Progress Meeting 3: Deployment Site Selection

Transcription

1 Progress Meeting 3: Deployment Site Selection Sponsored by: California Air Resources Board Performed by: Institute of Transportation Studies University of California, Irvine November 4 th, 2014

2 Outline 1. Project Overview 2. Task Schedule 3. Deployment Guidelines and Resources 4. Site Selection Methodology 5. Deployment Options 6. Summary 7. Next Steps

3 1. Project Overview Purpose: Address the body type data gap in quantifying the criteria pollutants and GHG emissions from trucks, and Fill a critical research need in goods movement studies. Method: Develop new models capable of classifying trucks by body type Inductive loop detector (ILD) signature data (at VDS locations), and Integration of WIM and ILD signature data (at WIM locations) Benefits: Improves emissions inventory and data for freight forecasting models Cost effective approach for truck activity data collection Uses existing detector infrastructure with minor cabinet hardware upgrades Non-intrusive deployment Existing traffic operations are not impacted by the upgrade

4 Comparison of Detector Technologies for Feature Obtaining Truck Data Conventional Inductive Loop Inductive Loop Signature WIM WIM + Inductive Loop Signature Truck Volumes * General Axle Configuration Body Configuration Information Total Number of Axles Axle Spacings Axle Weights Available Deployment Locations > 7,000 > 7, *Estimated HHDT and non-hhdt truck volumes via CalVAD 4

5 Automobile Transport Body Class FHWA 9 Examples Livestock Basic Platform Low Boy Platform Logging 53ft Box Container 40ft Box Container Tanks Enclosed Van Refrigerated Van Drop Frame Van

6 2. Task Schedule

7 Phase 3 Phase 2 Progress to Date Task Task Description Completion Phase 1 Proof of Concept Models 100% 2.1 Data Collection 100% 2.2 Model Enhancement from data fusion with WIM and signature data 60% 2.3 Investigate propagation of the WIM weight data to VDS 40% 2.4 Develop techniques for backcasting body classification data 75% 2.5 Develop optimal facility location model 100% 3.1 Deploy advanced detector cards and equipment to selected WIM and VDS stations 10% 3.2 System Shakedown 0%

8 3. Deployment Guidelines Up to 16 stations to be deployed Combination of VDS WIM station deployments Depends on available number of detector cards Inductive Loop Sensors Inductive Loop Sensors WIM Sensors VDS Site: Inductive Loop Sensors WIM Site: Inductive Loop + WIM Sensors

9 Benefits by Detector Type Truck Volume Data Available Weigh in Motion Vehicle Detection Station Before Deployment FHWA Classification Truck Weights Truck Body Types Truck Weights by Body Type Truck Volume Data Available Weigh in Motion Vehicle Detection Station After Deployment FHWA Classification Truck Weights Truck Body Types Truck Weight by Body Type

10 Field Hardware Components Hardware WIM 1060 Controller WIM isinc Controller VDS Field Processing Unit Communications (wireless modem) 1 per cabinet 1 per cabinet Advanced Detector Cards 1 lane per card none Up to 2 lanes per card Other Key Components Card file adapter Serial Bus Module none Field Processing Unit Card File Adapter Serial Bus Module

11 Advanced Detector Cards IST Cards Sampling rates: 150Hz 1200Hz USB, serial port Available IST Cards Sample Rate # Cards 150Hz Hz 7 USDOT SBIR CLR Analytics: Transportation System Performance Measurement Using Existing Loop Infrastructure Advanced detector card product development Sample rate: 5000Hz (adjustable with software) USB, SPI Port, Bluetooth, and Ethernet* (*planned feature) Prototype cards available in next few months?

12 4. Site Selection Methodology Stakeholder Input -ARB: Nesamani, Todd Sax, others -Caltrans: Doug, Stan, others Stakeholders define the region and potential corridors for analysis Optimization Method - Objective: Select sites within a region which maximize the total amount of net origin destination flows captured and variability in truck body types - Method: Flow-interception approach with truck GPS samples from ATRI Optimal locations are selected within region Stakeholder Review & Feedback Final review and approval Deployment Sites

13 5. Deployment Options: Air Basin Central Valley Major Routes: CA-99 and I-5 Other Routes: I-205, CA-180, CA-41, CA-152, CA-58 Existing Detector Sites: Total # WIM 1 (isinc) 13 (1060) Total # VDS 652

14 27 candidate VDS locations Central Valley Site Selection Available WIM and VDS Locations Possible WIM and VDS Deployment

15 5. Deployment Option: Metro. Area Los Angeles County Major Routes: I-5 and I-405 Other Routes: I-10, I-110, I-710, I-605, I-210, CA 91, and CA 60 Existing Detector Sites Total # WIM 5 (isinc) 9 (1060) Total # VDS Candidate VDS LA Area

16 LA Metro Area Available WIM and VDS Locations Possible WIM and VDS Deployment

17 5. Deployment Option: State-Wide Total number of detection sites in CA: Total # WIM 18 (isinc) 98 (1060) Total # VDS 7,927 2 Strategies: (A) Stakeholder Insight VDS Only (B) Optimization Approach WIM Only 17

18 Strategy A: Stakeholder Insight Currently Deployment Automatic vehicle classifier (AVC) sites and WIM to serve as CVCs Focus on heavy truck corridors with no WIMs or nearby WIMS Upgrade existing VDS into Pseudo Continuous Vehicle Class Sites (CVC) VDS sites with signature cards = Pseudo CVCs Deployment only as VDS locations 18

19 Strategy B: Optimization Evaluated for WIM sites (i.e. no VDS included in analysis) Site Name 3 Antelope Valley (I-80) 1 Lodi (I-5) 57 Pinole (I-80) 102 Delhi (CA-99) 47 Castaic (I-5) 82 Glendora (I-210) 77 Colton (I-10) 59 LA 710 (I-710) 95 Ontario (CA-60) 15 Irvine (I-5) 19

20 6. Summary Outlined a general approach for site selection: Stakeholders select region then optimization algorithm selects sites Defined three deployment options: 1. Air Basins: Central Valley 2. Metropolitan Areas: LA Metro Region 3. State-Wide: (A) Stakeholder Insight (B) Optimization

21 7. Next Steps Wrap-up model development Classification models under investigation Propagation model under investigation Deployment Final site selection Hardware and software configuration design

22 Questions? Thank you.