August 7, 2003

1
Mike Kofi Okyere Indiana University -
Bloomington Mentors Professor Edward A.
Lee Yang Zhao
Virtual City A Heterogeneous System Model of an
Intelligent Road Navigation System Incorporating
Data Mining Concepts
http//chess.eecs.berkeley.edu

• IRNS Sample Run
• User Input
• Start Location A1
• Destination P20
• The DataReader actor executes the Query Fig. 4
  on the data warehouse and sends result sets to
  GraphBuilder actor
• The GraphBuilder actor converts the received
  result sets into a directed graph (digraph) and
  sends the created digraph to the ShortestPath
  actor
• The ShortestPath actor verifies the validity of
  the input nodes and graph, in order to then
  determine the most efficient route by applying an
  extension of Dijkstras Shortest Path Algorithm

• Disadvantages of Current Route Planners
• Calculation of shortest and fastest route using
  static data
• Road Length
• Constant Travel Speed
• No emphasis is placed on traffic behavior or road
  specifications

Overview Generating satisfactory directions for
route guidance is a challenging task, because the
effectiveness and advantage of particular routes
depend on various road specifications and
characteristics. Current route planners, such as
MapQuest.com, Yahoo.com and Maps.com, present
only limited route options to the drivers of
personal or commercial vehicles. Such directions
are based on static evaluation criteria and do
not consider real-time information related to
traffic conditions, road construction, road
inclination or weather conditions.

• Advantages of the Intelligent Road Navigation
  System
• Calculates routes by taking into account the
  various road characteristics in addition to the
  static data
• Congestion Construction Sites
• Road Inclination Weather Condition
• Enables roadways to operate at peak volume levels
  
• Establishes a self-balancing Traffic System

Static Road Map
Dynamic Road Map
The New Approach The Intelligent Road Navigation
System consists of a dynamic data warehouse that
contains real-time road information, ranging from
road name and length to road inclination and
traffic density. The most efficient route is
calculated by an extension of the Dijkstras
Shortest Path Algorithm to obtain driving
directions that focus on minimizing either travel
time, gasoline usage, driving mileage or a
combination of all.
Figure 3 Showing the Ptolemy II model of the
Intelligent Route Navigation System
SELECT START, END, LENGTH/(SPEEDTrafficFacto
rConstructionFactor)60 AS TrafficTime FROM
Construction INNER JOIN (Traffic INNER JOIN
RoadRules ON Traffic.TrafficTypeID
RoadRules.TRAFFIC) ON Construcion.ConstructionSite
TypeID RoadRules.CONSTRUCTION"
Figure 4 Showing the Query used to find the
shortest travel time between road segments
Dijkstras Shortest Path Algorithm
Shortest Path from (a) to (d) is calculated as
follows Graph G (V, E) V a, b, c, d, E
(a, b, 4), (a, c, 2), (b, c, 3), (b, d, 1),(c,
a, 2), (c, b, 1), (c, d, 5) 1. Init d(a) 0,
d(b) INF., d(c) INF., d(d) INF. 2. 0 a,b
4 4 0 a,c 2 from (a) ? (c) 2 Pick c 3. 2 b,c
3 2 b,d 7 ? (d) 7 Pick b 4. 3 b,d 4
set distance from (a) ? (d) 4 The
algorithm stops, since the shortest path has been
found. Shortest Path (a) ? (c) ? (b) ? (d)
Figure 2 Showing the Fastest Route using
Dynamic Data
Figure 1 - Showing the Fastest Route using a
Static Data
August 7, 2003