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Overview 1
DALI Concepts and Operation 2
DALI Simulation 3
DALI Deployment 4
Related Publications 5
Presentation 6
Demos 7
Awards & Press Coverage 8

The pur­pose of the DALI project is to address the fol­low­ing problem:

Giv­en an exist­ing cen­tral­ized traf­fic man­age­ment infra­struc­ture, how can we turn it into a smart dis­trib­uted infra­struc­ture with­out the need for expen­sive changes or upgrades?

The DALI solu­tion calls for enhanc­ing exist­ing traf­fic infra­struc­tures by:

  • Plug­ging-in smart soft­ware agents into exist­ing inter­sec­tion controllers
  • Mak­ing use of Agent-to-Agent communications
  • Imple­ment­ing a dis­trib­uted, adap­tive, coop­er­a­tive strategy

Cen­tral­ized Traf­fic Man­age­ment System


DALI (Dis­trib­uted, Agent-based traf­fic LIghts), is a smart, col­lab­o­ra­tive traf­fic sig­nal tim­ing sys­tem. With DALI, inter­sec­tion con­troller agents com­mu­ni­cate with each oth­er through direct links and do not have a super­vis­ing unit to over­see coordination.

DALI’s Agent

A DALI Agent archi­tec­ture is giv­en below. It con­sists of four modules:

The inter­ac­tion mod­ule han­dles the agent’s inter­ac­tion with exter­nal enti­ties, sep­a­rat­ing envi­ron­ment inter­ac­tion from agent inter­ac­tion. The Envi­ron­ment Per­cep­tion Mod­ule process­es traf­fic sen­sor infor­ma­tion. The Agent Com­mu­ni­ca­tion Mod­ule imple­ments agent-to-agent communication. 

DALI’s Agent 

The knowl­edge mod­ule is par­ti­tioned into Exter­nal Knowl­edge Mod­ule (EKM) and Inter­nal Knowl­edge Mod­ule (IKM). The EKM serves as the por­tion of the agent’s mem­o­ry that is ded­i­cat­ed to main­tain­ing knowl­edge about traf­fic data, and adja­cent agents. The IKM serves as the por­tion of the agent’s mem­o­ry that is ded­i­cat­ed to stor­ing self-knowl­edge, includ­ing the agen­t’s cur­rent state, tim­ing con­straints, and behav­ioral limitations. 

The task mod­ule man­ages the atom­ic tasks that the agent can perform. 

The plan­ning and con­trol mod­ule serves as the brain of the agent. It uses infor­ma­tion pro­vid­ed by the oth­er mod­ules to plan, ini­ti­ate tasks, make deci­sions, and achieve goals. 

DALI’s Operation

By default, agents exe­cute a tim­ing strat­e­gy that improves traf­fic flow. At the same time, they observe and ana­lyze their respec­tive inter­sec­tions. If at any giv­en time, an agent deter­mines that its inter­sec­tion is con­gest­ed, it delib­er­ates and defines a new tim­ing plan. It also deter­mines which direct inter­sec­tions may be affect­ed by the new tim­ing plan and com­mu­ni­cates with the con­cerned inter­sec­tion agents. They, in turn, com­mu­ni­cate with those agents that may be affect­ed, and the process con­tin­ues until all affect­ed inter­sec­tions are noti­fied. The agents then nego­ti­ate and col­lab­o­rate with one anoth­er to ensure that the traf­fic flow will be opti­mized through­out the intersections.

Simulation of the City of Richardson

DALI was val­i­dat­ed by traf­fic engi­neers as well as through exten­sive sim­u­la­tion of var­i­ous traf­fic net­work mod­els includ­ing the City of Richardson’s traf­fic net­work. A mod­el of the City’s road net­work includ­ing 1365 road seg­ments, 128 sig­nal­ized inter­sec­tions and 965 non-sig­nal­ized inter­sec­tions was cre­at­ed in MATISSE.

2D visu­al­iza­tion of the City of Richardson’s Traf­fic Network. 

Sim­u­la­tion of DALI using real world data

DALI: Hybrid Simulation

In addi­tion to mod­el-based sim­u­la­tions, hybrid sim­u­la­tions (i.e., inte­gra­tion of con­trollers in the field with the sim­u­la­tor) were run to ver­i­fy com­pli­ance with the strict traf­fic regulations.

Hybrid Simulation

DALI was deployed in the City of Richardson’s Water­view Park­way cor­ri­dor at three major inter­sec­tions. The data col­lect­ed over a peri­od of three weeks shows that on aver­age, DALI reduced delay by 40.12%. (43.56 per­cent dur­ing week­day peak hours).

DALI agents exe­cut­ing in the lab

Agent inter­face (right hand side) dur­ing execution. 

Sce­nario illus­trat­ing agent exe­cu­tion on Frank­ford Rd and Water­view Pkwy.

Com­par­i­sion of con­ven­tion­al sys­tem and DALI exe­cu­tion at Syn­er­gy Dr and Water­view Pkwy.

  • Behnam Tora­bi, Rym Z. Wenkstern, and Robert Say­lor. A Col­lab­o­ra­tive Agent-Based Traf­fic Sig­nal Sys­tem For High­ly Dynam­ic Traf­fic Con­di­tions. Jour­nal of Autonomous Agents and Mul­ti-Agent Sys­tems (JAAMAS), to appear, 2019.
  • Behnam Tora­bi, Rym Z. Wenkstern, and Robert Say­lor. A Self-Adap­tive Col­lab­o­ra­tive Mul­ti-Agent based Traf­fic Sig­nal Tim­ing Sys­tem. In Pro­ceed­ings of the 4th IEEE Inter­na­tion­al Smart Cities Con­fer­ence, ISC2 2018, Kansas City, Mis­souri, USA, Sep­tem­ber 2018. 
  • Behnam Tora­bi, Rym Z. Wenkstern, and Robert Say­lor. A Col­lab­o­ra­tive Agent-Based Traf­fic Sig­nal Sys­tem For High­ly Dynam­ic Traf­fic Con­di­tions. In Pro­ceed­ings of the 21st IEEE Inter­na­tion­al Con­fer­ence on Intel­li­gent Trans­porta­tion Sys­tems, IEEE ITSC 2018, Maui, Hawaii, USA, Novem­ber 2018. 
  • Behnam Tora­bi, Rym Z. Wenkstern, and Robert Say­lor. A Mul­ti-Hop Agent-Based Traf­fic Sig­nal Tim­ing Sys­tem for the City of Richard­son. In Pro­ceed­ings of the 16th Inter­na­tion­al Con­fer­ence on Autonomous Agent and Mul­ti­a­gent Sys­tems, AAMAS 2018, page 2094–2096, Stock­holm, Swe­den, July 2018. 
  • Behnam Tora­bi, Rym Z. Wenkstern, and Robert Say­lor. Agent-based decen­tral­ized traf­fic sig­nal tim­ing. In Pro­ceed­ings of the 21st Inter­na­tion­al Sym­po­sium on Dis­trib­uted Sim­u­la­tion and Real Time Appli­ca­tions, DS-RT 17, page 123–126, Rome, Italy, Octo­ber 2017.
  • Moham­mad Al-Zinati and Rym Wenkstern. Sim­u­la­tion of traf­fic net­work re-orga­ni­za­tion oper­a­tions. In Pro­ceed­ings of the 20th IEEE/ACM Inter­na­tion­al Sym­po­sium on Dis­trib­uted Sim­u­la­tion and Real Time Appli­ca­tions, DS-RT 16, pages 178–186, Sep­tem­ber 2016. 
  • Moham­mad Al-Zinati and Rym Wenkstern. Matisse 2.0: a large-scale mul­ti-agent sim­u­la­tion sys­tem for agent-based its. In Pro­ceed­ings of the 2015 ieee/wiciacm inter­na­tion­al con­fer­ence on intel­li­gent agent tech­nol­o­gy, lAT’ 15, pages 328–335, Decem­ber 2015.
  • Moham­mad Al-Zinati and Rym Wenkstern. A self-orga­niz­ing vir­tu­al envi­ron­ment for agent-based sim­u­la­tions. In Pro­ceed­ings of the 2015 inter­na­tion­al con­fer­ence on autonomous agents and mul­ti­a­gent sys­tems, AAMAS ’15, pages 1031–1039, May 2015.

More pub­li­ca­tions avail­able here 

Deploy­ment of a Mul­ti-Agent Traf­fic Sig­nal Tim­ing Sys­tem (DALI) — AAMAS 2020

Deploy­ment of DALI at inter­sec­tion of Syn­er­gy Dr and Water­view Pkwy 

Deploy­ment of DALI at inter­sec­tion of Frank­ford Rd and Water­view Pkwy

Before and After Deploy­ment Com­par­i­sion at inter­sec­tion of Syn­er­gy Dr and Water­view Pkwy

DALI Agents Run­ning in the Lab

Eval­u­a­tion of DALI through simulation

2019 Smart 50 Award, Mobil­i­ty Cat­e­go­ry. The award rec­og­nizes the 50 most influ­en­tial smart-city projects in the world, Smart Cities Con­nect Con­fer­ence, Den­ver, CO, April 2019.

Final­ist, Tech Titan Awards, Inno­va­tors Cat­e­go­ry. This award rec­og­nizes the elite in North Texas tech­nol­o­gy – indi­vid­u­als cur­rent­ly trans­form­ing the high-tech indus­try, Dal­las, TX, August 2019. 

Home­town Tech­nol­o­gy Hero, Procla­ma­tion, City of Richard­son, Sep­tem­ber 2019. 

Final­ist, D CEO Mag­a­zine’s Inno­va­tion Awards, Trans­porta­tion Cat­e­go­ry. This award hon­ors CEOs, CIOs, CTOs, entre­pre­neurs, and oth­er lead­ers dri­ving inno­va­tion in North Texas. 

CBS 11 News seg­ment, Richard­son Intro­duces New, Smarter Traf­fic Lights, March 2019.

Inter­view with the Dal­las Busi­ness Jour­nal, UT Dal­las Pro­fes­sor Helps Invent Traf­fic Lights That Talk To Each Oth­er And Reduce Con­ges­tion, August 2019. 

Inter­view with Smart Cities Con­nect, Uni­ver­si­ty of Texas at Dal­las and City of Richard­son Team Up On Col­lab­o­ra­tive Traf­fic Sig­nal Tim­ing Sys­tem, April 2019. 

Arti­cle in Dal­las Inno­vates, Go Time: Traf­fic-Con­trol Sig­nals Cut Stop­light Wait by 40% in Richard­son, March 2019. 

Arti­cle in Com­mu­ni­ty Impact News­pa­per, Mul­ti­year Over­haul to Traf­fic Infra­struc­ture Sys­tem Under­way in Richard­son, April 2019.