A low-information, adaptive routing strategy for mobile and in-vehicle guidance systems is introduced to reduce congestion in road traffic networks, tailored for mixed-autonomy systems. Its efficacy and efficiency are demonstrated analytically and numerically through the development of a novel game-theoretic framework, Evolutionary Stackelberg Routing (ESR). In ESR, boundedly rational individuals influence each other's strategies over time through route and guidance system choices. This thesis also discusses, using traffic simulators, how such a sustainable guidance system spreads through the population as soon as individuals perceive the technology's popularity or personal advantage, thereby reducing congestion.

A low-information, adaptive routing strategy for mobile and in-vehicle guidance systems is introduced to reduce congestion in road traffic networks, tailored for mixed-autonomy systems. Its efficacy and efficiency are demonstrated analytically and numerically through the development of a novel game-theoretic framework, Evolutionary Stackelberg Routing (ESR). In ESR, boundedly rational individuals influence each other's strategies over time through route and guidance system choices. This thesis also discusses, using traffic simulators, how such a sustainable guidance system spreads through the population as soon as individuals perceive the technology's popularity or personal advantage, thereby reducing congestion.

Routing in Mixed-Autonomy Road Transportation Systems: Evolutionary Game Theory Perspective

BERTOLINI, ANDREA
2026

Abstract

A low-information, adaptive routing strategy for mobile and in-vehicle guidance systems is introduced to reduce congestion in road traffic networks, tailored for mixed-autonomy systems. Its efficacy and efficiency are demonstrated analytically and numerically through the development of a novel game-theoretic framework, Evolutionary Stackelberg Routing (ESR). In ESR, boundedly rational individuals influence each other's strategies over time through route and guidance system choices. This thesis also discusses, using traffic simulators, how such a sustainable guidance system spreads through the population as soon as individuals perceive the technology's popularity or personal advantage, thereby reducing congestion.
16-set-2026
Inglese
A low-information, adaptive routing strategy for mobile and in-vehicle guidance systems is introduced to reduce congestion in road traffic networks, tailored for mixed-autonomy systems. Its efficacy and efficiency are demonstrated analytically and numerically through the development of a novel game-theoretic framework, Evolutionary Stackelberg Routing (ESR). In ESR, boundedly rational individuals influence each other's strategies over time through route and guidance system choices. This thesis also discusses, using traffic simulators, how such a sustainable guidance system spreads through the population as soon as individuals perceive the technology's popularity or personal advantage, thereby reducing congestion.
ITS; Smart Cities; Stackelberg; Routing; Evolutionary Games
PESENTI RAFFAELE
CASTELLI, LORENZO
Università degli Studi di Trieste
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/380709
Il codice NBN di questa tesi è URN:NBN:IT:UNITS-380709