University of Central Florida Transportation Engineering

1. University of Central FloridaTransportation Engineering Intermodal Freight Transportation Research *Project funding provided by FDOT

2. Role of Academia Enthusiastic Talented Students Professors with diverse backgrounds Extensive resources in Universities Bridge between public and private Unbiased analysis Information dissemination through education

3. Modeling Heavy Truck Traffic Generated by Florida Seaports Haitham Al-Deek, Ph.D., P.E. Jack Klodzinski, Ph.D. Determine Truck Volumes From Vessel Freight Data Analyze Freight Movements Determine Routes Trucks Use Alternative Route Choice Evaluate Port Transportation Security.

4. Benefits From Modeling Optimization (scheduling) Utilize knowledge of traffic patterns Tracking Economize daily trips Security Efficiency in processing Safety Database utilization (route choice).

5. UCF Freight Data Inventory Daily truck counts (1660+ days) Vessel Records for 6 Major Florida Ports Daily vessel records (up to 10 years) Monthly historical vessel records (up to 10 years) Site specific information Commodity types which are top imports/exports Access roads THIS RESEARCH WAS BASED HEAVILY ON FIELD OBSERVATIONS AND ACTUAL FIELD DATA COLLECTED AND ANALYZED. Truck data: 4 ports, 23 count stations, 1361 days of classification counts (summarized the # of days collected at each of the 4 ports at each of the locations, a location may include more than one count station but does not duplicate the # of days). Note: Tampa-691 days + Ph3 75 days, Everg-440 days, Palm B-106 days, Jacks-125 days, Canav-96 days. (Miami also added to this count-113 days) Vessel data: 4 ports and almost 10 years of Vessel data (average 48,000 records per year) Miami data: 73,000+ gate passes entered, 113 days of truck count records THIS RESEARCH WAS BASED HEAVILY ON FIELD OBSERVATIONS AND ACTUAL FIELD DATA COLLECTED AND ANALYZED. Truck data: 4 ports, 23 count stations, 1361 days of classification counts (summarized the # of days collected at each of the 4 ports at each of the locations, a location may include more than one count station but does not duplicate the # of days). Note: Tampa-691 days + Ph3 75 days, Everg-440 days, Palm B-106 days, Jacks-125 days, Canav-96 days. (Miami also added to this count-113 days) Vessel data: 4 ports and almost 10 years of Vessel data (average 48,000 records per year) Miami data: 73,000+ gate passes entered, 113 days of truck count records

6. Modeling Heavy Truck Traffic Generated by Florida Seaports At the 95% confidence level, ANN performed with better accuracy when compared to the previous regression modeling approach.At the 95% confidence level, ANN performed with better accuracy when compared to the previous regression modeling approach.

8. Port of Miami

9. Port of Miami Operations

10. Port of Tampa

11. Port of Tampa Road Network Port of Tampa includes: Hooker�s Point, Pendola Point, Port Sutton The reason for the selection of these links is because they can accommodate high truck volumes leaving and entering the Tampa Port cordon. Most of the links are interstate highways or state roads that have high capacity due to their geometric features. Lower capacity roads were chosen because they link the major roads in the network (e.g. Madison Avenue links SR 41 and SR 301). Major roads located in this area that are considered main routes for truck volumes at the port are I-4, I-75, I-275, SR 41, SR 618 and SR 60. The network has 8 links on freeways and 22 links on either state roads or urban streets. Three of these 8 links are on a toll road (SR 618). The network is bounded by SR 301, to the East, I-4 & I-275 to the north and I-75 is located to the south east of the network. I-275 is carrying most of the freight trucks that are headed north (or coming from north). I-275 is the only Interstate that is directly connected to Hookers Point (through I-4) and headed north. On the other hand, freight trucks that are headed north (or coming from north) can use I-75 for Pendola Point through Madison Avenue. The selected nodes represent intersections or any significant changes in a link (I.e. reduction or increase in the number of lanes)Port of Tampa includes: Hooker�s Point, Pendola Point, Port Sutton The reason for the selection of these links is because they can accommodate high truck volumes leaving and entering the Tampa Port cordon. Most of the links are interstate highways or state roads that have high capacity due to their geometric features. Lower capacity roads were chosen because they link the major roads in the network (e.g. Madison Avenue links SR 41 and SR 301). Major roads located in this area that are considered main routes for truck volumes at the port are I-4, I-75, I-275, SR 41, SR 618 and SR 60. The network has 8 links on freeways and 22 links on either state roads or urban streets. Three of these 8 links are on a toll road (SR 618). The network is bounded by SR 301, to the East, I-4 & I-275 to the north and I-75 is located to the south east of the network. I-275 is carrying most of the freight trucks that are headed north (or coming from north). I-275 is the only Interstate that is directly connected to Hookers Point (through I-4) and headed north. On the other hand, freight trucks that are headed north (or coming from north) can use I-75 for Pendola Point through Madison Avenue. The selected nodes represent intersections or any significant changes in a link (I.e. reduction or increase in the number of lanes)

12. Port Canaveral(Daily Truck Counts for ANN Model) Define initial highway network Develop ANN model utilizing field truck counts and vessel freight data 96 days of data collection (Sept 20 2001 to Dec 24 2001), 53 weekdays 21 weekends comprehensive outbound, 56 weekdays 22 weekends comprehensive inbound Forecast truck counts using ANN model Model Port Canaveral network and validate at the 95% confidence level Use ANN model truck volume forecast results to forecast truck volumes on networkDefine initial highway network Develop ANN model utilizing field truck counts and vessel freight data 96 days of data collection (Sept 20 2001 to Dec 24 2001), 53 weekdays 21 weekends comprehensive outbound, 56 weekdays 22 weekends comprehensive inbound Forecast truck counts using ANN model Model Port Canaveral network and validate at the 95% confidence level Use ANN model truck volume forecast results to forecast truck volumes on network

13. Port Canaveral Network(Peak Hour Port Generated Trucks) 352 average inbound, 316 average outbound Define initial highway network Develop ANN model utilizing field truck counts and vessel freight data 96 days of data collection (Sept 20 2001 to Dec 24 2001), 53 weekdays 21 weekends comprehensive outbound, 56 weekdays 22 weekends comprehensive inbound Forecast truck counts using ANN model Model Port Canaveral network and validate at the 95% confidence level Use ANN model truck volume forecast results to forecast truck volumes on network352 average inbound, 316 average outbound Define initial highway network Develop ANN model utilizing field truck counts and vessel freight data 96 days of data collection (Sept 20 2001 to Dec 24 2001), 53 weekdays 21 weekends comprehensive outbound, 56 weekdays 22 weekends comprehensive inbound Forecast truck counts using ANN model Model Port Canaveral network and validate at the 95% confidence level Use ANN model truck volume forecast results to forecast truck volumes on network

14. Port of Palm Beach

15. Port Everglades

16. Port of Jacksonville

17. ANN Model accurately determines truck volumes generated by vessel freight activity ANN Model output applications: Input to network models using seaports as special generators Determine where port transportation infrastructure improvements are needed including implementing new security measures. Conclusions

18. VISSIM network model accurately assigns port generated traffic/trucks to a defined network Network model applications: ITS applications such as ATIS Route alternatives Incident management. Conclusions

19. Port Security Investigate the application to infrastructure modifications for port security Modify for direct application to specific terminals and freight commodity types Use model output as input for simulation models to test new security enhancements Security Applications

20. TPSIM Applications for Seaport Security Security Gate Operations Use TPSIM to evaluate the effects and efficiency of new clearance procedures on customer processing time.

21. Freight Security Track containerized freight on identified freight highway corridors Estimate possible stolen freight destinations (Fax Alert Program) Determine and model existing and alternative freight transportation routes Evaluate reliability of Florida�s highway infrastructure to operate during times of national crisis. Security Applications

22. Origin/Destination of trucks statewide Determination of what routes are used by trucks transporting freight generated by port vessel traffic. Provides possible freight theft corridors (Fax Alert Program). Accomplish this by: GPS tracking Database information Security Applications

23. Security Applications(use of GPS for tracking)