An approach to grouping traffic signals for coordination using clustering methods

Zhang, Lei; Lee, Minha; Chang, Hyoseuk; Carrión, Carlos

doi:10.1109/mtits.2017.8005620

Cited by 2 publications

(2 citation statements)

References 10 publications

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“…They found that the three techniques functioned similarly and could produce the same solutions in all scenarios. Clustering analysis, such as hierarchical distance-based clustering ( 10 ) and K -clustering ( 11 ), was applied to partition an arterial to improve operational performance. In addition, a lot of research centered on proposing mathematical models to partition an arterial into multiple subsystems to achieve enhanced arterial signal progression ( 12 – 14 ).…”

Section: Literature Reviewmentioning

confidence: 99%

OD-Based Partition Technique to Improve Arterial Signal Coordination Using Connected Vehicle Data

Tian

2022

Transportation Research Record: Journal of the Transportation R

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Maximizing two-way arterial bands often plays a critical role in signal coordination along urban arterials. With an increasing number of signals involved, the arterial bands tend to shrink to some extent resulting in inefficient arterial signal coordination, and not all vehicles fully take advantage of the arterial bands to travel through the entire corridor. In response to that, system partition is a technique for handling arterials with many signals. Rather than designing end-to-end signal coordination, efficient arterial signal coordination is highly reliant on traffic origin and destination (OD) patterns on the arterial, which have been difficult to obtain using conventional data collection methods. The emerging big data sources, such as connected vehicles, provide great potential to gather such invaluable OD information for improving arterial signal coordination. This research proposes an easy-to-implement OD-based partition technique to improve arterial signal coordination by utilizing vehicle trajectory data automatically collected from connected vehicles. The proposed signal timing technique was tested using an arterial with 17 signalized intersections in Orange County, California. The results demonstrated that the OD-based partition technique improved the arterial average travel speed by 2.7% and 12.1% for the eastbound and westbound directions, respectively. At the same time, the proposed technique shortened the arterial average travel time by 2.6% and 11.1% for the eastbound and westbound directions, respectively. The total travel time was shortened both for the main-street and side-street major traffic flows.

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Section: Literature Reviewmentioning

confidence: 99%

OD-Based Partition Technique to Improve Arterial Signal Coordination Using Connected Vehicle Data

Tian

2022

Transportation Research Record: Journal of the Transportation R

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“…However, they tested one network that includes a specific group of subnetworks with a simplified signal phase, thereby offering limited results. A grouping method was developed to decrease delay and number of stops while minimizing traffic operators' subjective decisions [34] and was applied to a oneway corridor network with 21 intersections in Montgomery County, Maryland. A principal component analysis (PCA) method was developed to dynamically group controllers into clusters, but only a few signalized intersections were considered within their tested traffic networks [35].…”

Section: Introductionmentioning

confidence: 99%

Centralized and Decentralized Signal Control with Short-Term Origin-Destination Demand for Network Traffic

Zhang

Qiu

Kim

2022

Journal of Advanced Transportation

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We develop and assess centralized and decentralized signal control systems with short-term origin-destination (OD) demands as inputs. Considering each intersection turning movement as a virtual link, we assign traffic demand to paths based on minimal instantaneous travel time. Then, the optimal control is formulated using a G/G/n/FIFO open queueing network model (QNM). We also solve the issue of optimal control using a three-step naïve method for the centralized system with the new inputs. Because the optimization of large-scale network traffic signals can involve sizeable numbers of decision variables and nonlinear constraints, making it a nondeterministic polynomial time (NP) complete problem, we further decompose the centralized system into a decentralized system where the network is divided into subnetworks. Each subnetwork has a dedicated agent that optimizes signals within it. Furthermore, traffic demand for the entire network is decomposed into demands for subnetworks via path decomposition index (PDI). The proposed control systems are applied to test scenarios constructed using different demand profiles in grid networks. We also investigate the impact of network decomposition strategy on signal control system performance. Results show that network decomposition with smaller subnetworks results in less computational time (CT) but increased average travel time (ATT) and total travel delay (TTD).

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An approach to grouping traffic signals for coordination using clustering methods

Cited by 2 publications

References 10 publications

OD-Based Partition Technique to Improve Arterial Signal Coordination Using Connected Vehicle Data

OD-Based Partition Technique to Improve Arterial Signal Coordination Using Connected Vehicle Data

Centralized and Decentralized Signal Control with Short-Term Origin-Destination Demand for Network Traffic

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