相关论文: Interactive Car-Following: Matters but NOT Always

While intelligence of autonomous vehicles (AVs) has significantly advanced in recent years, accidents involving AVs suggest that these autonomous systems lack gracefulness in driving when interacting with human drivers. In the setting of a…

Connected and automated vehicles (CAVs) have attracted more and more attention recently. The fast actuation time allows them having the potential to promote the efficiency and safety of the whole transportation system. Due to technical…

Autonomous navigation in crowded, complex urban environments requires interacting with other agents on the road. A common solution to this problem is to use a prediction model to guess the likely future actions of other agents. While this…

The car-following behavior of individual drivers in real city traffic is studied on the basis of (publicly available) trajectory datasets recorded by a vehicle equipped with an radar sensor. By means of a nonlinear optimization procedure…

Rapid advancements in driver-assistance technology will lead to the integration of fully autonomous vehicles on our roads that will interact with other road users. To address the problem that driverless vehicles make interaction through eye…

Understanding how road users resolve space-sharing conflicts is important both for traffic safety and the safe deployment of autonomous vehicles. While existing models have captured specific aspects of such interactions (e.g., explicit…

Interactive decision-making is essential in applications such as autonomous driving, where the agent must infer the behavior of nearby human drivers while planning in real-time. Traditional predict-then-act frameworks are often insufficient…

The way we communicate with autonomous cars will fundamentally change as soon as manual input is no longer required as back-up for the autonomous system. Maneuver-based driving is a potential way to allow still the user to intervene with…

Motivated by the need to develop simulation tools for verification and validation of autonomous driving systems operating in traffic consisting of both autonomous and human-driven vehicles, we propose a framework for modeling vehicle…

Affective technology offers exciting opportunities to improve road safety by catering to human emotions. Modern car interiors enable the contactless detection of user states, paving the way for a systematic promotion of safe driver behavior…

Many intelligent systems currently interact with others using at least one of fixed communication inputs or preset responses, resulting in rigid interaction experiences and extensive efforts developing a variety of scenarios for the system.…

Car-following (CF) modeling, an essential component in simulating human CF behaviors, has attracted increasing research interest in the past decades. This paper pushes the state of the art by proposing a novel generative hybrid CF model,…

Understanding adaptive human driving behavior, in particular how drivers manage uncertainty, is of key importance for developing simulated human driver models that can be used in the evaluation and development of autonomous vehicles.…

When pedestrians encounter vehicles, they typically stop and wait for a signal from the driver to either cross or wait. What happens when the car is autonomous and there isn't a human driver to signal them? This paper seeks to address this…

Predicting future motions of road participants is an important task for driving autonomously in urban scenes. Existing models excel at predicting marginal trajectories for single agents, yet it remains an open question to jointly predict…

Safe planning of an autonomous agent in interactive environments -- such as the control of a self-driving vehicle among pedestrians -- poses a major challenge as the behavior of the environment is unknown and reactive to the behavior of the…

Understanding driver interactions is critical to designing autonomous vehicles to interoperate safely with human-driven cars. We consider the impact of these interactions on the policies drivers employ when navigating unsigned intersections…

This paper analyzes the car following behavioral stochasticity based on two sets of field experimental trajectory data by measuring the wave travel time series of vehicle n. The analysis shows that (i) No matter the speed of leading vehicle…

This study investigates the role of haptic feedback in a car-following scenario, where information about the motion of the front vehicle is provided through a virtual elastic connection with it. Using a robotic interface in a simulated…

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…