1 Behavioral Micro-Simulation Jose Holguin-Veras, Ph.D., P.E. William H. Hart Professor VREF’s Center of Excellence for Sustainable Urban Freight Systems Center for Infrastructure, Transportation, and the Environment Rensselaer Polytechnic Institute jhv@rpi.edu
Main goals 2 To produce a reasonable guess of freight traffic in metropolitan areas using: Freight trip generation estimates (using NCFRP 25 models) Known delivery patterns, such as tour length distributions by industry sectors (obtained from data collected by RPI from carriers and receivers) Observed traffic counts at key corridors The BMS was originally developed to assess the impacts of alternative policies to foster off-hour deliveries (7PM to 6AM)
Key components 3 Freight trip generation (FTG): estimated using the NCFRP 25 models and Zip Code Business Pattern data Synthetic population of carriers (and receivers, if needed) is created Using the data collected by RPI, the sample data is used to create the population of carriers needed to make all deliveries in the metro area The origin of the deliveries are set to be the locations were warehouses and distribution centers are located Delivery tours are created: Match the tour length (number of stops) by industry sector Match the number of deliveries by ZIP code (or any other level of geography used)
Graphically: Freight Trip Generation 4
Graphically: Synthetic population of carriers 5 Different industry sectors have different tour lengths NYC and NJ (Holguin-Veras et al. 2012): Average: 8.0 stops/tour; 12.6% do 1 stop/tour; 54.9% do < 6 stops/tour; 8.7% do > 20 stops Synthetic population match observed traffic and FTG
Tour simulations 6 Select a truck in an industry sector Number of stops is randomly assigned Select receivers at random from the group of receivers in that sector Compute optimal tour and store it Repeat until delivery tours satisfy the FTG for the entire area 2) Five receivers 1) Origin of a truck that carries food products to five restaurants
Example: Use of the BMS in the OHD project
BMS use in the off-hour delivery project 8 Define range of incentives to receivers for OHD Carrier/receiver synthetic generation Randomly select industry segment o Generate/locate carrier o Generate/locate receivers to serve Ordinal logit model (Holguin-Veras et al 2013) Receiver behavioral simulation Model receiver’s decision to accept OHD a) Base case (no OHD) b) Mixed operation Carrier behavioral simulation Compute costs for base case and mixed operation Model carrier’s decision Repeat for another carrier-receivers set Change incentives, reset participation counts Legend: End Carrier depot Regular-hour receiver Off-hour receiver Output: Joint Market Share (JMS) of OHD Receivers Market Share (RMS) at TAZ level
Ordered logit model with random effects 9 This model reproduces receivers’ response to incentives Model Model 1 Model 2 Independent variables Parameter t-stat Parameter t-stat Constant 0.61 (2.78) 0.22 (1.00) Number of deliveries -0.07 (-9.17) -0.08 (-11.66) Incentives One time incentive in $1000 (OTI) 0.18 (6.95) 0.17 (6.76) Carrier discount in percent (CDR*100) 3.00 (6.81) 3.10 (7.12) Incentives Business Support (BS) 0.55 (3.82) 0.51 (3.52) Public Recognition (PR) 0.34 (2.24) 0.38 (2.48) Trusted Vendor (TV) 0.94 (4.29) NAICS NAICS code Clothing stores, binary variable -2.73 (-4.57) -2.46 (-4.32) Performing arts, binary variable -1.96 (-5.69) -4.80 (-12.38) Interaction terms: OTI and NAICS Interaction terms: OTI for food and beverage stores 0.12 (2.56) 0.20 (4.24) OTI for apparel manufacture stores 0.23 (1.72) 0.11 (1.88) OTI and NAICS OTI for clothing stores 0.24 (3.18) 0.25 (3.40) OTI for nondurable wholesalers 0.33 ( 6.83) 0.37 (7.62) Interaction terms: CDR and NAICS CDR for personal laundry -2.11 (-2.98) -2.08 (-3.25) Interaction terms: Trusted vendor and NAICS Interaction terms: TV for food and beverage stores 4.35 (7.29) 2.02 (3.17) TV for performing arts 4.65 (2.56) 13.49 (11.16) TV and NAICS TV for clothing stores 5.06 (8.28) 2.24 (4.06) TV for miscellaneous stores retailers 6.59 (13.63) 3.17 (5.86) Parameters µ (1) 1.88 ( 21.54) 1.91 (21.36) µ(2) 4.56 (34.64) 4.56 (34.14) µ(3) 7.63 (40.45) 7.55 (40.51) Sigma 4.58 (27.64) 4.74 (25.83) 1522 1522 n Log likelihood -1390.89 -1388.50
BMS Results 10 OTI = $0 OTI = $4,000 OTI = $2,000 avg = 2.2% avg = 3.4% avg = 2.7% max = 6.2% max = 7.6% max = 7.6% min = 0.6% min = 1.3% min = 1.2% OTI = $6,000 OTI = $8,000 OTI = $10,00 avg = 4.3% avg = 5.5% avg = 7.0% max = 9.9% max = 11.9% max = 13.4% min = 1.9% min = 2.6% min = 3.5%
Example: Geographically Oriented Incentives
Geographically focused incentives: case of NYC 50% of establishments are located in Midtown Manhattan being Upper Manhattan (UM) responsible for 52% of the + incoming freight trips to the city Central Park (CP) Two geographic distribution have been considered: Midtown Manhattan (1) Lower and Midtown (MM) + (2) Central Park and Upper Lower Manhattan (LM) Scenarios consider giving incentives to either the entire Manhattan or only to Lower and Midtown Manhattan
Results of geographically focused incentives 13 Ratio Budget/JMS provides an idea about the amount of resources required to achieve a 1% JMS The results also show the superiority of geographically focused incentives which requires between 71% and 75% less expenditures than incentives spread out all over Manhattan Ratio Budget/JMS Lower and Midtown Central Park and OTI Lower and Midtown Manhattan Upper Manhattan Manhattan ($K) Manhattan OTI JMS RMS Budget JMS RMS Budget 1 0.31 0.22 ($K) (%) (%) ($M) (%) (%) ($M) 2 0.67 0.48 1 6.5 1.7 1.4 6.7 1.8 0.4 3 1.05 0.75 2 7.0 1.9 3.4 7.0 1.9 0.8 4 1.45 1.08 3 7.4 2.1 5.5 7.0 1.9 1.2 5 1.89 1.40 4 7.8 2.3 8.5 7.5 2.2 2.1 6 2.41 1.76 5 8.0 2.4 11.2 8.2 2.4 2.8 7 2.85 2.16 6 8.6 2.7 15.2 8.4 2.6 3.7 8 3.46 2.68 7 8.9 2.7 19.2 8.6 2.7 4.5 9 4.07 3.10 8 9.7 3.2 26.1 9.1 2.9 5.9 10 4.68 3.52 9 9.6 3.3 29.7 9.7 3.3 7.3 10 10.3 3.6 36.2 9.9 3.4 8.8
Example: Self-Supported Freight Demand Management
Self supported freight demand management 15 A self-supported freight demand management system (SS-FDM), is one that generates the funds required for a continuing improvement towards sustainability The incentives to be handed out to the receivers are generated by a toll surcharge to the vehicles that travel in the regular hours The analyses consider tolls to only trucks (per axle) or both; trucks and cars. Finally, different levels of toll collection efficiency were also considered
Results: tolls to trucks (per axle) 16 OHD Total Yearly Yearly toll revenues (car surcharge = $0) One-time- % OHD tours incentive incentive Freight vehicle surcharge per axle: incentive (year) budget budget $1 $2 $5 $8 $10 $0 7.1% 8,467 $0.00 $0.00 $77.44 $154.88 $387.19 $619.51 $774.39 $1,000 7.6% 9,031 $5.65 $1.88 $77.04 $154.09 $385.21 $616.34 $770.43 $2,000 8.2% 9,783 $26.32 $8.77 $76.52 $153.03 $382.58 $612.13 $765.16 Toll collection $3,000 8.8% 10,463 $59.89 $19.96 $76.04 $152.08 $380.19 $608.31 $760.39 $4,000 9.5% 11,265 $111.95 $37.32 $75.48 $150.95 $377.38 $603.81 $754.76 100% $5,000 10.3% 12,209 $187.14 $62.38 $74.81 $149.63 $374.07 $598.51 $748.14 $6,000 11.0% 13,058 $275.51 $91.84 $74.22 $148.44 $371.09 $593.75 $742.19 $7,000 11.9% 14,175 $399.58 $133.19 $73.44 $146.87 $367.18 $587.49 $734.36 $8,000 12.8% 15,200 $538.65 $179.55 $72.72 $145.43 $363.59 $581.74 $727.17 $9,000 13.7% 16,279 $703.14 $234.38 $71.96 $143.92 $359.80 $575.68 $719.60 $10,000 14.9% 17,754 $928.70 $309.57 $70.93 $141.85 $354.63 $567.41 $709.26 Yearly toll revenues (car surcharge = $0) OHD Total Yearly One-time- % OHD tours incentive incentive Freight vehicle surcharge per axle: incentive (year) budget budget $1 $2 $5 $8 $10 $0 7.1% 8,467 $0.00 $0.00 $58.08 $116.16 $290.40 $464.63 $580.79 $1,000 7.6% 9,031 $5.65 $1.88 $57.78 $115.56 $288.91 $462.26 $577.82 Toll collection $2,000 8.2% 9,783 $26.32 $8.77 $57.39 $114.77 $286.93 $459.10 $573.87 $3,000 8.8% 10,463 $59.89 $19.96 $57.03 $114.06 $285.15 $456.23 $570.29 75% $4,000 9.5% 11,265 $111.95 $37.32 $56.61 $113.21 $283.04 $452.86 $566.07 $5,000 10.3% 12,209 $187.14 $62.38 $56.11 $112.22 $280.55 $448.89 $561.11 $6,000 11.0% 13,058 $275.51 $91.84 $55.66 $111.33 $278.32 $445.31 $556.64 $7,000 11.9% 14,175 $399.58 $133.19 $55.08 $110.15 $275.38 $440.62 $550.77 $8,000 12.8% 15,200 $538.65 $179.55 $54.54 $109.08 $272.69 $436.30 $545.38 $9,000 13.7% 16,279 $703.14 $234.38 $53.97 $107.94 $269.85 $431.76 $539.70 $10,000 14.9% 17,754 $928.70 $309.57 $53.19 $106.39 $265.97 $425.56 $531.95 Note: The shaded cells represent non-feasible combinations of financial incentives to receivers and tolls.
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