infrastructure points in the Las Vegas Innovation District such as traffic intersections, roundabouts and busy roads.

They act as a local hub for sensor data exchange as well as a service/application platform that can be used to enhance the safety of all road users and help optimize traffic management.
They act as a local hub for sensor data exchange as well as a service/application platform that can be used to enhance the safety of all road users and help optimize traffic management.

Working with the local partner, Southwest Traffic Systems, Commsignia supplied its next generation Smart City ITS-RS4 Roadside Units as part of the infrastructure to support the driverless shuttle at junctions and other critical points along the route.

The ITS-RS4 acts as a local hub for sensor data exchange as well as a service/application platform that can be used to enhance the safety of all road users and help optimize traffic management. The ITS-RS4 gathers information from the surrounding environment such as traffic cameras, traffic light controllers, sensors and V2X connected vehicles – cars, motor-cycles and even bicycles. A powerful Deep Neural Network / GPU accelerated Artificial Intelligence processor creates a real-time representation of the information to create a dynamic model of the environment.

Applications and services in the ITS-RS4 utilize the dynamic model to enhance road-safety generating real-time alerts to drivers, connected autonomous vehicles and pedestrians, whilst escalating events and aggregated data for analytics to Traffic Management Centers.

Outcome

The deployment is one of the largest smart city deployment in Northern America to date.The infrastructure has been operational for 2 years and counting, with no major hardware failure. The cooperation has been since expanded, from the initial 80 RSUs now the number exceeds 100 devices. The driverless shuttle carried over 30,000 passengers in its first 11 months of operation.

RELEVANT EXPERTISES