IBM Research Smarter Transportation Analytics

Transcription

1 IBM Reseach Smate Tanspotation Analytics Laua Wynte PhD, Senio Reseach Scientist, IBM Watson Reseach Cente INSTRUMENTED We now have the ability to measue, sense and see the exact condition of pactically eveything. INTERCONNECTED People, systems and objects can communicate and inteact with each othe in entiely new ways. INTELLIGENT We can espond to changes quickly and accuately, and get bette esults by pedicting and optimizing fo futue events IBM Copoation

2 The commute pain index Suveyed 8,042 commutes in 20 cities on six continents to bette undestand consume attitude towad taffic congestion Compiled the esults into an Index that anks the emotional and economic toll of commuting in 20 intenational cities (on a scale of 1 to 100, with 100 being the most oneous) The index is compised of 10 issues: o commuting time o time stuck in taffic o pice of gas is aleady too high o taffic has gotten wose o stat-stop taffic is a poblem o diving causes stess o diving causes ange o taffic affects wok o taffic so bad diving stopped, o decided not to make tip due to taffic Click fo the 2011 Commute Pain Suvey In ode to impove taffic flow and congestion, cities need to move beyond knowing and eacting; they have to find ways to anticipate and avoid situations that cause congestion that could tun the wold into one giant paking lot 2011 IBM Copoation

3 IBM Smate Tanspotation Focus Aeas Tanspotation Stategy and Planning Tanspotation Matuity Model Total Cost of Owneship Models Multi-Domain Impact Analysis Tanspotation Advisoy Sevices Integated payment solutions fo multiple tanspotation modes Shaed Back office acoss multiple cities Cloud Infastuctue Integated Fae Management ITS Solutions Innovative Tanspotation Picing Single Highway/Bidge Tolling Netwok of Tolled Highway (incl. HOT netwoks) City Congestion Chaging Usage Based Picing/Taxation Tanspotation Infomation Management Real Time Multimodal Tavele Infomation Pefomance Management and Repoting Taffic Pediction and Analytics Asset Management Decision Suppot Systems Multimodal Integation and Opeations Optimization 2011 IBM Copoation

4 Multimodal Tanspotation Matuity Model Benchmaking Key: San Diego London Stockholm Singapoe Seoul Othe 2011 IBM Copoation

5 Multimodal Tanspotation Matuity Model Benchmaking Key: San Diego London Stockholm Singapoe Seoul Othe 2011 IBM Copoation

6 Multimodal Tanspotation Matuity Model Benchmaking Key: San Diego London Stockholm Singapoe Seoul Othe 2011 IBM Copoation

7 Multimodal Tanspotation Matuity Model Benchmaking Key: San Diego London Stockholm Singapoe Seoul Othe 2011 IBM Copoation

8 Multimodal Tanspotation Matuity Model Benchmaking Key: San Diego London Stockholm Singapoe Seoul Othe 2011 IBM Copoation

9 Multimodal Tanspotation Matuity Model Benchmaking Key: San Diego London Stockholm Singapoe Seoul Othe 2011 IBM Copoation

10 Multimodal Tanspotation Matuity Model Benchmaking Key: San Diego London Stockholm Singapoe Seoul Othe 2011 IBM Copoation

11 Innovation Concepts Tanspot Infomation Management Issue: stained infastuctue Moe tanspot capacity is needed, but constuction of new physical infastuctue is cost pohibitive, if even possible Issue: navigating mass tansit Tansit is pat of the solution, but it must be easie fo taveles to find thei way and weigh options Requied Innovation: foundation of data integation & analytics Multiple data souces acoss tanspot modes Integated to single foundation of infomation Leveaged fo multiple uses Based on open standads Integated systems appoach, not point solutions bus tain weathe sevice vanpool ai taxi pobe fleets histoical data incident loop detectos floating cell 3 d paty video analytics paking toll ganty Data Integation & Analytics Data Analytics: Taffic Pediction Tool Data Expansion Algoithm Bus Aival Pediction Decision Suppot System Optimize Tavele Advice Netwok Response eal-time advice oute planning pesonalization signal timing tansit outing incident esponse pefomance measuement 2011 IBM Copoation

12 Intelligent IBM TPT Tanspotation Systems Initiative Building the Foundation fo Smate Tanspotation Integate assets and infomation to impove opeations Identify impact of changes to custome expeience & opeations Pedict issues acoss tanspotation modes to optimize capacity Unique value ealized What data is elevant? How can it be acquied, cleansed, and integated? 1 Manage Data Descibe the cuent state Pedict futue states Pescibe optimal actions 2 Analyze Pattens 3 Optimize Outcomes How to implement actions? How to disseminate infomation? Management efficiency Retun on assets Custome loyalty Sales and pofit Netwok awaeness Custome satisfaction Incident pevention Reduced netwok congestion Enabled by the IBM Govenment Industy Famewok Use of Smate Planet capabilities 2011 IBM Copoation

13 Taffic Pediction Tool (TPT) Issue: eal-time is too late Little automated use is made of the gigabytes of eal-time taffic data today; often, by the time it is eceived, it is no longe epesentative of the actual taffic IBM Innovation: foecast the futue IBM s TPT povides a laye of intelligence by using senso data in sophisticated algoithms that ceate elevant insights fom the aw data blue = foecast black = actual ed = incident volume time tool sceenshot TPT accuately foecasts futue taffic conditions Aeas of Potential Use Taffic Opeations: Advanced Tavele Infomation; taffic signal timing, amp meteing, oute planning & advice, dynamic picing 2011 IBM Copoation

14 ID ID ID ID ID ID ID ID ID minute-ahead volume foecast (blue) vs. actual on Dec 10, Roadwoks wee pesent on Link and a vehicle beakdown on Link IBM Copoation

15 NJTA TPT Test Section of Expessway Studied Gaden State Pakway o Raitan Toll Plaza to Exit 145/I-280 o Southbound o Compising 30 links on the Pakway New Jesey Tunpike - I-95 o Nothbound and Southbound o Compising 65 links on the Tunpike Deployment undeway following successful tests Gaden State Pakway, 10-mn pedictions, daily aveage by oad link Oveall aveage accuacy ove two days analyzed is 95% 2011 IBM Copoation

16 Taffic Pediction value poposition Adjust taffic contol to optimise taffic flow Dynamically change oad picing Reduced congestion Input to Taffic Management Adjust taffic contol to pioitise public tansit Enhanced dive satisfaction Taffic Pediction Tool Visualise pedicted taffic status Calculate jouney times Infom individual (eg. tavelles potal) Input to jouney / oute estimation (eg. SatNav) Set Vaiable Message Signs Pedict bus aival times at stops Reduced envionmental impact Economic efficiency benefits Enhanced tavelle satisfaction Optimise bus dispatching Geate use of public tanspot IBM Copoation

17 Intelligent IBM TPT Tanspotation Systems Initiative IBM DATA EXPANSION ALGORITHM (DEA) Cuent state of LTA taffic volume data Poblem desciption: Detemine eal-time taffic when senso data is unavailable Solution: IBM s Data Expansion Algoithm (DEA) Outcome and Benefits: Expand eal-time data to as close as possible to full netwok 2011 IBM Copoation

18 Intelligent IBM TPT Tanspotation Systems Initiative BUS ARRIVAL PREDICTION (BAP) Poblem desciption: Povide tavelles with accuate and fequently updated futue bus aival time. Existing simila systems pefomance failed to match the sophistication level of data souce. Innovative appoach is needed to fully unleash the useful infomation hidden in vaious data souce in a moe sophisticated manne, in ode to bing the foecasting accuacy up to a level nea plus/minus 1 minute with 90% confidence. (*Cuent sevice level is within +/- 3 min with 85% confidence) Solution: IBM is cuently collaboating with LTA, co-developing a new foecasting algoithm. It is mining peiodic tends and pattens of bus aivals, using bus GPS data as well as the TPT pediction of futue taffic status on subsequent links along the bus outes. Outcome (ongoing wok, inteim outcome): Selected bus sevice oute 61 and 75, 8 bus stops each IBM Copoation

19 Decision Suppot System (DSS) Optimize Tanspotation Command Centes today ae lagely not equipped to detemine esponse plans based upon lage volumes of data and analytic methods. Typically, today, some eal-time data is visualized, but the expected outcomes of potential esponses ae geneally not computed. It is widely accepted that the Command Cente of the Futue should leveage the massive amounts of tanspot data fo moe effective esponse plan geneation. This is the motivation of the Decision Suppot System (DSS) Optimize 2011 IBM Copoation

20 Intelligent IBM TPT Tanspotation Systems Initiative Without DSSO Late! All Routes Ealy! Off Route Malfunction ALARM! Request To Talk? What ae the impacts to late sevice? 2011 IBM Copoation

21 Decision Suppot System Optimize Without DSS Optimize 2011 IBM Copoation

22 Decision Suppot System Optimize With DSS Optimize 1) VMS Route Guidance 2) Ramp Closues 3) Optimized signal & amp meteing Response Plan Deploy Time Release Time Expected benefit 1, 2 and 3 Immediate T + 30 min Highest 1 and 3 only Immediate T + 20 min Modeate 2 only T + 5 min T + 45 min Modeate 2011 IBM Copoation

23 Sceen Shot of DSSO Includes taffic pediction, useful fo nomal o semi-nomal conditions Incident detection module is pesent. Includes Incident Impact Facto Evaluation, a linkby-link list of impacted links and the degee of impact. DSSO Optimal contol plan geneation. Expected benefit and isk of each DSSOgeneated plan Ability to ente a diffeent, non-dsso geneated plan and assess its expected benefit IBM Copoation