相关论文: Low-Latency High-Level Data Sharing for Connected …
Cooperative driving at isolated intersections attracted great interest and had been well discussed in recent years. However, cooperative driving in multi-intersection road networks remains to be further investigated, because many algorithms…
When people pick routes to minimize their travel time, the total experienced delay, or social cost, may be significantly greater than if people followed routes assigned to them by a social planner. This effect is accentuated when human…
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…
Real-time traffic prediction from high-fidelity spatiotemporal traffic sensor datasets is an important problem for intelligent transportation systems and sustainability. However, it is challenging due to the complex topological dependencies…
This paper presents a distributed traffic state estimation framework in which infrastructure sensors and connected vehicles act as autonomous, cooperative sensing nodes. These nodes share local traffic estimates with nearby nodes using…
In the context of evolving smart cities and autonomous transportation systems, Vehicular Ad-hoc Networks (VANETs) and the Internet of Vehicles (IoV) are growing in significance. Vehicles are becoming more than just a means of…
The exploitation of vehicles as mobile sensors acts as a catalyst for novel crowdsensing-based applications such as intelligent traffic control and distributed weather forecast. However, the massive increases in Machine-type Communication…
Intelligent connected vehicles equipped with wireless sensors, intelligent control system, and communication devices are expected to commercially launch and emerge on road in short-term. These smart vehicles are able to partially/fully…
Connected Autonomous Vehicles (CAVs) are widely expected to improve traffic safety and efficiency by exploiting information from surrounding vehicles via V2V communication. A CAV typically adapts its speed based on information from the…
Balancing passenger demand and vehicle availability is crucial for ensuring the sustainability and effectiveness of urban transportation systems. To address this challenge, we propose a novel hierarchical strategy for the efficient…
This work addresses the problem of autonomous traffic management at an isolated intersection for connected and automated vehicles. We decompose the trajectory of each vehicle into two phases: the provisional phase and the coordinated phase.…
Expected to provide higher transportation efficiency and security, autonomous driving has attracted substantial attentions from both industry and academia. Meanwhile, the emergence of edge intelligence has further introduced significant…
As semi-automated vehicles (SAVs) become more common, ensuring effective human-vehicle interaction during control handovers remains a critical safety challenge. Existing studies often rely on single-session simulator experiments or…
Cooperative automated vehicles exchange information to assist each other in creating a more precise and extended view of their surroundings, with the aim of improving automated-driving decisions. This paper addresses the need for scalable…
Latent space models are frequently used for modeling single-layer networks and include many popular special cases, such as the stochastic block model and the random dot product graph. However, they are not well-developed for more complex…
Recent developments in the smart mobility domain have transformed automobiles into networked transportation agents helping realize new age, large-scale intelligent transportation systems (ITS). The motivation behind such networked…
In recent years, with the rapid development of sensing technology and the Internet of Things (IoT), sensors play increasingly important roles in traffic control, medical monitoring, industrial production and etc. They generated high volume…
This paper studies the need for individualizing vehicular communications in order to improve collision warning systems for an N-lane highway scenario. By relating the traffic-based and communications studies, we aim at reducing highway…
In this paper, we explore the use of vehicle-to-vehicle (V2V) communication to improve the perception and motion forecasting performance of self-driving vehicles. By intelligently aggregating the information received from multiple nearby…
Vehicular big data is anticipated to become the "new oil" of the automotive industry which fuels the development of novel crowdsensing-enabled services. However, the tremendous amount of transmitted vehicular sensor data represents a…