Presentation on theme: "MAG New Generation Freight Model SHRP2 C20 IAP Project Vladimir Livshits, Ph.D. 2014 AMPO Annual Conference, Atlanta, GA October 23, 2014 Freight Session."— Presentation transcript:
MAG New Generation Freight Model SHRP2 C20 IAP Project Vladimir Livshits, Ph.D. 2014 AMPO Annual Conference, Atlanta, GA October 23, 2014 Freight Session
Planning efforts at ADOT, MAG and PAG have to address new scale of geography – Arizona’s Sun Corridor Mega-Region – Very significant growth in the freight traffic – Part of the global supply chain 10/23/20142014 AMPO Annual Conference3 Modeling areas reflect mega-regional approach. MAG/PAG ABM includes Maricopa, Pinal, Pima and portions of Yavapai and Gila counties Source: http://www.jpacaz.org/map.asp
10/23/20142014 AMPO Annual Conference4 Freight Planning Safety and Efficiency of shipping Congestion and Hazards Economic Impact Communities and Social Equity Integration with Regional Planning – Freight Corridors Land Use and Environmental Impact Freight Mobility
The Legacy 10/23/20142014 AMPO Annual Conference5
State of the Practice Truck Models served us well but fall short in answering future freight planning needs Aggregated model – does not provide for detailed land use, infrastructure, community planning scenario analysis. Insensitive to agent-based economic scenarios, does not account for evolutionary developments of economic agents in the forecast, insensitive to fine-grained network changes. Does not include supply chain models and is not suitable for development of economic scenarios on mega-regional scale. Insensitive to mega-regional supply chain scenarios and technological shifts. Static model - does not provide for integration with dynamic traffic simulations, detailed safety analysis, and agent-based passenger travel demand models with continuous timeline. Trip-based – is not consistent with operational behavior of carriers and as a result insensitive to operational scenarios or relevant network improvements. Does not account for multi-modal aspect of supply chains, does not forecast multimodal freight flows and is not sensitive to multimodal freight issues. 10/23/20142014 AMPO Annual Conference8
The Vision 10/23/20142014 AMPO Annual Conference9
SHRP2 C20 Guidance Strategic objectives of SHRP2-C20 project: Improve and expand the knowledge base Develop modeling methods to reflect actual supply chain management practices Develop modeling methods based on sound economic principles Maximize use of freight tools by public sector for planning and programming Improve availability and visibility of data between public and private sectors In order to achieve the above objectives, the following SHRP2 research initiatives will be addressed in this work: Establish techniques and standard practices to validate freight forecasts. Establish modeling approaches for “behavior-based” freight movement. Establish analytical approaches that describe how elements of the freight transportation system operate, perform, and impact the larger overall transportation system. Determine how economic, demographic, and other factors/conditions drive freight patterns and characteristics. Document economic and demographic changes related to freight choices. Advance research to effectively integrate logistics practices (private sector) with transportation policy, planning, and programming (public sector). 10/23/20142014 AMPO Annual Conference10
The Approach 10/23/20142014 AMPO Annual Conference11
Main Methodological Principles Agent-based micro-simulation model Multi-modal freight model Behavioral model, including economic behavior of establishments, shiuppers, carriers in travel generation and tour formation Integration with activity-based passenger model Industry-specific model 10/23/20142014 AMPO Annual Conference12
10/23/20142014 AMPO Annual Conference13 Tour Generation Heavy truck tour rates by industry type Stop Generation1 stop2 stops……..11 stopsTour Completion Yes – return to home base No – does not return Stop Purpose One of 10 stop types Retail Constr. Farming Resid. Govt. Warehs. Transp. Office Industrial Service Stop Location One of 3,000 TAZs Stop TOD Choice 1 st Stop TOD (24 1-hr periods) Next Stop TOD (24 1-hr periods) Source: Kuppam, A. et al. Development of a Tour-Based Truck Travel Demand Model using Truck GPS Data. Presented at the 2014 TRB 93 rd Annual Meeting. January 2014.
10/23/20142014 AMPO Annual Conference14 ATRI GPS All Truck IDs April 2011 All Trucks in April 2011 GPS Events = 3,429,603 Truck Tours = 58,637 Trucks = 22,657 All Trucks in April 2011 GPS Events = 3,429,603 Truck Tours = 58,637 Trucks = 22,657 ATRI GPS Truck ID 3570452 April 2011 One Truck (ID 357042) in April 2011 GPS Events = 719 Truck Tours = 40 Trucks = 1 One Truck (ID 357042) in April 2011 GPS Events = 719 Truck Tours = 40 Trucks = 1 Source: Kuppam, A. et al. Development of a Tour-Based Truck Travel Demand Model using Truck GPS Data. Presented at the 2014 TRB 93 rd Annual Meeting. January 2014.
10/23/20142014 AMPO Annual Conference15 Contractual work and administration Work plan and organization of TAG Data Collection – GPS data Data requirements and data sources Commodity flow data acquisition GPS data analysis and processing Collection and analysis of traffic counts List of main traffic generators and industries Establishments/ firm synthesis models Behavioral establishment interaction model/ distribution models Tour formation models for different truck types/industries Establishment survey, commercial vehicles survey Multimodal network and corresponding documentation. Mode choice models Firm Evolution Model Model Structure and methods Employment and land use projections Quality control and Assurance