Projected Arrival Time Michael Pao Michael Smeets Li-Ren Zhou Abstract The Projected Arrival Time...
-
Upload
juliana-urry -
Category
Documents
-
view
213 -
download
0
Transcript of Projected Arrival Time Michael Pao Michael Smeets Li-Ren Zhou Abstract The Projected Arrival Time...
Projected Projected Arrival TimeArrival Time
Michael PaoMichael PaoMichael SmeetsMichael Smeets
Li-Ren ZhouLi-Ren Zhou
AbstractAbstractThe Projected Arrival Time (PAT) system uses the Global Positioning System (GPS) to provide accurate, real-time arrival estimates to users of a bus system. PennBus West was used for purposes of evaluating the project. Each bus carries an onboard GPS unit which transmits data to a central server running the Java 2 Platform, Enterprise Edition (J2EE) with Enterprise JavaBeans (EJB) technology. On the backend, positioning and velocity data are combined to predict arrival times, which users call via a webpage.
The PAT system adjusts to variations in weather and traffic patterns. However, conditions do arise which severely hamper the ability of buses to run on schedule, such as extreme weather and breakdown. Despite its limitations, the system is reliable to the point where it can be deployed commercially as a trustworthy convenience.
Advisors:Advisors:Siddharth DeliwalaSiddharth Deliwala
Philip FarnumPhilip Farnum
Demonstrations:Demonstrations:April 21April 21stst, 2005, 2005
RCA Lab, 1:30 – 3:30 PMRCA Lab, 1:30 – 3:30 PM
Rayming TN – 202 GPS Receiver
HP iPAQ 3815
Samsung SGH-E 105 Cell Phone
Server
PAT Website
End User End User End User
System OverviewSystem Overview
User InterfaceUser Interface
The onboard hardware components consist of the GPS receiver, the iPAQ and a mobile-phone. The position and speed of the bus are recorded on the iPAQ via the Rayming GPS Receiver. This data is then transmitted to the server over a mobile-phone connection.
On the server side, the speed and position data are then processed by the PAT Algorithm to produce a projected time of arrival. The PAT and position data are relayed to the user, along with a map generated by MapQuest.
Department of Electrical and Systems and EngineeringDepartment of Electrical and Systems and Engineering
Prediction Error vs. Zone Distance of the PAT System
-150
-100
-50
0
50
100
150
200
250
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Zone Distance
Pre
dic
tion
Err
or
(Act
ua
l - E
stim
ate
d)
(s)
Source: 100 Samples per Zone Distance, Collected on 12/7/04, 12/17/04, 1/19/05, 1/26/05, 4/8/05
ResultsResultsThe box plot below illustrates the actual arrival time minus the estimated arrival time of data collected on PennBus West. Upper and lower quartile results satisfy the 120 second threshold requirement set at the beginning of the project. Moreover, there is an upward skew, i.e. actual arrival times lagged estimated times. This was purposely integrated into the algorithm, as it is preferable for the end user to be slightly early than to miss the bus altogether.
A web-based graphical user interface empowers users to simultaneously track a bus’s real-time location and projected arrival time. This feature also allows the user to intuitively grasp if the bus is experiencing operating problems or detect system malfunction.
(Left) Onboard hardware: receiver, iPAQ, null-modem and mobile-phone(Right) PennBus West on break
Software ArchitectureSoftware Architecture
GPS Data Event
Add GPS String to Queue
New Queue Item?
Connect to Server?
Attempt Reconnect
Transmit GPS String
Poll For Data
Parse GPS Data
Determine Zone
Insert Data
Wait For New Connection
Create New Thread
Insert Data Into DB
Retrieve DB Information
DB
Bus Thread
Interface
Data Access Bean
Server
Shared Object Yes
No
No
YesTCP/IP
PDA
PAT AlgorithmPAT AlgorithmPennBus West serves West Philadelphia between the intersections of 33rd and Walnut and 48th and Baltimore. This route has been divided into 28 regions. Distance between the bus and desired stop is calculated by summing the distances between the current regions of the vehicle and desired stop. Arrival time is projected by dividing distance by the average velocity of the last 120 samples, adjusted by a scaling factor based on the current position of the bus.