Title: Multiagent Traffic Management: A Reservation-Based Intersection Control Mechanism
1Multiagent Traffic Management A
Reservation-Based Intersection Control Mechanism
- Roberto Valenti
- Felix Hageloh
- Zhiwei Zhan
2Overview
- Introduction
- The Model
- The Metric
- Traffic Light Theory
- The Simulator
- Intersection Control Policies
- Coffee break .. ?
- Empirical Results
- Discussion and Conclusion
- Questions
3Introduction
- Problem for future Traffic Congestion
- Lose productivity
- decrease standard of living in urban settings
- a lot more.
4Introduction
- Current Solutions
- Overpass
- Drawback Expensive, Only worth the cost at the
most congested intersections - 2. Traffic lights
- Drawback Inefficient, requiring cars to remain
stopped even when no cars are present on the
intersection road. - Do we have better solution?
5Introduction
- MASReservation-Based System!
- Every individual car is an independent autonomous
agent - There will be mechanisms for coordination among
independent agents behaviors - Goal maximize the efficiency of moving cars
through intersections with minimal centralized
infrastructure
6The Model of Intersection traffic
- Assumptions of intersection traffic
- Cars can not turn
- All cars begin with the same speed
- Every car is always trying to travel at the speed
limit - Every car is capable of reaching the speed limit
on any roads - --But how do we measure which
intersection is better?
7The Metric
- We need metrics
- 1. Safety
- It should be the primary concern
- Considered to be a prerequisite in this paper
- Efficiency
- throughput
- delay
8The Metric
- Throughput
- Its the amount of traffic that can be handled by
an intersection - hard to measure precisely
- make qualitative claims regarding throughput of
three different systems (discussed later)
9The Metric
- Delay--definition
- Its the primary metric considered
- It stands for the effect that the intersection
has on the overall journey of a vehicle - What the system want?
- The average delay should be not bad
- The worst delay should be not too bad
10The Metric
- DelayTwo types
- 1. Average Delay
-
- 2. Maximum Delay
-
- C set of all vehicles every car in
C - t(i) actual arriving time t0(i) optimal
arriving time
11Traffic Light Theory
- For overpass, the average and maximum delay are
both zero - For traffic light, things are more complicated
- the timing of the lights
- how many cars are on the road
- what are the velocities of the other cars
12Traffic Light Theory
- To analyze this model, we need assumptions
- Cars traveling in the same direction do not
interact with one another - 2. Cars that have to decelerate due to a red
light reach the intersection at full speed
precisely when the light turns green again
13Traffic Light Theory
- The parameters for the formulas
- P the period of the traffic light
- the fraction of the lights period that
the light spends on green in one direction - Two constraints
- Pgt0 and 0lt lt1
14Traffic Light Theory
- The delay for one car is dependent only on
- P and
- max delay (1- )P min delay 0
- the average delay is
- the total expected delay is
15Whats next?
- The Simulator
- Intersection Control Policies
16The Simulator
17The Simulator Dimensions
- Simulation values are constant on all the
experiments - Number of lanes
- Probabilities of a Vehicle to spawn on each
direction - Area of 400X400 m.
- Lanes are 3.5 m wide.
- Vehicles are 2 m wide by 4 m long.
18The Simulator Rules
- Vehicles are randomly spawned with a predefined
probability. - Vehicles are placed uniformly at random in one of
the lanes traveling in that direction. - Collision?
- Overflow?
- The driver of each vehicle is given the distance
to the car in front of it. - Cameras
- Range-Finders
19The Simulator Rules
- Each driver then takes an action based on this
information - ACCELERATE (increase velocity by 3 m/s2)
- DECELERATE (decrease velocity by 15 m/s2)
- COAST (maintain current velocity).
- All spawned vehicles are traveling at the speed
limit. - Speed Invariant 0 lt speed lt top speed.
- Vehicles position and velocity are updated
according to the drivers actions. - Vehicles which have left the domain of the
simulator are removed from the simulation. - Each vehicle tracks its own delay.
20The Simulator Driver Agents
- Agents and Simulator are Independent
- Pseudo code
- COAST
- If speed lt speed limit, ACCELERATE
- If less than 1 second or 1 meter behind the
vehicle in front and speed gt 0, DECELERATE - If not through the intersection already, interact
with the intersection as specified separately for
each Intersection Control Policy.
21Intersection Control Policies
- Three Intersection Control Policies (ICP)
- Overpass
- Traffic Light
- Reservation System
22ICP Overpass
- Is the simplest
- lets vehicles through all the time.
- No explicit third dimension in the simulator
- vehicles traveling in orthogonal directions are
allowed to travel to pass through one another. - The overpass is an optimal solution
- Not actually an intersection
Demo
23ICP Traffic light
- Three Parameters
- the period of the light system
- the time between green lights in which all four
directions lights are red (in fraction) - the time for which the North/South lights are
green (in fraction) - North and South, East and West are always
identical - Yellow lights are not necessary
Demo
24ICP Traffic light
- The interaction is sequential
- The driver calculates when it will reach the
traffic light given its current velocity. - The driver sends a message to the intersection
informing it of the time at which the driver
expects to arrive. - The intersection responds with the range of times
during or after the time specified by the driver,
at which the lights will be green. - The driver can make any adjustments to ensure
that the vehicle enters the intersection with
green lights.
Demo
25ICP Reservation System
- The intersection is divided into an n x n grid of
reservation tiles, where n is called the
granularity of the reservation system. - The reservation system allows the driver agents
to call ahead and reserve the spaces they will
need. - Each tile can be reserved by one car per time
step. - To use the reservation system, the car sends a
message containing several parameters.
26ICP Reservation System
- Parameters
- The time the vehicle will arrive
- The speed at which the vehicle will arrive
- The direction the vehicle will be facing when it
arrives - The vehicles maximum velocity
- The vehicles maximum and minimum acceleration
- The vehicles length and width
27ICP Reservation System
- If the driver has not yet made a reservation, it
sends the intersection a message. - If the intersection accepts the request, the
driver agent notes that a reservation has been
made (parameters are now fixed) - If the Intersection rejects the request, the
driver decelerates and tries again at the next
time step. - If the driver has made a reservation, it
determines whether or not it can keep the
reservation. - If it determines that it can not meet the
reservation, it cancels the reservation and the
reservation-making process begins again.
Demo
28Whats next?
- Coffee break ? (Whats the time?)
- Empirical Results
- Discussion
- Conclusion
- Questions
29Coffee break
30Empirical Results
- Results obtained using the simulator
- The three systems are compared by looking at the
average and maximum delays
31Results Overpass
- Obviously the most ideal case
- Normally vehicles experience 0 delay
- Delays only occur if vehicles top speed is below
the speed limit or if traffic is spawned faster
than it can move through the intersection - The overpass system gives the lower bound
32Results Traffic Light
- Results are obtained for different periods and
different spawning probabilities - In general we can say that for light traffic,
short periods are better and for heavy traffic,
long periods - Traffic light intersections become overloaded
very quickly
33Results Traffic light
- 1 lane in each direction and a 1 tile reservation
system
34Results Reservation System
- The graph shows that the reservation system
performs much better - Doesnt break down until a much higher traffic
load - Before that, the performance is close to the
overpass system - On overloading the performance depends on many
random factors, hence the jagged line
35Results Reservation System - Scalability
- The reservation system outperforms the traffic
light system, but does it scale when increasing
the number of lanes?
traffic light period of 20 seconds run for
1,000,000 steps spawning probability 0.001.
36Results Reservation System - Granularity
- Main parameter to set is the granularity of the
reservation system - For the first example increasing the granularity
from 1 to 2 has a big impact
Each data point represents 1,000,000 steps of
simulation
37Results Reservation System - Granularity
Measured for 2 lanes in each direction and a
spawning probability of 0.001.
38Results Reservation System - Granularity
- Apparently odd numbered granularities give worse
performances - The problem is deadlocks. They happen when two
cars traveling in opposite directions compete for
the same tile - Hence the granularity should always be at least
be equal to the number of lanes or a multiple of
it
Demo
39Results Reservation System - Granularity
- Increasing the granularity increases the
performance - However, memory requirements and computational
cost rise as a square of the granularity
Average delays over at least 500,000 steps.
40Discussion The Real World
- Can this reservation system easily be applied to
the real world? - Margin of error is too small for human drivers
- Margin can be increased for human drivers (also
in mixed scenarios) - However, for a large number of human drivers the
system probably performs almost the same as
traffic lights
41Discussion Related work
- Most other studies on intersection control focus
on improving current control systems, i.e.
traffic lights. A similar system was by Kolodko
and Vlacic and has been successfully implemented
using autonomous vehicles
42Conclusion
- Two major outcomes of this research
- An intersection simulator with a precise metric
for measuring intersection control performances - A new type of intersection control policy that
outperforms traffic light systems dramatically - However, many limiting assumptions were made on
the current research
43Questions