Signal timing optimization based on minimizing vehicle and pedestrian delay by genetic algorithm

There are two objectives for this research. One is to develop an effective procedure to optimize intersection signal timing by minimizing total delay for both vehicles and pedestrians. The second objective is to establish guidance for pedestrian crossing phase selection (two-way or scramble) and the length of WALK phase when scramble crossing is used. An optimization procedure for signal plans in an isolated intersection is developed. The procedure yields up to four phases for vehicles with either the two-way or scramble pedestrian crossing phase. A simple Genetic Algorithm (GA) is used in finding suitable signal plans because of the existence of a very large solution space. The GA fitness function is the total users delay (or cost). Compared with Highway Capacity Software (HCS) GA function, the proposed procedure has the same accuracy and more capabilities. When there is no pedestrian at the intersection, with the same input, the total delay from HCS and the proposed GA procedure has no significant difference (<0.2%) before optimization. After optimization, the signal plans recommended by the proposed procedure can result in delay values that are slightly less than or at least as much as the delay values from the HCS GA optimized signal plans. However, when pedestrian delay is considered in signal timing, such a comparison could not be made because the HCS does not compute a delay for pedestrians, while the proposed GA procedure does. Contour diagrams and look-up tables are generated to guide the decision between two-way and scramble phases. The guidance considers different combinations of vehicular volume, pedestrian volume, relative value of time, initial queue, and geometric layout of the intersection. Not only pedestrian volumes and right-turn vehicle volumes need to be taken into account, but also through (and left-turn) vehicle volumes. Scramble crossing is beneficial when pedestrian and right-turn vehicle volumes in an approach are high but through vehicle volumes are relatively lower.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Civil Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2010

Author dc:creator

• Yang, Zengyi

Contributors dc:contributor

• Benekohal, Rahim F.

• signal timing optimization
• Genetic Algorithm (GA)
• scramble crossing
• pedestrian delay
• vehicle delay

Statement dc:rights

• Copyright 2010 Zengyi Yang

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/16870

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/16870