RT Journal Article
T1 Context-dependent reconfiguration of autonomous vehicles in mixed traffic
A1 Horcas-Aguilera, José Miguel
A1 Monteil, Julien
A1 Bouroche, Mélanie
A1 Pinto-Alarcón, Mónica
A1 Fuentes-Fernández, Lidia
A1 Clarke, Siobhán
K1 Ingeniería del software
K1 Tráfico - Regulación
K1 Vehículos autodirigidos
AB Human drivers naturally adapt their behaviour depending on the traffic conditions, such as thecurrent weather and road type. Autonomous vehicles need to do the same, in a way that is bothsafe and efficient in traffic composed of both conventional and autonomous vehicles. In this paper, wedemonstrate the applicability of a reconfigurable vehicle controller agent for autonomous vehiclesthat adapts the parameters of a used car-following model at runtime, so as to maintain a highdegree of traffic quality (efficiency and safety) under different weather conditions. We follow aDynamic Software Product Line (DSPL) approach to model the variability of the car-followingmodel parameters, context changes and traffic quality, and generate specific configurations for eachparticular context. Under realistic conditions, autonomous vehicles have only a very local knowledgeof other vehicles’ variables. We investigate a distributed model predictive controller agent forautonomous vehicles to estimate their behavioural parameters at runtime, based on their availableknowledge of the system. We show that autonomous vehicles with the proposed reconfigurablecontroller agent lead to behaviour similar to that achieved by human drivers, depending on thecontext
PB Wiley
YR 2018
FD 2018-04
LK https://hdl.handle.net/10630/32685
UL https://hdl.handle.net/10630/32685
LA eng
NO Política de acceso abierto tomada de: https://v2.sherpa.ac.uk/id/publication/7508
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026