METRANS UTC

14-13 <p>Smart Truck Driver Assistant: A Cost Effective Solution for Real Time Management of Container Delivery to Trucks</p>

Project Number

14-13

Project Summary

Smart Truck Driver Assistant: A Cost Effective Solution for Real Time Management of Container Delivery to Trucks

Project Status

Complete

Project Brief

Year

2014

Topic Area

Integrated Freight and Passenger Systems

P.I. Name & Address

Professor and Chair, Computer Engineering and Computer Science; College of Engineering
California State University Long Beach
1250 Bellflower Blvd.
ECS-542
Long Beach, CA 90840
United States
burkhard.englert@csulb.edu

Co-P.I.

Professor, Department of Computer Engineering and Computer Science; College of Engineering
California State Univeristy, Long Beach
1250 Bellflower Blvd.
ECS-539
Long Beach, CA 90840
United States
mehrdad.aliasgari@csulb.edu
Professor, Department of Computer Science and Computer Engineering; College of Engineering
California State University, Long Beach
1250 Bellflower Blvd.
ECS-535
Long Beach, CA 90840
United States
shadnaz.asgari@csulb.edu

Funding Source(s) and
Amounts Provided (by each agency or organization)

Caltrans

$74,928

Total Project Cost

$74,928

Agency ID or Contract Number

Grant No: 65A0533

Start and End Dates

1/1/2015 to 12/31/2015

Brief Description of
Research Project

Truck turn times have a significant impact on the tactical and operational planning for a transportation network.  In particular, the longest cycle time (in contrast to commonly presumed average cycle time) plays a critical role in successful planning of the events in the network.  For example, if average turn time is the only parameter used in planning while truck turn time variance is large, then the schedules need to be revised repeatedly.  Hence, determining accurate turn times is an essential factor in efficient, productive and cost-effective supply chain operations.  There have been several attempts to measure and study truck turn times at the Los Angeles and Long Beach Port terminals.  However, most studies so far relied either on installing expensive equipment on a few select trucks to track them or on using inaccurate and error-prone methods of data collection.  Lack of proper and precise data measurements is an obstacle in developing and implementing appropriate policies with respect to port productivity.

In this project, we propose to obtain accurate truck and port monitoring data at no additional equipment cost.  Our system will utilize the rich sensors of ubiquitous smartphones to track all movements of trucks outside and inside terminals.  It will allow us to measure truck turn times more accurately than before by using GPS, network antenna and inertial sensors of truck drivers' smartphones.  Our algorithms will then analyze collected data to derive real time and detailed models of cargo traffic flow in and around terminals. Our mobile phone application additionally will provide information to drivers as well as port and terminal authorities.  This will ensure the use of our application by port stakeholders and hence in turn allow us to collect the needed data.  This cost-effective and efficiently collected data can be employed to build a comprehensive database of port transportation.

The proposed project has significant potential to be further extended.  Future work on our mobile platform could facilitate easier communication between truck drivers and terminals.  This will likely reduce the number of trouble tickets issued and hence lead to additional productivity.  Our proposed system will ultimately act as a digital hub for truck drivers who access the ports.  It will allow for large scale and accurate truck data collection as well as information dissemination to drivers at no extra cost to stakeholders.

Describe Implementation of Research Outcomes (or why not implemented)

 

Impacts/Benefits of Implementation (actual, not anticipated)

 

Web Links, Reports, Project website

http://www.metrans.org/research-projects/metrans-utc