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Application of Computer Simulation in Traffic Analysis

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90% crashes attributed to driver error rather than failures in the ... Compare to ... Epochs in which the index car was overtaken were more frequent ... – PowerPoint PPT presentation

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Title: Application of Computer Simulation in Traffic Analysis


1
Application of Computer Simulation in Traffic
Analysis
  • Presented By Lei Huang

2
Motor Vehicle is a Mixed Blessing
  • During a average day in U.S., about 100 people
    step into a vehicle and do not emerge alive
  • gt90 crashes attributed to driver error rather
    than failures in the vehicle or roadway
  • The most important factor in driver error is
    alcohol (40)
  • A better understanding of other errors might
    allow people travel at lower risk

3
Inappropriate Lane Changing May Have Substantial
Risks
  • It causes the individual to straddle traffic
    flows and be exposed to two streams of vehicles
  • It requires the driver to make rapid judgments
    about sufficient spacing
  • It increases the hazard related to other vehicles
    approaching along the drivers blind spot
  • Is disrupts the traffic pattern for following
    vehicles

4
Question?
  • Whether people can accurately judge if they are
    in a lane that is slower than the other lane on a
    congested roadway?
  • Survey indicate most people expect to spend equal
    amounts of time passing and being overtaken
  • A videotape obtained from field observations
    confirmed peoples mistaken impressions of speed
    on a congested roadway

5
Answer
  • Since testing on real drivers seamed to be
    unsafe, unethical and expensive, how do we find
    out the answer to above question?
  • Answer Computer Simulation

6
Method Individual Vehicle Perspective
  • A vehicle would accelerate if it was traveling
    slower than its target speed and no other vehicle
    ahead was within the minimum headway distance
  • A vehicle would decelerate if another vehicle was
    ahead and within the minimum headway distance
  • A vehicle would maintain a constant speed if it
    achieved target speed and no other vehicle ahead
    was too close

7
Method Individual Vehicle Perspective
  • The target speed was 63 mi/h (100km/h) for all
    vehicles
  • The acceleration and deceleration was set uniform
    for all vehicles
  • The minimum headway distance (d) was a function
    of velocity (v), where
  • d (v2/100) 1
  • thus a vehicle traveling at 100km/h requires a
    minimum headway of 101 m

8
Aggregate Traffic Characteristics
  • The number of vehicles and amount of available
    roadway was stable, thus conditions which
    provided little total roadway for large numbers
    of vehicles resulted in substantial congestion
  • The completely realistic simulation of a single
    lane of traffic was impossible because vehicles
    can differ in target speed, headway tolerance,
    acceleration, deceleration, starting position,
    current velocity.

9
Aggregate Traffic Characteristics
  • The model was designed with a few initial sources
    of randomness, then gradually made more complex
  • The baseline condition assumed that all vehicles
    has identical performance and starting at zero
    velocity
  • The starting position (spacing between vehicles)
    was generated by normal distribution

10
Aggregate Traffic Characteristics
  • The second lane was established with
    characteristics identical to the index lane
  • By applying a different starting seed to the
    random generator, the two lanes could follow
    somewhat different patterns yet obtain the same
    average speed

11
Psychological and Statistical Issues
  • People tend to judge their speed by assessing
    their speed relative to others in the next lane
  • Passing epoch
  • when the index driver started behind and ended
    ahead of one or more drivers in the other lane
    after a one-second interval
  • Being overtaken epoch
  • when the index driver started ahead and ended
    behind one or more drivers in the other lane
    after a one-second interval
  • Drivers prefer passing rather than being overtaken

12
Speed and Position of Vehicle in Single Lane
  • Long intervals of slow velocity and short bursts
    of high velocity
  • Strong and correlation between a vehicles
    current speed and spacing relative to vehicle
    ahead

13
Compare to Vehicle in Next Lane
  • Substantial variation in relative speed and
    relative position was observed even over a short
    period of time

14
Summary of Finding
  • Epochs in which the index car was overtaken were
    more frequent than epochs in which the index care
    was passing(43 vs. 33, ratio 130)
  • However, the total number of overtakes equaled
    the total number of passes
  • The baseline condition indicated that the next
    line might mistakenly appear faster than the
    drivers current line

15
Reasons for the mistaken impression
  • A driver on a congested roadway can pass many
    vehicles in a brief interval, whereas it takes
    much more time for the driver to be overtaken by
    the same number of vehicles
  • Although every driver should normally expect to
    spend more time going slower than going faster,
    people usually expect that the amount of good
    times should balance the amount of bad times

16
Other factors
  • Drivers direct more attention ahead than behind
    consequently, passed vehicle turn invisible
    whereas overtake vehicle stay conspicuous
  • Glances at the next lane may be more frequent
    when drivers are relatively idle
  • Human psychology may make losses appear more
    salient than the corresponding gains

17
Less Congested Roadway
  • Lesser congestion leads to higher speed, fewer
    passing and overtaking epochs, and smaller
    asymmetry

18
Conclusion
  • Results from computer simulation suggested a
    roadway illusion namely, that the next lane on
    a congested roadway appears to be moving faster
    than the drivers current lane even if both lanes
    have the same average speed
  • Naïve attempts to rush may be misguided without a
    careful understanding of queuing theory
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