Towards an enhanced driver situation awareness system

This paper outlines our current research agenda to achieve enhanced driver situation awareness. A novel approach that incorporates information gathered from sensors mounted on the neighboring vehicles, in the road infrastructure as well as onboard sensory information is proposed. A solution to the fundamental issue of registering data into a common reference frame when the relative locations of the sensors themselves are changing is outlined. A description of the vehicle test bed, experimental results from information gathered from various onboard sensors, and preliminary results from the sensor registration algorithm are presented. ©2007 IEEE

Realistic following behaviors for crowd simulation

International audienceWhile walking through a crowd, a pedestrian experiences a large number of interactions with his neighbors. The nature of these interactions is varied, and it has been observed that macroscopic phenomena emerge from the combination of these local interactions. Crowd models have hitherto considered collision avoidance as the unique type of interactions between individuals, few have considered walking in groups. By contrast, our paper focuses on interactions due to the following behaviors of pedestrians. Following is frequently observed when people walk in corridors or when they queue. Typical macroscopic stop-and-go waves emerge under such traffic conditions. Our contributions are, first, an experimental study on following behaviors, second, a numerical model for simulating such interactions, and third, its calibration, evaluation and applications. Through an experimental approach, we elaborate and calibrate a model from microscopic analysis of real kinematics data collected during experiments. We carefully evaluate our model both at the microscopic and the macroscopic levels. We also demonstrate our approach on applications where following interactions are prominent

A Synthetic-Vision Based Steering Approach for Crowd Simulation

International audienceIn the everyday exercise of controlling their locomotion, humans rely on their optic flow of the perceived environment to achieve collision-free navigation. In crowds, in spite of the complexity of the environment made of numerous obstacles, humans demonstrate remarkable capacities in avoiding collisions. Cognitive science work on human locomotion states that relatively succinct information is extracted from the optic flow to achieve safe locomotion. In this paper, we explore a novel vision-based approach of collision avoidance between walkers that fits the requirements of interactive crowd simulation. By simulating humans based on cognitive science results, we detect future collisions as well as the level of danger from visual stimuli. The motor-response is twofold: a reorientation strategy prevents future collision, whereas a deceleration strategy prevents imminent collisions. Several examples of our simulation results show that the emergence of self-organized patterns of walkers is reinforced using our approach. The emergent phenomena are visually appealing. More importantly, they improve the overall efficiency of the walkers' traffic and avoid improbable locking situations

Empirical evaluation of an autonomous vehicle in an Urban environment

Operation in urban environments creates unique challenges for research in autonomous ground vehicles. Due to the presence of tall trees and buildings in close proximity to traversable areas, GPS outage is likely to be frequent and physical hazards pose real threats to autonomous systems. In this paper, we describe a novel autonomous platform developed by the Sydney-Berkeley Driving Team for entry into the 2007 DARPA Urban Challenge competition. We report empirical results analyzing the performance of the vehicle while navigating a 560-meter test loop multiple times in an actual urban setting with severe GPS outage. We show that our system is robust against failure of global position estimates and can reliably traverse standard two-lane road networks using vision for localization. Copyright © 2007 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved

The orchestration of behaviours using resources and priority levels

Reproducing daily behaviours requires the ability to schedule behaviours depending on resources (body parts for example) and priority (intentions or physiological parameters) constraints. A simple way is to say that behaviours which are using the same resources are mutually exclusive. This approach is not sufficient to achieve realism purpose, as in real life, humans are able to combine them in a much microscopic way. All day long, humans mix different behaviours, as for example reading a newspaper while drinking a coffee and smoking a cigarette. If all behaviours using common resources were mutually exclusive, an agent could not reproduce this example, except if a specific behaviour is created. This solution becomes rapidly too complex and has motivated the work presented in this paper. It consists in an extension of HPTS, our behavioural model, by the introduction of resources and priority levels. In the contrary of some previous approaches, it is not necessary to specify exhaustively all behaviours that are mutually exclusive; this is done implicitely by attaching resources to nodes and a priority function to each state machine, and by using a scheduler

Empirical Evaluation Of An Autonomous Vehicle In An Urban Environment

Operation in urban environments creates unique challenges for research in autonomous ground vehicles. Due to the presence of tall trees and buildings in close proximity to traversable areas, GPS outage is likely to be frequent and physical hazards pose

GHOST: a GHOst STory-writer

Often, small independent studios developing video games are forced to ask game or level designers to write stories for their products. Unfortunately, game writing requires a different set of skills than game design. Moreover, there is a shortage of interactive tools devoted to help non-writers to (learn how to) create compelling storylines for interactive media like video games. Our goal has been to design, implement and test a tool embedded into a game engine to help non-writers to create stories (for video games). Our solution, designed with the help of domain-experts, does not generate contents, but interactively helps the user to produce a solid narrative structure for a story, to avoid falling into banality or creating boring, repetitive tales