Bottleneck Congestion Management in Commuting Systems
Summary
Bottleneck congestion occurs when capacity‐constrained sections of a transport network restrict traffic flow, giving rise to queues, increased travel times and variability in commuter schedules. Managing such congestion is central to urban mobility, economic productivity and environmental sustainability. Research spans analytical modelling of commuter departure decisions, control-theoretic approaches to real-time traffic regulation and market-based instruments such as dynamic tolling and tradable credits. Advances in sensing technology and data analytics have enabled adaptive control strategies that respond to fluctuating demand, while the advent of autonomous and electric vehicles introduces new dimensions for demand management via in-vehicle activities and incentive schemes. Interdisciplinary efforts draw on traffic flow theory, microeconomic pricing, optimisation and fuzzy logic to design policies that align individual choices with system-wide objectives, thereby enhancing throughput, reducing delays and improving social welfare across global commuting corridors.
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Bottleneck Congestion Management in Commuting Systems publication trend
The graph below shows the total number of articles in bottleneck congestion management in commuting systems across all publications each year (not limited to Nature Index journals).
Technical terms
Bottleneck: A section of roadway or network link whose maximum flow rate is lower than adjacent segments, causing upstream queues and delays.
Congestion pricing: A demand-management mechanism that varies tolls or fees in real time to internalise the external costs of delay and reduce peak-period traffic volumes.
Departure time choice equilibrium: A stable state in which commuters select departure times such that no individual can lower their personal travel cost by unilaterally changing time.
Adaptive fuzzy control: A control methodology employing fuzzy-logic rules and adaptive weighting to adjust system inputs under uncertain or imprecise conditions.
Activity-based model: An analytical framework that incorporates travellers’ non-driving in-vehicle activities into their scheduling and routing decisions, affecting overall traffic patterns.
References
- Enhancing transportation network intelligence through visual scene feature clustering analysis with 3D sensors and adaptive fuzzy control. PeerJ Computer Science (2024).
- Autonomous cars and activity-based bottleneck model: How do in-vehicle activities determine aggregate travel patterns?. Transportation Research Part C Emerging Technologies (2022).
- Incentive-based electric vehicle charging for managing bottleneck congestion. European Journal of Control (2022).
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