Open AccessEnhancement of safety and comfort of cyclists at intersections
Author(s) -
Lu Meng,
Blokpoel Robbin,
Joueiai Mahtab
Publication year - 2018
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2017.0250
Subject(s) - controller (irrigation) , adaptive control , stability (learning theory) , engineering , control (management) , intelligent transportation system , transport engineering , function (biology) , electronic stability control , simulation , computer science , control theory (sociology) , control engineering , automotive engineering , artificial intelligence , machine learning , evolutionary biology , agronomy , biology
Cyclist safety is increasingly becoming a societal problem in Europe, as shown by road safety statistics. Frequent stops for red traffic lights at intersections are experienced by cyclists as a major inconvenience. This study introduces a green wave concept for cyclists, with focus on the traffic management and control aspects under cooperative intelligent transport systems applications. It especially addresses increasing stability of the adaptive control system, to overcome the drawbacks of both actuated and traditional adaptive control (which are too unpredictable for a green wave speed advice). In addition, solutions for avoiding increased delays for other traffic are investigated, as generally result from a classic green wave approach (with only fixed‐time control) and traditional adaptive control. This study introduces an adaptive control algorithm for a real‐time model‐predictive controller and implements a plan‐deviation cost function to address stabilisation. Simulation results show that the developed method increases stability of the adaptive control system, limits extra delays for other traffic and yields a high success rate for the green wave concept.