TrafficView: A Scalable Traffic Monitoring System

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TrafficView A Scalable Traffic Monitoring System

• Tamer Nadeem, Sasan Dashtinezhad, Chunyuan Liao,
  Liviu Iftode

Department of Computer Science University of
Maryland, College Park Now with Rutgers
University
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TrafficView

• Enable drivers to see vehicles in front of their
  cars, farther than they can see, in real-time
• Use vehicle-to-vehicle ad hoc networks

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How TrafficView Works

• Each vehicle has an embedded system
• GPS receiver (location, speed, time)
• Short-range wireless NIC
• On-Board Diagnostics interface (optional)

Receive data from remote vehicle
Local data
Broadcast data
Validate
Non-validated dataset
Validated dataset
Display
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Need for Data Aggregation

• Ad hoc networks of vehicles are dynamic
• Data propagation must be simple
• Send all data in one packet (up to MTU)
• Use data aggregation to put as much information
  as possible in one packet

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How Far Can You See?

• Problem
• How to aggregate data to see vehicles as far as
  possible with acceptable accuracy loss
• Natural Solution
• Aggregate data for vehicles that are close to
  each other
• Perform more aggregation as distance increases

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Outline

• Motivation and Problem Definition
• Data Representation
• Aggregation Algorithms
• Evaluation
• Conclusions and Future Work

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Data Representation

• Vehicles store records
• Vehicle ID (ID), position (POS), speed (SPD),
  broadcast time (BT)
• Broadcast time the time at which the originating
  vehicle sent out the record
• An aggregated record contains more than one ID

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Aggregated Records

• Having n records

• Calculate the aggregated records fields

POS and SPD are weighted averages.
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Aggregation Algorithms

• Ratio-based
• Cost-based

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Ratio-based Aggregation
Aggregation ratio inverse of the number of
records that would be aggregated in one record
Portion value amount of the remaining space in
the broadcast message
1. Calculate region boundaries
2. Calculate merge thresholds
3. In each region, each two consecutive records
that are closer than the merge threshold, are
merged
Current Vehicle
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Cost-based Algorithm

• The Ratio-based algorithm selects the records to
  be aggregated blindly!
• Assign a cost to merging two records, select
  records corresponding to lowest cost
• Cost function
• High cost to close vehicles
• Minimize error due to merging records
• Minimize number of cars in merged records

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Information Aging

• Problem
• Vehicles move and change speed
• Records can be out-of-date
• Received information might be invalid
• Solution
• Delete record if no information about that
  vehicle is received in a while
• Compute expected delay for each record received
• Store record only if
• actual delay expected delay lt
  threshold

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Evaluation

• Metrics
• Road Scenarios
• Simulation Results

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Metrics

• Visibility
• Average distance ahead about which a vehicle has
  information
• Accuracy
• Average position error introduced due to
  aggregation
• Knowledge Percentage
• Average percentage of vehicles in each region
  ahead about which a vehicle has information

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Traffic Model

• Evenly distributed entries and exits
• Random constant speed during time intervals
• Changing lanes randomly

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Simulations

• NS-2 simulations
• 802.11b with 11Mbps bandwidth
• transmission range of 250m
• MTU 2312 bytes
• 15,000m road, 4 lanes
• 300s duration of simulation
• Algorithms
• Ratio-based, Cost-based, Non-aggregation, and
  Brute-force Cost-based
• Selected parameters using preliminary simulations

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Scenarios
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Effect of Road Parameterson Visibility (1)
Cost-based Aggregation
Ratio-based Aggregation
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Effect of Road Parameterson Visibility (2)
Brute-force Cost-based
Non-aggregation
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Visibility (High-density Highway)
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Accuracy (High-density Highway)
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Knowledge Percentage(High-density Highway)
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What We Learned

• Intuitively, cost-based algorithm appeared to be
  a better choice
• Cost-based algorithm is only marginally better
  for relatively closer distances
• Ratio-based algorithm is better for farther away
  distances and is more flexible

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Conclusions

• TrafficeView provides drivers with real-time view
  of vehicles in front of their cars
• Designed and evaluated two aggregation algorithms
  using realistic road scenarios
• Ratio-based algorithm is a good algorithm
• Good visibility and small position error

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Future Work

• Working on prototype implementation
• Linear programming model to automatically
  calculate the aggregation parameters
• Privacy and Trust

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Thank You!
http//www.cs.umd.edu/nadeem/projects/trafficview