Integrated Commodity Flow Survey with Advanced

TechnologyMoshe Ben-Akiva

August 2015

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Outline

1. Future Mobility Sensing

2. Truckers @ MIT

3. Integrated approach

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1. Future Mobility Sensing

2. Truckers @ MIT

3. Integrated approach

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Automated travel survey that leverages• increasingly pervasive smartphone ownership• advanced sensing technologies• machine learning techniques

to deliver previously unobtainable range of behavioral data and insights.

Future Mobility Sensing

July 2, 2015 | Presentation to MoT

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Automated and integrated travel survey system

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User Interfaces

Non-intrusive iOS and Android apps

User friendly activity diary that users can edit and provide additional information

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Field Test in Singapore

• LTA conducted Household Interview Travel Survey (HITS) 2012 with ~10,000 households.

• More than 1500 HITS respondents also participated in FMS demonstration project (October 2012 – September 2013)

• Known issues in traditional method:

– Short activities under-reported– Over-estimated travel times for short trips– Reporting of a simple (typical) day

• FMS delivers richer, higher resolution, multi-day travel and activity dataset

HITS vs FMS: An example

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Recent Developments

1. Enhanced technology2. Additional capabilities

• Event based on-phone surveys- Happiness- Transit quality

• Context specific SP3. Commercialization

1. Future Mobility Sensing

2. Truckers @ MIT

3. Integrated approach

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Motivation

• Toll roads (Perez and Lockwood 2006)

- 30-40% of new urban expressway mileage in the US

- 150 new centerline miles expected per year

• Heavy trucks on typical toll road (S&P 2005)

- 10% of traffic flow

- 25% of revenue

• Toll road forecasts biased and with high variance (Bain 2009)

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This study

• survey of truck route choice

• data collected directly from drivers

• two phases:

- Phase I – Driver questionnaires with route choice stated

preferences (SP)

- Phase II – GPS-based revealed preferences (RP) data

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SP study: Effect of tolls

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Phase I – Key findings

• Wide variability in preferences towards toll roads and tolls

• Route choices depend on multiple factors

- Travel time, tolls, delays

- Toll bearing terms

- Driver compensation method

- Shipment characteristics

• For more details: Moshe Ben Akiva, Hilde Meersman, Eddy van de Voorde (eds), Freight Transport Modelling, Emerald Books, May 2013

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Phase II – RP data collection (adaptation of FMS)

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GPS logger• Trucks equipped with off-the-shelf loggers (SANAV CT-24)

- Monitor all trips continuously- Transmit data in real-time to server

• Collects:- Location data- Speed- Timestamp

• Report Intervals- Time intervals- Minimum distance

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Backend Algorithms

• Applied to the data received by the backend (MIT server):

- Trace creation (FMS)

- Stop detection (FMS)

- Map Matching (Open Street Map)

- Toll detection (Open Street Map)

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Web interface• Validate and correct movement information

• Collect additional information

- Pick-up & delivery schedules

- Cargo type

- Tolls, methods of paying

• Exit survey

- Personal information

- Context specific SP18

Web interface

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Exit Survey

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Data collection process

• Over the phone using lists of trucking companies

• At truck stops and rest areas

- Indiana

- Massachusetts

- Texas

- Ontario

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Driver type: Long tour

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Driver type: Short tour

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Driver type: ‘Gypsy’

Same driver, different route

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Same driver, different route

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Same day, different route

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Truck Drivers’ Survey in Singapore• System setup for data collection in Singapore•New questionnaires designed for urban freight

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• Use the On-Board Diagnostic (OBD) port to connect to vehicle’s engine

• Data collected (second-by-second):– GPS location– vehicle speed– fuel consumption– other engine parameters (engine rpm,

air intake temperature, etc.)

• Able to track route, stops, driver behavior, idling, fuel use and emissions

Truck Telematics - OBD Devices

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Sample OBD Data from a TruckLogged truck trips in a single day

Idling as % of trip time = 51%Idling as % of fuel use = 25%

Single trip sample OBD data logged

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1. Future Mobility Sensing

2. Truckers @ MIT

3. Integrated approach

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Integrated approach

•integrated survey design

- establishments

- carriers/drivers

• innovative technology

- FMS

- tracking/tracing of vehicles and shipments

•urban CFS and nationwide CFS

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Business Establishments

Truck Drivers

Carriers

Tablet-based questionnaire• Needs and capacity, storage, parking, loading

and unloading, fleet size, etc. • Commodities

• GPS logger • Web-based or tablet-based verification

• Web-based questionnaire and GPS loggers for drivers

Tracking shipment• RFID tags attached to

shipments

Integrated approach (cont’d)

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2a. Producer- Questionnaire- Tag shipments

1. Surveyor

3. Truck driverPick-up/delivery

2b. Retailer, etc.- Questionnaire- Tag shipments

4. Carriers- Web-based

questionnaire

5. Truck driver (hired or owned)- Verify stop purpose

and commodity type

Establishment and Driver survey

Carrier and Driver survey

Operational flow

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Integrated technology

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Establishments and carrier surveys• Tablet-based questionnaires and shipment tracking

Raw data

Server

Survey Data

GIS data &

POI

TRACKING SHIPMENTS

WEB- TABLET-BASED SURVEYS

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Thank You!

mba@mit.edu