
Intersection Signal Timing Optimisation for an Urban Street Network to Minimise Traffic Delays
Author(s) -
Manel Terraza,
Ji Zhang,
Zongzhi Li
Publication year - 2021
Publication title -
promet
Language(s) - English
Resource type - Journals
eISSN - 1848-4069
pISSN - 0353-5320
DOI - 10.7307/ptt.v33i4.3694
Subject(s) - intersection (aeronautics) , signal timing , pedestrian , transport engineering , weighting , street network , computer science , traffic congestion , pedestrian crossing , signal (programming language) , traffic signal , highway capacity manual , simulation , real time computing , engineering , level of service , medicine , radiology , programming language
The ever-increasing travel demand outpacing available transportation capacity especially in the U.S. urban areas has led to more severe traffic congestion and delays. This study proposes a methodology for intersection signal timing optimisation for an urban street network aimed to minimise intersection-related delays by dynamically adjusting green splits of signal timing plans designed for intersections in an urban street network in each hour of the day in response to varying traffic entering the intersections. Two options are considered in optimisation formulation, which are concerned with minimising vehicle delays per cycle, and minimising weighted vehicle and pedestrian delays per cycle calculated using the 2010 Highway Capacity Manual (HCM) method. The hourly vehicular traffic is derived by progressively executing a regional travel demand forecasting model that could handle interactions between signal timing plans and predicted vehicular traffic entering intersections, coupled with pedestrian crossing counts. A computational study is conducted for methodology application to the central business district (CBD) street network in Chicago, USA. Relative weights for calculating weighted vehicle and pedestrian delays, and intersection degrees of saturation are revealed to be significant factors affecting the effectiveness of network-wide signal timing optimisation. For the current study, delay reductions are maximised using a weighting split of 78/22 between vehicle and pedestrian delays.