Road Public Transport Informa5on Management Program BIG DATA. Market Consulta5on August 7, 2015

Transcription

1 Road Public Transport Informa5on Management Program BIG DATA Market Consulta5on August 7, 2015

2 How does DOTC collect transport data? 1. Data is collected either through household interviews (HIS) or on- board surveys 2. Study area is usually Metro Manila (17 ci5es 1 municipality) or Mega Manila ( + Bulacan, Laguna, Rizal, Cavite) 3. Data takes a very long 5me to be processed and by the 5me policies and ac5ons are implemented, travel demand has changed again JUMSUT JICA Update on Metro Manila Study on Urban Transport MMUTIS Metro Manila Urban Transport Integra5on Study MMPTPSS 2012 Mega Manila Public Transporta5on Planning and Support System RTRS Road Transit Ra5onalisa5on Study MUCEP MMUTIS Update and Capacity Enhancement Project

3 There must be a faster way to collect and analyze transport data.

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5 What is big data and what can it do? Big data describes large and increasing volumes of digital informa5on that are difficult to manage with tradi5onal data tools Heat maps generated from anonymous mobile data can produce similar results to data collected through tradi5onal surveys. Mobile Data Conven5onal Survey Big data plaaorm Any pla\orm that supports big data; captures, stores and Processes Big data Colombo (Sri Lanka) region transporta5on hotspots Source: h_p://

6 How will DOTC use big data? 1. Planning and Policy formula5on Collect trip ac5vity data and passenger profile Determine the opemal routes, number of PUV franchises per route, and service plan per route Determine policies to improve public transport 2. Regulatory and enforcement Provide addi5onal data to help regulate and enforce transporta5on rules (e.g., speeding, colorum, out- of- line) Provide services on routes with undersupply of public transporta5on and adjust those with oversupply of services 3. Infrastructure development Iden5fy major areas un- served (in public transport) that needs to be developed Recommend which mass transit modes and infrastructure are needed to be developed

7 Project Objec5ves 1. Data- driven transport planning 2. Real 5me demand analysis 3. Faster route ra5onaliza5on 4. Route op5miza5on 5. Build big data analysis capability within DOTC 6. Planning and policy recommenda5ons to provide commuters with: Faster travel 5me Be_er transport infrastructure Safer and more reliable transport services

8 Project Scope Project Area: Mega Manila (as defined in MUCEP) DATA SUBSCRIPTION AND DATABASE MANAGEMENT Secured data center rental Big data pla\orm Irreversible anonymous aggregated telco data subscrip5on VISUALIZATION PLATFORM AND TRANSPORT PLANNING ANALYSIS Transport planning applica5on sofware with license and maintenance support Bi- annual corridor reports and service plans CONSULTING SERVICES, TRAINING AND CAPACITY BUILDING Program and project management Consul5ng and transport analysis Capacity building on big data analysis

9 RAW DATA SOURCES Solu5on Default Package Consultant Provided DOTC Telco Standard reports Service plans / corridor reports DOTC generated reports PUV data Big Data Solu5on GPS Anonymized data pool

10 Project Deliverables DELIVERABLES % Timeline 1. Validate and update MUCEP HIS database, transport models, and reports* 10% Year 1 2. Prepare road public transport service plans (eg. PUB, PUJ, AUV) and update RTRS* 10% Year 1 3. Update medium and long term transporta5on Greater Metro Manila master plan based on Roadmap for Transport Infrastructure Development for Metro Manila and its Surrounding Areas (Region III 10% Year 3 and Region IV- A) (JICA DREAM plan)* 4. Provide 10 bi- annual reports on insights to improve public transporta5on level of service in Metro Manila (eg. decrease travel 5me, cost, transfers, etc.) With documenta5on on replicable methodology used for modeling and simula5ons in the report* a. Reports % Year 1 b. Reports % Year 2 c. Reports % Year 3 d. Reports % Year 4 e. Reports % Year 5 5. Capacity building and knowledge transfer, training on database usage 5% + 5% Year 1 & 4 and cluster compu5ng framework for DOTC stakeholders.

11 Considera5ons 1. The project is for consultancy services 2. Firms should have experience in providing big data solu5ons 3. Telephone companies must be available to have contracts with more than one big data solu5on provider 4. Requires remote access and secure connec5on from DOTC to data center

12 Proposed Timelines Milestones Feasibility assessment and approvals Invita5on to Pre- qualify and bid Submission of Qualifica5on documents Pre- qualifica5on Evalua5on Issuance of Request for Bid Proposal Bid prepara5on Pre- bid conference Bid submission and evalua5on No5ce of Award August nd week September th week September 2015 October 2015 October 2015 November 2015 November 2015 December 2015 December 2015

13 For inquires and comments please e- mail: