motion planning for multiple autonomous vehicles: chapter 7b - congestion avoidance in city traffic

7/23/2019 Motion Planning for Multiple Autonomous Vehicles: Chapter 7b - Congestion Avoidance in City Traffic

http://slidepdf.com/reader/full/motion-planning-for-multiple-autonomous-vehicles-chapter-7b-congestion-avoidance 1/18

School of Systems, Engineering, University of rkala.99k.orgApril, 2013

Motion Planning for Mltiple

Atonomos !ehicles

Rahl

"ala

#ongestionAvoidance in #ity

$ra%cPresentation of paper& R' "ala, "' (ar)ic* +201- #ongestion

Avoidance in #ity $ra%c' Journal of Advanced Transportation,./+.-& 1/'



$ra%c

Motion Planning for Mltiple Atonomos !ehicles

"ey #ontritions

• Proposing city trac as a scenario tostdy tra%c congestion'

• Proposing the importance of considering

trac lights in decision ma*ingregarding rotes'

• Proposing a simple routing algorithm that eliminates the high density of tra%cand hence minimies congestion'

• Stressing frequent short term re- planning of the vehicle in place of long

term +complete- infre4ent re5planning'r*ala'//*'org




Assmption

• !ehicles have very diverse speeds

• 6on5recrrent tra%c +does not follo)

historical tra%c patterns-

• City tra%c scenario

Objective

• Minimie non5recrrent congestion

r*ala'//*'org




#ity $ra%c Scenario

r*ala'//*'org

S.No.

Characteristic

Highway Trafc City Trafc

1' 7nfrastrctre 8ess nmer oflong length roads

Many short lengthroads (alternativeroads) intercepting

each other. Verycop!tationallye"pensive ro!ting.

2' !ehicleEmergence

9istant entry: e;itpoints' 6e)vehicles do not

invalidateanticipated plans'

Many entry# e"itpoints at road ends#$etween roads.

%eca!se o& newvehicles' anticipationnot possi$le.

3' Planning<re4ency

=igh anticipationfavors long termplanning

ow anticipationinvalidates long terplans




Roting Systems

r*ala'//*'org

(

i i t

a t i o n

s




Planning =ypothesis

Mae frequent e!ective shortterm plans

or, plan part of the rote reglarly as the vehiclemoves

• <re4ent > #onstantly adapt to changes

• Short $erm > 8imit comptational re4irement

r*ala'//*'org


http://slidepdf.com/reader/full/motion-planning-for-multiple-autonomous-vehicles-chapter-7b-congestion-avoidance 7/18Motion Planning for Mltiple Atonomos !ehicles

$ra%c Simlation

• riving Speed "ntelligent #river Model +standard model, converts

vehicle separations into speed-

• ane Change #hoose lane )ith ma;imie Time to Collision +if any in

the crrent-

Stay on the leftmost lane +if crrently close to

ma;imm speed- $his allo)s other vehicles to overta*e +from the right-

r*ala'//*'org



Single 8ane ?verta*e

• !ehicles vary a lot in speeds and hence everyoverta*e is important

• !ehicle is allo)ed to move on the $rong side,overtae the slo)er vehicle and return to itslane

• !ehicle are pro@ected +)ith acceleration for theoverta*ing vehicle-'

• ?verta*e shold e feasile as per pro@ections)ith enogh separations

• ?ther vehicles may additionally cooperate postinitiation of single lane overta*e, to overcomencertainties

r*ala'//*'org



Single 8ane ?verta*e

r*ala'//*'org

A B

C

A B

C

B

A C

AB

C

(a) A checks feasibility to

overtake B while C is coming

from opposite end

Arrows indicate separation checks. Since A and C are moving in opposite direction,

needed separation is much larger.

(b) Projected positions of

vehicles when A is expected to

lie comfortably ahead of B

(c) Completion of overtake.



!ehicle Roting

H y p

o t h e s i s

r*ala'//*'org



!ehicle Roting

r*ala'//*'org

8et&Arro)s denote roads8ine (idths denote crrent tra%c density=eristic costs to goal may replace actal costs

after threshold

Sorce oal

*o!te +, 8ong, Moderate density, more tra%c lights

*o!te -, Short, =igh tra%c density, less tra%clights

*o!te , /re&era$le 8ong, 8o) tra%c density, less

tra%c lights



!ehicle Roting

r*ala'//*'org

maxHistoricalSelected

Path

Current

position

Current

position

Selected

Path

maxHistoricalSelected

PathCurrent

positionOrigin

Goal

(a) From current position

the vehicle plans towards

the goal and after

maxHistorical cost stops

the current search and

moves by the best path

(b) fter reaching the next

crossing! change of plan

takes place as per the new

information available

(c) "ehicle finally reaches

a point from where the

goal is near



#omparisons

r*ala'//*'org

S.No.

Method 0$1ective# 2re3!ency

1' ?ptimistic +static- Minimie e;pected travel time assminghighest speeds

2' Pessimistic +static- Minimie e;pected travel time assming

highest speeds, prefer roads )ith morelanes

3' $ra%c Messaging#hannel +$M#, static-

$rac* vehicles to get immediate travelspeeds +adapted for diverse speedvehicles-, planned for only at the start

.' $M# +dynamic- S' 6o' 3, plan at every crossing

' 9ensity +dynamic- Minimie e;pected travel time yconsidering crrent tra%c density, planat every crossing

B' $M# )ith tra%c lights+dynamic-

S' 6o' ., e;pected time )aiting at thecrossing added

4. ensity with trafc /roposed ethod' S. No. ' e"pected



Reslts

r*ala'//*'org

!" ! #" # $" $ %" %"

!"

!

#"

#verage #ime of Completion of $ourney

optimistic

pressimistic

&'C static

&'C d(namic

&'C with tra))ic lights

densit(

densit( with tra))iclights

%umber of vehicles per second

verage #ime of completion of journey (minutes)



Reslts

r*ala'//*'org

!" ! #" # $" $ %" %"

".

!

!.

#

#.

$

$.

%

%. verage &istance #ravelled

optimistic

pressimistic

&'C static

&'C d(namic

&'C with tra))iclights

densit(

densit( withtra))ic lights


verage &istance #ravelled (miles)



Reslts

r*ala'//*'org

!" ! #" # $" $ %" %"

#

%

*

+

!"

!#

!%

!*

!+

#"verage 'peed

optimistic

pressimistic

&'C static

&'C d(namic

&'C with tra))iclights

densit(

densit( with tra))iclights


verage 'peed (mileshr)



Reslts

r*ala'//*'org

"

!"

!

#"

#

verage #ime of Completion of $ourney

with overtaking

without overtaking


verage #ime of completion of journey (minutes)

*es!lts with and witho!t single lane

overtaking



Motion Planning for Mltiple Atonomos !ehicles r*ala //* org

$han* Co

• 5cknowledgeents,

• #ommon)ealth Scholarship#ommission in the United "ingdom

• Dritish #oncil

motion planning for multiple autonomous vehicles: chapter 7b - congestion avoidance in city traffic

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