Improving Traffic Efficiency With Lane Guidance Based on Desired Speeds

Drivers initiate a discretionary lane change when they perceive an anticipated improvement in their own driving condition from moving to another lane. However, such a lane change can slow down other vehicles on the target lane, and even worse initiate a disturbance. In this work, we argue that the b...

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Bibliographic Details
Published in:IEEE transactions on intelligent transportation systems 2024-03, Vol.25 (3), p.2222-2234
Main Authors: Mahajan, Niharika, Hegyi, Andreas, Hoogendoorn, Serge P., van Arem, Bart
Format: Article
Language:English
Subjects:
Composition
Control systems
cooperative lane-changing
Decisions
desired speeds
Driving conditions
Efficiency
Free flow
Guidance systems
Heterogeneity
Lane changing
Lane guidance
Merging
Optimization
Real-time systems
Roads
Traffic control
traffic efficiency
user preferences in traffic control
Vehicle dynamics
Vehicles
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Summary:Drivers initiate a discretionary lane change when they perceive an anticipated improvement in their own driving condition from moving to another lane. However, such a lane change can slow down other vehicles on the target lane, and even worse initiate a disturbance. In this work, we argue that the blocking effect triggered by individual lane changes results from the heterogeneity in the desired speeds of vehicles, and thus using desired speed information of vehicles when regulating lane-changing decisions can improve traffic efficiency. In doing so, our work also exemplifies the usefulness of incorporating user preferences into control decisions. The proposed lane guidance system uses an optimization-based approach to update the target range of desired speeds on each lane in real time, and accordingly recommends individual lane changes. The control system coordinates the lane-changing decisions at the link level, for which the road stretch is subdivided into multiple sections that are controlled independently. We evaluate the performance of the lane guidance system in micro-simulation, for different network demands and desired speed distributions. The results highlight that the proposed approach utilizing the desired speed preferences of drivers results in positive efficiency gains for most traffic compositions in free flow. Moreover, the highest gains are expected in medium to high demand, and when the traffic composition includes a higher proportion of vehicles desiring higher speeds. The gains also increase when the desired speeds of vehicles that want to drive fast and those that want to drive slower are more separated.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2023.3340881