The MIT – Cornell Collision and Why It Happened
ABSTRACT Mid-way through the 2007 DARPA Urban Challenge, MIT’s autonomous Land
Rover LR3 ‘Talos’ and Team Cornell’s autonomous Chevrolet Tahoe ‘Skynet’ collided
in a low-speed accident, one of the first well-documented collisions between
two full-size autonomous vehicles. This collaborative study between MIT and Cornell
examines the root causes of the collision, which are identified in both teams’
system designs. Systems-level descriptions of both autonomous vehicles are given,
and additional detail is provided on sub-systems and algorithms implicated in the
collision. A brief summary of robot–robot interactions during the race is presented,
followed by an in-depth analysis of both robots’ behaviors leading up to and during
the Skynet–Talos collision. Data logs from the vehicles are used to show the
gulf between autonomous and human-driven vehicle behavior at low speeds and
close proximities. Contributing factors are shown to be: (1) difficulties in sensor
data association leading to phantom obstacles and an inability to detect slow moving
vehicles, (2) failure to anticipate vehicle intent, and (3) an over emphasis on
lane constraints versus vehicle proximity in motion planning. Eye contact between
human road users is a crucial communications channel for slow-moving close encounters
between vehicles. Inter-vehicle communication may play a similar role for
autonomous vehicles; however, there are availability and denial-of-service issues to
- SourceAvailable from: Thierry Fraichard
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- "2 They demonstrate robotics systems traveling significant distances at high speed in complex and realistic environments. However such systems remains prone to accidents (see Fletcher et al. 2008). While moving (especially at high speed), AGVs (and other robotic systems as well) can be potentially dangerous should a collision occur; this is a critical issue if such systems are to transport or share space with human beings. "
ABSTRACT: This paper addresses the problem of navigating a mobile robot with a limited field-of-view in a unknown dynamic environment. In such a situation, absolute motion safety, i.e. such that no collision will ever take place whatever happens, is impossible to guarantee. It is therefore settled for a weaker level of motion safety dubbed passive motion safety: it guarantees that, if a collision takes place, the robot will be at rest. Passive motion safety is tackled using a variant of the Inevitable Collision State (ICS) concept called Braking ICS, i.e. states such that, whatever the future braking trajectory of the robot, a collision occurs before it is at rest. Passive motion safety is readily obtained by avoiding Braking ICS at all times. Building upon an existing Braking ICS-Checker, i.e. an algorithm that checks if a given state is a Braking ICS or not, this paper presents a reactive collision avoidance scheme called PASSAVOID. The main contribution of this paper is the formal proof of PASSAVOID's passive motion safety. Experiments in simulation demonstrates how PASSAVOID operates.Autonomous Robots 04/2012; 32(3):174-179. DOI:10.1109/ICRA.2012.6224932 · 1.75 Impact Factor
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- "Within this perspective, driver intention estimation (and more generally situation assessment) has been identied as a key problem for intelligent vehicles, and one of the three main remaining challenges . Indeed, trac at intersections is highly dynamic and involves complex interactions between vehicles. "
ABSTRACT: This work proposes a novel approach to risk assessment at road intersections. Unlike most approaches in the literature, it does not rely on trajectory prediction. Instead, dangerous situations are identified by comparing what drivers intend to do with what they are expected to do. What a driver intends to do is estimated from the motion of the vehicle, taking into account the layout of the intersection. What a driver is expected to do is derived from the current configuration of the vehicles and the traffic rules at the intersection. The proposed approach was validated in simulation and in field experiments using passenger vehicles and Vehicle-to-Vehicle communication. Different strategies are compared to actively avoid collisions if a dangerous situation is detected. The results show that the effectiveness of the strategies varies with the situation.
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- "They demonstrate robotics systems traveling significant distances at high speed in complex and realistic environments. However such systems remains prone to accidents (see ). While moving (especially at high speed), AGVs (and other robotic systems as well) can be potentially dangerous should a collision occur; this is a critical issue if such systems are to transport or share space with human beings. "
ABSTRACT: This paper addresses the problem of provably safe navigation for a mobile robot with a limited field-of-view placed in a unknown dynamic environment. In such a situation, absolute motion safety (in the sense that no collision will ever take place whatever happens in the environment) is impossible to guarantee in general. It is therefore settled for a weaker level of motion safety dubbed passive motion safety: it guarantees that, if a collision is inevitable, the robot will be at rest. The primary contribution of this paper is a relaxation of the Inevitable Collision State (ICS) concept called Braking ICS. A Braking ICS is a state for which, no matter what the future trajectory of the robot is, it is impossible to stop before a collision takes place. Braking ICS are designed with a passive motion safety perspective for robots with a limited field-of-view in unknown dynamic environments. Braking ICS are formally defined and a number of important properties are established. These properties are then used to design a Braking ICS checker, i.e. an algorithm that checks whether a given state is a Braking ICS or not. In a companion paper, it is shown how the Braking ICS checker can be integrated into a reactive navigation scheme whose passive motion safety is provably guaranteed.2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2011, San Francisco, CA, USA, September 25-30, 2011; 09/2011