Traffic signal optimisation in disrupted networks, to improve resilience and sustainability. (January 2021)

• Record Type: Journal Article
• Authors: Abudayyeh, Dana; Nicholson, Alan; Ngoduy, Dong
• Is Part Of: Travel behaviour and society. Volume 22(2021)
• Page Start: 117
• Page End: 128
• Publication Date: 2021-01
• Subjects: Disrupted networks -- Traffic signal optimisation -- Cross-Entropy method -- Semi-dynamic assignment -- Resilience -- Carbon dioxide emissions; Transportation -- Periodicals; Population geography -- Periodicals; 303.48305
• DOI: 10.1016/j.tbs.2020.08.005
• Languages: English
• ISSNs: 2214-367X

Abstract

Highlights: Optimising signal settings to assist drivers re-routing in disrupted networks. Applying the Cross-Entropy and semi-dynamic approach, to optimise signals. Including minimising travel time or minimising CO2 emissions in disrupted networks. Testing 4 minutes up to full hour degradations and 25% up to 100% reductions. Signal optimisation reduces travel time by almost 6% and CO2 emissions by almost 8%. Abstract: Transport has a critical role in economic development; an efficient transport system can enable economic growth and enhance social well-being. Road networks, as a part of a transport system, are among the most important lifeline systems. Urban road networks experience serious congestion because of infrequent major disruptions. Due to these disruptions the traffic system performance is reduced and the travel time and emissions in a road network are increased. This paper describes a method for optimising traffic signal settings (i.e. green times and offsets) to assist drivers to avoid partial or complete blockages, to minimise the travel time or carbon dioxide emissions in the case of disruptions in road networks. This method involves applying the Cross-Entropy optimisation method, along with a semi-dynamic approach, to optimise traffic signal control in disrupted road networks. This includes investigating two objective functions: minimising the travel time or minimising carbon dioxide emissions. To achieve this, short-term blockages are tested with different durations (a degradation for 4 minutes up to full hour) and level of capacity reductions (i.e. 0%, 25%, 50%, 75%, and 100%). The results for minimising the travel time, in the Cambridge (UK) network, show that applying signal optimisation reduces the travel time by almost 6% and carbon dioxide emissions by almost 8% for a complete capacity reduction at the most congested node, compared to not optimising the signal settings.