On November 24, USC news featured an article titled “Big data offers a new look at Expo Line” that highlights the success of Expo Line in attracting public transportation riders towards reducing the traffic congestion. This study is conducted based on ADMS project – a big data framework for transportation systems -   developed by IMSC.

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ADMS Tables explanations

Tuesday, 13 October 2015 13:28
HIGHWAY_CONGESTION_CONFIG

The explanations for columns in  HIGHWAY_CONGESTION_CONFIG table:
 
CONFIG_ID                                        
A common Id that shows last active sensors on freeways.  
 
AGENCY                                                
ID of a transit agency that reports for the specific sensor. In fact the city has partitioned tos some parts and every part is reported by an agency. 
 
CITY                                                        
The city that sensor is located. (right now it's null in our databse)
 
DATE_AND_TIME                             
The time that we have received this set of configs (config_id). 
 
LINK_ID                                                
This is Sensor_id and it's uniq for every sensor.
 
LINK_TYPE                                           
It shows the general type of sensor (example values: highway, arterial). In this table all values are 'highways'. 
 
ONSTREET                                            
The freeway name that sensor has located.
 
FROMSTREET                                      
Nearest exit to location of this sensor.
 
TOSTREET                                            
This field is useful for arterial sensors. For highway sensors this field will be null all the time. 
 
START_LAT_LONG                           
It's an SDO_Geometry object that stores Lattitude and Longitude of sensor.
 
DIRECTION                                          
In which direction the sensor has located. (0, 1, 2 and 3 for north, south, east and west)
 
POSTMILE                                            
It shows the distance between sensor and begining of the highway in mile. This value determined for every agency separately. It means this value is defined for thay part of the highway that located in the specific partition based on the agency field. 
 
AFFECTED_NUMBEROF_LANES
It shows the lane number that sensor is located. Numbers start from 1 and starts from speed lane.
 
The table structure is:
 

HIGHWAY_CONGESTION_CONFIG

 

CONFIG_ID

NUMBER(10,0)

AGENCY

VARCHAR2(50 BYTE)

CITY

VARCHAR2(50 BYTE)

DATE_AND_TIME

DATE

LINK_ID

NUMBER(10,0)

LINK_TYPE

VARCHAR2(20 BYTE)

ONSTREET

VARCHAR2(50 BYTE)

FROMSTREET

VARCHAR2(50 BYTE)

TOSTREET

VARCHAR2(50 BYTE)

START_LAT_LONG

SDO_GEOMETRY

DIRECTION

VARCHAR2(20 BYTE)

POSTMILE

NUMBER(10,2)

AFFECTED_NUMBEROF_LANES

NUMBER(2,0)

 
 
 
HIGHWAY_CONGESTION_DATA

The explanations for columns in  HIGHWAY_CONGESTION_data table:

CONFIG_ID
A common Id that shows last active sensors on freeways.  

AGENCY
ID of a transit agency that reports for the specific sensor. In fact the city has partitioned tos some parts and every part is reported by an agency. 

DATE_AND_TIME
The time that we have received this data. 

LINK_ID
This is Sensor_id and it's uniq for every sensor.

OCCUPANCY
A percentage number that shows the percentage of time period that this sensor was covered by vehicles.

SPEED
Average speed of vehicles those have passed in time period. 

VOLUME
Average Number of vehicles those have passed in time period for all sensors in all lanes across the road (including carpool lane if exist). 

HOVSPEED
Average speed of vehicles those have passed in time period if carpool lane is exist. 

LINK_STATUS
If this value is 'OK', it means that the data is valid. 

The table structure is:

HIGHWAY_CONGESTION_DATA

 

CONFIG_ID

NUMBER(10,0)

AGENCY

VARCHAR2(32 BYTE)

DATE_AND_TIME

DATE

LINK_ID

NUMBER(10,0)

OCCUPANCY

NUMBER(10,0)

SPEED

NUMBER(10,2)

VOLUME

NUMBER(10,2)

HOVSPEED

NUMBER(10,2)

LINK_STATUS

VARCHAR2(10 BYTE)

 

 

On September, 2015, Apps Policy Forum broadcasted an article titled "Navigating Policy with Driver-less cars" by Cyrus Shahabi, director of IMSC. In this article, Cyrus has mentioned about the potencial next steps after replacing drivers with machines.

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USC News report about Driverless Cars

Monday, 24 August 2015 11:12

On August 20, 2015, USC news broadcasted a news titled "Driverless cars will change the world, but how exactly?". In this report, Cyrus Shahabi, director of IMSC, mentioned Los Angeles’s potential to lead the way.

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2015-2016 IMSC Affiliated Faculty

Tuesday, 18 August 2015 16:03

 

Aleksandra Korolova
Assistant Professor, Computer Science
(213) 740-
  Yan Liu
Assistant Professor, Computer Science
(213) 740-4371
     
Gerard Medioni
Professor, Computer Science
(213) 740-6440
  Jongmoo Choi
Senior Research Associate, Computer Science
(213) 740-0991
     
Antonio Ortega
Professor, Electrical Engineering
(213) 740-2320
  Bhaskar Krishnamachari
Associate Professor, Electrical Engineering
(213) 821-2528
     
Patrick Joseph Lynett
Professor, Civil Engineering
(213) 740-3133
   
IMSC won the best paper award in the 2nd IEEE International Workshop on Mobile Multimedia Computing which was held in conjunction with the 2015 IEEE International Conference on Multimedia & Expo (ICME 2015), Turin, Italy.
MediaQ was introduced in the article “ The citizen journalist: How ordinary people are taking control of the news” by Digital Trends. Keith Nelson Jr. introduced MediaQ as an example of  supporting system to help and work with citizen journalism.
The details can be found here.

Retreat 2015 Photo Gallery

Tuesday, 07 April 2015 17:20
 
       

MediaQ in Education

Tuesday, 10 March 2015 17:46

As a part of IMSC’s international collaboration effort in education, MediaQ software has been successfully used in an advanced graduate level course in Germany. Prof. Matthias Renz at the Ludwig-Maximilians-Universität München, Germany, used IMSC’s MediaQ system and software for his graduate level seminar class.

NSF announced six newly funded projects which improve future disaster management using Big Data. This is a part of international effort between US NSF and Japan’s JST (Japan Science and Technology Agency).