In this paper we present a new approach to the threat assessment problem for semi-autonomous and fully autonomous vehicles, based on the estimation of the control freedom afforded to a vehicle. Given sensor information available about the surrounding environment, an algorithm is described for identifying fields of safe travel through which the vehicle can safely navigate. Within each candidate field, we then characterize the level of threat, to influence autonomous navigation or driver support inputs. To characterize threat, the fields of safe travel are associated with sets of feasible trajectories generated from a lattice sampled in the vehicle's input space. A planner then computes a metric associated with available control freedom from these sampled trajectories. This method potentially allows a semi-autonomous control system to honor safe driver inputs while ensuring safe and robust navigation properties. It could also serve as an input to an autonomous decision-making layer.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A margin-based approach to threat assessment for autonomous highway navigation


    Contributors:


    Publication date :

    2014-06-01


    Size :

    2933904 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    A MARGIN-BASED APPROACH TO THREAT ASSESSMENT FOR AUTONOMOUS HIGHWAY NAVIGATION

    Constantin, A. / Park, J. / Iagnemma, K. et al. | British Library Conference Proceedings | 2014


    A margin-based approach to vehicle threat assessment in a homotopy framework for semi-autonomous highway navigation

    Constantin, Alexandre, S.M. Massachusetts Institute of Technology | DSpace@MIT | 2014

    Free access

    A margin-based approach to vehicle threat assessment

    Constantin, Alexandre | Online Contents | 2014


    A margin-based approach to vehicle threat assessment

    Constantin,A. / Park,J. / Iagnemma,K. et al. | Automotive engineering | 2014


    An Image-Based Visual Threat Cue for Autonomous Navigation

    Kundur, S. / Raviv, D. / IEEE; Computer Society; Technical Committee for Pattern Analysis and Machine Intelligence | British Library Conference Proceedings | 1995