6533b872fe1ef96bd12d36fa

RESEARCH PRODUCT

Autonomous vehicle with communicative driving for pedestrian crossing: Trajectory optimization

Alexandre LombardAbderrafiaa KoukamAbdeljalil Abbas-turkiKang-hyun JoMeng Zhang

subject

050210 logistics & transportation0209 industrial biotechnologyComputer science05 social sciences02 engineering and technologyTrajectory optimizationPedestrian crossingPetri netOptimal controlVehicle dynamics020901 industrial engineering & automationHuman–computer interaction0502 economics and businessPath (graph theory)TrajectoryCollision avoidance system

description

Connected and autonomous vehicles (CAV) is a key technology for this century. One of the main challenges is to define a smart interaction behavior of CAV with the other road users. The challenge is mainly raised at conflicting points where path of CAV intersects with the other users. Recent studies show interaction with humans is a big challenge. It not only requires a collision avoidance system but also more communicative behaviors of the CAV. More precisely, pedestrian needs to understand the intention of the incoming CAV whether it will cross first or not according to its speed profile. One way to overcome this issue is to design optimal trajectory control of the CAV that matches with the pedestrian expectation. However, such a design faces the non-linearity of the space sharing constraint. This paper uses sequence modeling based on Petri Net in order to overcome the problem. It also uses Hamiltonian analysis to derive the optimal control. Numerical examples of the communicative behavior of CAV at pedestrian crossing show that the proposed approach provides CAV with a kind of automatic courtesy.

yearjournalcountryeditionlanguage
2020-09-202020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)
https://doi.org/10.1109/itsc45102.2020.9294325