The Acquisition of Long-Distance Freight Data Workshop B6: ISCTSC 2008 Annecy, France This workshop will focus on how to improve the acquisition of long-distance freight data. Long distance is defined as 500+ kilometers (about 300+ miles). Data on long distance freight transport can "acquired" by management sources (for rail, waterborne transport, etc.) or by surveys (e.g., Commodity Flow Surveys, surveys on freight vehicles harmonized by EUROSTAT). Challenging issues are: How to capture information on the multiple "trips" of the transport chain that might include more than one mode of transportation; Opportunities and barriers provided by data acquisition technologies (e.g., RFID); How to optimize the sample scheme to collect information on alternatives to truck-only chains; How and when to combine survey data with administrative records; How to capture data on vehicles and loading factors for the measurement of energy consumption and GHG emissions; among others. *more freight jpgs* B6. The Acquisition of Long Distance Freight Data Workshop Chair: Kara Kockelman, UT Austin, Texas (kkockelm@mail.utexas.edu, http://www.ce.utexas.edu/prof/kockelman/home.html) Rapporteur: Professor Michael Browne - University of Westminster, m.browne@westminster.ac.uk Resource Paper Authors: Alan McKinnon, Heriott Watt University, Scotland and Jacques Leonardi, INRETS, France (A.C.McKinnon@hw.ac.uk & jacques.leonardi@inrets.fr) Discussant: Christophe Rizet, INRETS, France (christophe.rizet@inrets.fr) WORKSHOP SCHEDULE: Thurs. 11-1 Contributed papers: 30 minutes + 10 min for any discussant + 10-20 min for Q&A - Houée Michel, The experience of the progressive elaboration of a multinational harmonised database about freight transit through Alps and Pyrenees - Pedro José Pérez-Martínez, The Vehicle Approach for Freight Road Transport: Energy & Environmental Analysis in Spain (recent addition) Friday AM: Resource paper: Alan McKinnon and Jacques Leonardi, The Collection of Long Distance Road Freight Data in Europe (Christophe Rizet, discussant) to be delivered by Jacquest, 45 minutes presentation + 20-30 minutes discussant remarks (+ 4 hours of healthy discussion!) Friday PM: Work-groups on key issues identified; presentation & discussion of recommendations for the larger conference group. CONTENT SUGGESTIONS BY COLLEAGUES WHO CANNOT MAKE IT TO ANNECY: Jose Holguin-Veras: One interesting assignment is a discussion about the pros and cons of the different alternatives to a national freight survey: 1) Shipper based survey (like CFS) 2) A longitudinal carrier based survey (like the French survey) that tracks shipments as they mode along the supply chain 3) Traditional carrier based surveys (like the ones in traditional origin-destination surveys) 4) Hybrid modalities involving combinations of the above Nathan Erlbaum suggests "rolling up" data by industry and/or location in order to avoid 50% non-reportable data that often emerges in CFS & other freight data sets (for anonymity protection of US firms). (E.g., trip generation by establishment size [across US]) Could probably reduce to 4 or 5 commodity categories & get all the data one needs to do reasonable models. He is a fan of establishment surveys if one has the money. But simply re-organizing the US CFS data should do it, he thinks. The government gives us County Business Patterns, so why don't they give us truck data by county or at least by Census reguion? Transferability of freight model parameters & major trends are key topics. With high energy prices, will trucks & planes slow down & go less often? If so, will JITime shipping fall by the wayside? There's a structural reorganization going on in the US, due to mortgage crisis, run up of fuel costs, depreciation of dollar, lack of energy plan, neglect of conservation. There's migration from climate change issues. And vehicle design, location of businesses, condition & congestion of roads & rail, etc. What are the things we need to know to make the difficult decisions in next 5 years? How important is energy? What can we do to shift? What does sustainable freight transport mean? Telematics on vehicle very important for knowing where vehicle really is; quite different from what shipper thinks. Need much more estab-based so can model. Data exists within cfs but need to pay to have summarized differently, to avoid cell-size issues. There's FAF long-distance & there's LTL intra-urban delivery. Most trucks on road are single unit. State DOTs focused on their jurisdictional networks, rather than local roads. For govt to provide appropriate infrastructure, probably don't need to know where boxes go. Final Notes: (1) Alan McKinnon (lead author of our resource paper) writes: "Sorry that I am not going to be able to attend the Annecy conference - particularly as I spent quite a bit of time writing the resource paper. I'm giving a presentation at the International Transport Forum on climate change in Leipzig that week and the logistics of attending the two events proved too complicated and expensive." (2) Horst Binnenbruck's paper is titled "The Acquisition of Long Distance Freight Data" and can be found at http://www.isctsc.let.fr/papiers/workshop%20final%20version/7%20B6%20Binnenbruck.doc (+Appendix at http://www.isctsc.let.fr/papiers/workshop%20final%20version/7%20B6%20Binnenbruck%20Annexe) ________________________________ Bonjour! Guten morgen! Good morning! Buenos dias!

Participants Michel Houée (Contributed paper) Pedro José Martínez-Pérez (Contributed paper) Alan McKinnon (Resource paper) Jacques Leonardi (Resource paper) Christophe Rizet (Discussant) Bastian Chlond & Peter Ottmann (Univ Karlsruhe) Julius Menge (German Aerospace Ctr, Berlin) Danièle Patier & Mariame Mbacke (LET & INRETS) Arnim Meyburg (Cornell Univ., USA) Mike Browne (rapporteur – Univ Westminster) Kara Kockelman (chair – Univ. of Texas) 4 French, 3 German, 2 UK, 2 US, 1 Spain = 12

What is the Question? Traffic loads & management Infrastructure needs Economic interactions of firms Vehicle utilization (driver & fuel use) Logistics improvements Safety concerns Response to potential policies & new technologies Siting logistics centers

Key Challenges Tying purpose to instrument & frame Variety: Questions & users, Commodities & modes, Industries & vehicles, Locations & routes … Missing information: Values & volumes moved, Shipper costs & prices by mode, International & intermodal ties, Public vehicles, Fuel consumption … Speed of change: Implications for data acquisition, assembly & distribution Maintaining collection over long run Linking survey results effectively across micro and macro level Anticipating the impact of land use patterns & other explanatory variables (on trade patterns)

Next Steps Complementary Data Sets Needed: Establishment-based & non-truck modes (EU), carrier-based (US), roadside interviews, policy driven, … More Global View: Up & down the supply chains (expanding the frame) Sharing Instruments & Harmonizing Data Sets (via terminology & frame definitions, greater collaboration across agencies & countries) Research topic: How can new technologies contribute to this discipline? Adopt KPI outside of UK.

Next Steps Comparison of Establishment & Vehicle-based Survey Designs Mechanisms for Protecting Confidentiality while Releasing Useful Results & Products (+ can exploit emerging technologies) Demonstrate Value & Use of Data Collected (via model development, tying surveys); Educate our Students & Stakeholders Research topic: How can new technologies contribute to this discipline? Adopt KPI outside of UK.

Next Steps No single approach Global view – appropriate focus Instruments (sharing); data sets (harmonizing) Establishment & vehicle-based survey designs: more comparisons needed Protect confidentiality but exploit technology Engage attention, demonstrate value and educate stakeholders Research topic: How can new technologies contribute to this discipline? Adopt KPI outside of UK.

Global view – appropriate focus Next Steps Global view – appropriate focus Establishment & vehicle-based survey designs: more comparisons needed No single approach Engage attention, demonstrate value and educate stakeholders Protect confidentiality but exploit technology Instruments (sharing); data sets (harmonizing) Research topic: How can new technologies contribute to this discipline? Adopt KPI outside of UK.

L’équipe GENEPI vous dit merci! Research topic: How can new technologies contribute to this discipline? Adopt KPI outside of UK.