Next-generation advanced driver-assistance systems (ADAS) and cooperative adaptive
cruise control (CACC) for advanced/autonomous driving are expected to increasingly use …

In this paper, we analyze mixed traffic environments consisting of fully autonomous vehicles,
vehicles capable of communication only, and manually driven vehicles to determine what …

The existing advanced driver assistance systems (ADAS) can only detect targets in certain
range while relying on on-board sensors, which cannot meet the requirements of collision …

Cooperation between vehicles and/or with static elements of the road infrastructure enables
a wide number of applications and services, such as traffic monitoring and prediction …

The real-time vehicle sensing at urban scale is essential to various urban services. To date,
most existing approaches rely on static infrastructures (eg, traffic cameras) or mobile …

The perception range of the automated vehicles is limited to the line-of-sight field of view of
their on-board sensors (eg, Cameras, Radars). The aim of Collaborative automated driving …

As the mainstream of future automotive industry, Intelligent and Connected Vehicles (ICVs)
have versatile connections between themselves and external devices, although able to …

Cooperative perception that integrates sensing capabilities from both infrastructure and
vehicle perception sensors can greatly benefit the transportation system with respect to …

A cooperative vehicle‐infrastructure system (CVIS) can provide perception information
beyond the visual range for autonomous vehicles via roadside directional sensors, such as …

Cooperative perception significantly enhances the perception performance of connected
autonomous vehicles. Instead of purely relying on local sensors with limited range, it …