6705 results for "drivers" across all locations
uberPOOL—A New Way to Ride in Boston
Today, we’re thrilled to introduce uberPOOL—the cheapest way to Uber in Boston. With uberPOOL, we’ll connect you with someone traveling the same way so that you can both share the ride and split the cost. uberPOOL is our most affordable Uber option yet with prices up to 70% cheaper than a Boston TAXI. Get the details on how uberPOOL works, so you can start POOL-ing (and saving money) today.
¡Nos volvimos locos! – Invita a tus amigos y recibe 2 viajes gratis.
Cada vez que compartas tu código promocional le estás otorgando a tu amigo 2 viajes gratis de hasta $10. Una vez el usuario realice su primer viaje tú recibirás igualmente 2 viajes gratis de hasta $10.
10 Restaurant Marketing Tips That Can Help Drive Results
Restaurant marketing is a crucial step to success. Here are 10 restaurant marketing tips that could help increase sales and your restaurant’s customer base.
Information for driving during the world’s highly-anticipated football tournament in Doha
Learn more about rideshare plans and earning opportunities during the upcoming tournament.
MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving
M. Teichmann, M. Weber, M. Zöllner, R. Cipolla, R. Urtasun
While most approaches to semantic reasoning have focused on improving performance, in this paper we argue that computational times are very important in order to enable real time applications such as autonomous driving. […] [PDF]
IEEE Intelligent Vehicles Symposium (IV), 2018
LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving
G. P. Meyer, A. Laddha, E. Kee, C. Vallespi-Gonzalez, C. Wellington
In this paper, we present LaserNet, a computationally efficient method for 3D object detection from LiDAR data for autonomous driving. The efficiency results from processing LiDAR data in the native range view of the sensor, where the input data is naturally compact. […]
[PDF]
Computer Vision and Pattern Recognition (CVPR), 2019
Joint Interaction and Trajectory Prediction for Autonomous Driving using Graph Neural Networks
D. Lee, Y. Gu, J. Hoang, M. Marchetti-Bowick
Using weakly intent label can potentially predict the interaction and the resulting trajectory better. We use a GNN to model the interaction. [PDF]
Conference on Neural Information Processing Systems (NeurIPS), 2019
Car dealerships driving better customer experiences with Uber Central
We’ve been thrilled to see how Uber Central has allowed one industry in particular to transform their service relationships, and that’s car dealership
The Most Instagram-Worthy Views of Philadelphia
Términos y Condiciones de la promoción para socios de flotilla por 6 mil pesos
Términos y condiciones de la promoción para socios de flotilla, en la que podrán obtener hasta 6 mil pesos.