agenda item 5 - e-voice.org.uk...2018/02/22 · report of: carolyn dwyer, director of the built...
TRANSCRIPT
Committee: Date:
Local Plans Sub (Planning and Transportation) Committee 22/02/18
Subject: Traffic in the City 2018
Public
Report of: Carolyn Dwyer, Director of the Built Environment
For Information
Summary
This report considers the traffic data gathered in 2017 and examines longer term trends in the Traffic Composition Survey (TCS) dataset.
The City of London TCS has been conducted on average every two years since 1999. They provide an overview of traffic volumes and composition across the City and are used to identify historical trends in the number and types of vehicles using streets in the Square Mile.
In 2017 an additional TCS was undertaken to provide more data to support the development of the City of London Transport Strategy. The new 2017 TCS found that traffic volumes, after dropping significantly from 2014 to 2016, have remained relatively unchanged since.
This year was the first year that pedestrian counts were also conducted at all sites. Over 413,000 pedestrian movements were counted, representing almost two-thirds of all counted movements. Thirteen of the fifteen sites surveyed saw more pedestrian traffic than all other traffic modes combined. Over 59,000 pedestrian movements were recorded ‘at night’ (between 19:00 and 07:00).
Recommendations
Members are asked to note the report.
Main Report
Background 1. This report provides an overview of the findings from the City of London Traffic
Composition Surveys (TCS). These surveys – conducted every two years since1999 – provide details of the number and types of vehicles using the City’sstreets.
2. In 2017 an additional TCS was undertaken. For the first time this includedpedestrian counts, further enhancing the dataset ahead of the development of theCity of London Transport Strategy.
Agenda Item 5
3. Vehicular and pedestrian traffic flows were recorded for a 24-hour period onNovember 16th, 2017 at the following sites:
Site ID Approximate Site Location CC1 New Bridge Street at Tudor Street CC2 New Change at Festival Gardens CC3 Queen Street south of Cheapside CC4 Queen Victoria Street west of Bucklersbury CC5 King William Street at Abchurch Lane CC6 Gracechurch Street north of Lombard Street CC7 Beech Street at Whitecross Street CC8 London Wall at Bassishaw Highwalk CC9 Gresham Street east of Basinghall Street CC10 Poultry west of Grocers’ Hall Court CC11 Cannon Street/Wallbrook at Dowgate Hill CC12 Upper Thames east of Queen Street Place CC13 Mark Lane south of Hart Street CC14 Old Broad Street at Great Winchester Street CC15 Long Lane east of Lindsey Street
4. This report considers the data gathered in the 2017 survey and examines longerterm trends in the TCS dataset. More detailed analysis is provided in Appendix 1.
Key Findings 5. Traffic volumes have continued to trend downwards since the TCS counts began
in 1999. However, the 2017 counts did not record a significant change in vehiclevolumes when compared to the recently-undertaken 2016 counts.
6. More pedestrians were counted in 2017 than all vehicles combined, representingalmost two-thirds of all traffic on City streets. Over 59,000 pedestrian movementswere recorded ‘at night’ (between 19:00 and 07:00), making walking the mostcommon mode of travel during this period.
7. Cycling volumes in the City are the only counted mode to have seen growth since1999, increasing by nearly 300%. However, recent cycling counts suggest thatcycling growth has stagnated.
8. Despite peak hour traffic volumes decreasing since at least 2007, the peakperiods are getting ‘peakier’, likely due to an increase in cycling.
9. Morning and evening peak hour traffic composition is considerably different, withmore goods and services vehicles on City streets in the morning and more cars,private hire vehicles and taxis in the evening.
10. Cycle, motorcycle, and pedestrian 24-hour time profiles indicated that thesemodes are predominantly driven by commuting traffic. All other modes did notshow peak-time variation, suggesting their role in facilitating commuting trips wasnot as significant.
11. Cars and private hire vehicles use the most space on City streets whilepotentially moving fewer people than buses. Pedestrian traffic constitutes themajority of people movement on City streets as more people were estimated tohave moved through the City on foot than by all other modes combined.
Conclusions 12. City of London Traffic Composition Survey (TCS) data indicates that street traffic
volumes have been declining since 1999, albeit at a slower rate in recent years.The 2017 TCS was the first year that pedestrian data was also collected,improving our understanding of pedestrian travel across the City. Overall, theTCS data will support the evidence-led development of the upcoming City ofLondon Transport Strategy.
Appendices Appendix 1 – Traffic in the City 2018 (please see digital copy or pdf).
Giacomo Vecia Department of the Built Environment T: 020 7332 1489 E: [email protected]
TRAF
FIC
IN T
HE C
ITY
2018
Febr
uary
201
8St
rate
gic
Tran
spor
tatio
nD
epar
tmen
t of t
he B
uilt
Envi
ronm
ent
Cont
ents
1.In
trodu
ctio
n……
……
……
……
……
……
……
……
……
……
……
……
……
……
……
……
……
……
……
……
…Pa
ge 2
2.Tr
affic
Com
posi
tion
Surv
ey T
rend
Dat
a……
……
……
……
……
……
……
……
……
……
……
……
……
……
…Pa
ge 6
3.Tr
affic
Com
posi
tion
Surv
ey20
17 D
ata
Anal
ysis
……
……
……
……
……
……
……
……
……
……
……
……
.....P
age
11
1
Intro
duct
ion
Ove
rvie
wTh
isre
port
prov
ides
anov
ervi
ewof
the
findi
ngs
from
the
City
ofLo
ndon
Traf
ficC
ompo
sitio
nSu
rvey
s(T
CS)
.The
sesu
rvey
s–
cond
ucte
dev
ery
two
year
ssi
nce
1999
–pr
ovid
ede
tails
ofth
enu
mbe
ran
dty
pes
ofve
hicl
esus
ing
the
City
’sst
reet
s.
In20
17an
addi
tiona
lTC
Sw
asun
derta
ken.
For
the
first
time
this
incl
uded
pede
stria
nco
unts
,fur
ther
enha
ncin
gth
eda
tase
tahe
adof
the
deve
lopm
ento
fthe
City
ofLo
ndon
Tran
spor
tStra
tegy
.
This
repo
rtco
nsid
ers
the
data
gath
ered
inth
e20
17su
rvey
and
exam
ines
long
erte
rmtre
nds
inth
eTC
Sda
tase
t.
Use
s an
d Li
mita
tion
Whi
leth
eTC
Spr
ovid
esa
com
preh
ensi
vees
timat
eof
City
-wid
etra
ffic
com
posi
tion,
the
surv
eys
dono
trep
rese
nta
‘cor
don
coun
t’an
dsh
ould
notb
eco
nsid
ered
aco
mpr
ehen
sive
coun
tofa
llC
itytra
ffic.
Inst
ead,
the
data
isus
edto
iden
tify
trend
sac
ross
sam
ple
year
san
dto
com
pare
prop
ortio
nsof
diffe
rent
type
sof
traffi
cbe
twee
nsi
tes
and
betw
een
coun
tsfro
mdi
ffere
ntye
ars.
Stru
ctur
eTh
is re
port
is s
truct
ured
as
follo
ws;
•C
hapt
er2
visu
alis
eshi
stor
ical
data
gath
ered
thro
ugh
the
TCS
from
1999
onw
ards
alon
gsid
eid
entif
ying
sign
ifica
nttre
nds
inth
eda
tase
t;•
Cha
pter
3pr
ovid
esan
in-d
epth
anal
ysis
of20
17TC
Sco
untd
ata.
TCS
Cou
ntLo
catio
ns•
The
Traf
ficC
ompo
sitio
nSu
rvey
bega
nin
1999
and
reco
rded
vehi
cula
rtra
ffic
flow
sat
the
follo
win
gfif
teen
site
s:
•C
C1
–N
ewBr
idge
Stre
etat
Tudo
rStre
et•
CC
2–
New
Cha
nge
atFe
stiv
alG
arde
ns•
CC
3–
Que
enSt
reet
sout
hof
Che
apsi
de•
CC
4–
Que
enVi
ctor
iaSt
reet
wes
tofB
uckl
ersb
ury
•C
C5
–Ki
ngW
illiam
Stre
etat
Abch
urch
Lane
•C
C6
–G
race
chur
chSt
reet
north
ofLo
mba
rdSt
reet
•C
C7
-Bee
chSt
reet
atW
hite
cros
sSt
reet
•C
C8
–Lo
ndon
Wal
latB
assi
shaw
Hig
hwal
k•
CC
9–
Gre
sham
Stre
etea
stof
Basi
ngha
llSt
reet
•C
C10
–Po
ultry
wes
tofG
roce
rs’H
allC
ourt
•C
C11
–W
allb
rook
atD
owga
teH
ill•
CC
12–
Upp
erTh
ames
east
ofQ
ueen
Stre
etPl
ace
•C
C13
–M
ark
Lane
sout
hof
Har
tStre
et•
CC
14–
Old
Broa
dSt
reet
atG
reat
Win
ches
terS
treet
•C
C15
–Lo
ngLa
neea
stof
Lind
sey
Stre
et
Thes
e si
tes
cove
r the
four
diff
eren
t cla
ssifi
catio
ns th
at m
ake
up th
e C
ity
stre
et n
etw
ork
(Tra
nspo
rt fo
r Lon
don
Roa
d ne
twor
k –
TLR
N B
orou
gh
Roa
d N
etw
ork
–BR
N; L
ocal
Roa
d N
etw
ork
–LR
N; a
nd L
ocal
Acc
ess
Rod
–LA
R).
His
toric
ally
, cou
nts
wer
e co
nduc
ted
over
a 1
2 ho
ur p
erio
d (0
7:00
to
18:5
9) in
bot
h di
rect
ions
at a
ll si
tes.
In 2
016,
the
coun
t per
iod
was
ex
tend
ed to
cov
er a
full
24 h
our p
erio
d.
2
1 Int
rodu
ctio
n
Figu
re 1
.1 L
ocat
ions
of C
ity T
raffi
c C
ompo
sitio
n Su
rvey
cou
nt s
ites
1 Int
rodu
ctio
n
3
1 Int
rodu
ctio
n
TCS
Cou
ntM
odes
Vehi
cula
rtra
ffic
was
coun
ted
atal
lsite
san
dre
cord
edin
ast
anda
rdco
untd
atab
ase.
Cou
ntda
taw
asre
cord
edin
15m
inut
ein
terv
als
bym
ode
and
dire
ctio
n.Th
em
odes
coun
ted
are.
Priv
ate
Car
–in
clud
esbo
thpr
ivat
ehi
re/m
inic
abve
hicl
es(e
.g.U
bera
ndAd
diso
nLe
e).
Taxi
–‘B
lack
Taxi
cabs
’.
Mot
orcy
cle
(MC
)–in
clud
esm
otor
cycl
esan
dm
oped
s.D
oes
noti
nclu
deel
ectri
ccy
cles
.
Ligh
tGoo
dsV
ehic
le(L
GV
)–in
clud
esal
lgoo
dsve
hicl
esup
to3.
5to
nnes
gros
sve
hicl
ew
eigh
t,an
dal
lcar
deliv
ery
vans
.
Hea
vyG
oods
Veh
icle
(OG
V1
&O
GV
2)–
Incl
udes
allr
igid
vehi
cles
over
3.5
tonn
esgr
oss
vehi
cle
wei
ghtw
ithtw
oor
mor
eax
els.
OG
V1sp
ecifi
cally
refe
rsto
allr
igid
vehi
cles
over
3.5
tonn
esgr
oss
vehi
cle
wei
ght
with
two
orth
ree
axle
s,an
dO
GV2
spec
ifica
llyre
fers
torig
idve
hicl
esw
ithfo
uror
mor
eax
les
and
alla
rticu
late
dve
hicl
es.
Pub
licS
ervi
ceV
ehic
le(P
SV
)–in
clud
esTf
Lbu
ses,
coac
hes,
and
tour
istb
uses
/ope
n-to
pbu
ses.
Cyc
le–
incl
udes
allp
erso
nal,
dock
less
cycl
ehi
re(i.
e.O
fo,M
obik
e),a
ndTf
LC
ycle
Hire
(San
tand
er)c
ycle
s.
Pede
stria
nco
unts
wer
eal
soun
derta
ken
in20
17an
ddi
stin
guis
hbe
twee
ndi
rect
ion
oftra
vela
ndsi
deof
road
used
.
4
2TC
S Tr
end
Data
His
toric
alTr
ends
inTr
affic
Volu
mes
City
traffi
cco
mpo
sitio
nha
sch
ange
dsi
gnifi
cant
lyov
erth
ela
sttw
ode
cade
s,bo
thin
term
sof
the
tota
lvol
ume
oftra
ffic
and
the
prop
ortio
nsof
diffe
rent
vehi
cle
type
sth
atm
ake
upth
attra
ffic.
Figu
re2.
1hi
ghlig
hts
the
perc
enta
gech
ange
into
talv
ehic
leco
unt
(blu
eba
rs)
and
the
abso
lute
num
ber
ofve
hicl
esco
unte
dea
chye
ar(o
rang
elin
e).
The
tota
lnum
bero
fveh
icle
sco
unte
don
the
City
’sst
reet
sha
sde
clin
edov
eral
lsin
ceco
untin
gbe
gan
in19
99*
from
ahi
ghof
over
200,
000
vehi
cles
toju
stun
der1
24,0
00in
2017
.Thi
sre
pres
ents
a40
perc
entd
ecre
ase
inco
unte
dve
hicl
em
omen
tsov
eral
lora
ppro
xim
atel
y-2
perc
enta
year
.How
ever
,th
isde
crea
seha
soc
curre
din
burs
tsra
ther
than
grad
ually
with
grea
ter
drop
sin
2004
,20
10,
and
2016
.Th
ese
coun
tye
ars
corre
spon
dw
ithth
ein
trodu
ctio
nof
the
Con
gest
ion
Cha
rge
Zone
(200
3),t
heG
loba
lRec
essi
on(2
008)
,and
the
intro
duct
ion
ofC
ycle
Supe
rhig
hway
s(2
016)
,alo
ngsi
deot
her
ongo
ing
fact
ors
such
asna
tiona
linc
reas
esin
rail
trave
land
traffi
csp
ace
real
loca
tions
onC
ityst
reet
s.Tr
affic
volu
mes
also
clim
bed
mar
gina
llyin
thre
eco
unty
ears
(200
7,20
12,a
nd20
17).
*His
toric
altre
ndda
tais
repr
esen
tativ
eof
the
twel
vesc
reen
line
coun
tsite
s(C
C1-
12).
2 Tra
ffic C
ompo
sitio
n Sur
vey T
rend
Dat
a
Figu
re 2
.1 C
hang
e in
day
-tim
e (1
2hr;
07:
00-1
9:00
) veh
icle
cou
nts
acro
ss th
e C
ity
050100
150
200
250
-20%
-15%
-10%-5
%0%5%10%
1999
2002
2004
2005
2007
2010
2012
2014
2016
2017
VEHICLES (000’S)
YEARLY VEHICLE COUNT CHANGE
206,
000
124,
000
2004
2010
2016
6
His
toric
alTr
ends
inM
odal
Volu
mes
Traf
ficvo
lum
esof
allv
ehic
ular
mod
es(e
xcep
tcy
clin
g)ha
vede
crea
sed
over
the
last
two
deca
des
byat
leas
tone
-third
,with
day-
time
car/t
axia
ndm
otor
cycl
e(M
C)t
raffi
cde
clin
ing
59an
d49
perc
ent
resp
ectiv
ely
sinc
e19
99(F
igur
e2.
2,rig
ht).
Hea
vygo
ods
vehi
cle
(OG
V)vo
lum
esha
vede
clin
edby
sim
ilar
amou
nts
whi
lelig
htgo
ods
vehi
cle
(LG
V)vo
lum
esha
vese
enth
eirn
umbe
rsre
mai
nre
lativ
ely
cons
iste
ntsi
nce
2004
afte
rdip
ping
roug
hly
ath
irdfro
m19
99le
vels
(Fig
ure
2.3,
belo
w).
Som
eof
the
stre
etca
paci
tyun
lock
edby
thes
ede
crea
ses
inm
otor
ised
vehi
cle
traffi
c,al
ongs
ide
cycl
ing
infra
stru
ctur
ein
stal
latio
nsac
ross
the
City
,ha
vefa
cilit
ated
a29
2pe
rcen
tin
crea
sein
cycl
ing
volu
mes
sinc
e19
99,w
ithan
addi
tiona
l24,
000
cycl
ing
jour
neys
reco
rded
onco
untd
ayin
2017
.The
seco
unts
-tak
enin
Oct
ober
and
Nov
embe
r–ar
ere
pres
enta
tive
ofw
inte
rcy
clin
gra
tes.
Itis
likel
yth
atcy
clin
gw
ould
mak
eup
anev
engr
eate
rsh
are
ofve
hicl
em
ovem
ents
durin
gth
esp
ring
and
sum
mer
mon
ths.
Not
show
nhe
rear
eco
unte
dbu
san
dot
herp
ublic
serv
ice
vehi
cle
(PSV
)vol
umes
.Cou
ntda
tafro
mPS
Vsar
ein
clud
edin
upco
min
gse
ctio
ns.
2 Tra
ffic C
ompo
sitio
n Sur
vey T
rend
Dat
aFi
gure
2.2
Per
cent
age
chan
ge 1
999-
2017
in d
ay-
time
time
vehi
cle
coun
ts a
cros
s th
e C
ity (1
2hr)
Figu
re 2
.3 A
bsol
ute
chan
ge in
day
-tim
e ve
hicl
e co
unts
acr
oss
the
City
by
year
(12h
r)
70
20,0
00
40,0
00
60,0
00
80,0
00
100,
000
120,
000
140,
000
160,
000
1999
2002
2004
2005
2007
2010
2012
2014
2016
2017
NUMBER OF VEHICLES
Car
& T
axi
LGV
OG
V
MC
Cyc
le
-59%
-37%
-51%
-49%
292%
-100
%
-50%0%50%
100%
150%
200%
250%
300%
350%
Car
& T
axi
LGV
OG
VM
CC
ycle
133,
877
93,3
54
55,2
16
His
toric
alTr
ends
inH
ourly
Volu
mes
and
Peak
Mod
alSp
litFi
gure
2.4
(righ
t)sh
ows
the
perc
enta
geof
tota
lday
-tim
etra
ffic
obse
rved
inea
chho
urpl
otte
das
alin
e.Th
eha
shed
oran
gelin
ere
pres
ents
2007
perc
enta
ges
and
the
hash
edbl
uelin
ere
pres
ents
2017
perc
enta
ges.
Des
pite
all
vehi
cula
rtra
ffic
decr
easi
ngdu
ring
the
mor
ning
peak
perio
d(a
sse
enin
Figu
re2.
5),p
eak
hour
traffi
cvo
lum
esas
apr
opor
tion
ofal
l-day
traffi
cvo
lum
esha
sin
crea
sed
sinc
e20
07,i
ndic
ated
byth
ehi
gher
peak
son
the
blue
line.
This
islik
ely
due
toth
eco
mbi
natio
nof
all-d
aym
otor
vehi
cula
rtra
ffic
redu
ctio
nsan
dan
incr
ease
inpe
ak-ti
me
cycl
eco
mm
utin
g.Th
isw
illbe
expl
ored
furth
erin
Cha
pter
3.
Figu
re2.
5(b
elow
)com
pare
sch
ange
sin
mor
ning
peak
hour
traffi
cvo
lum
esby
mod
e.Tr
affic
volu
mes
durin
gth
ispe
riod
have
decl
ined
sinc
eat
leas
t200
7*(a
lbei
twith
asm
alli
ncre
ase
obse
rved
in20
12).T
henu
mbe
rof
cycl
ists
coun
ted
durin
gth
em
orni
ngpe
akho
urha
sm
ore
than
doub
led
sinc
e20
07,
mak
ing
itth
esi
ngle
larg
est
mod
eof
trans
port
coun
ted
onC
ityst
reet
sfro
m08
:00
to09
:00.
Car
san
dta
xivo
lum
esco
unte
ddu
ring
the
mor
ning
peak
hour
have
decr
ease
dsi
nce
2007
whi
lego
ods
and
serv
ices
vehi
cle
volu
mes
have
rem
aine
dre
lativ
ely
unch
ange
dov
erth
esa
me
perio
d.
*Raw
data
from
prio
rto
2007
isun
avai
labl
eat
this
time.
2 Tra
ffic C
ompo
sitio
n Sur
vey T
rend
Dat
aFi
gure
2.4
Pro
port
ion
of a
ll da
y-tim
e tr
affic
by
hou
r of d
ay (m
easu
re o
f ‘pe
akin
ess’
)
Figu
re 2
.5 M
orni
ng p
eak
hour
(08:
00-0
9:00
) veh
icle
cou
nts
by m
ode
and
year
8
6%7%8%9%10%
11%
12%
78
910
1112
1314
1516
1718
2007
2017
050
0010
000
1500
020
000
2500
030
000
3500
0
2007
2010
2012
2014
2016
2017
NU
MBE
R O
F VE
HIC
LES
Car
Taxi
LGV
OG
V
Cyc
le
MC
PSV
His
toric
alTr
ends
inPe
akM
odal
Split
-Com
paris
onPe
akpe
riod
traffi
cco
mpo
sitio
nis
sign
ifica
ntly
diffe
rent
whe
nco
mpa
ring
betw
een
the
mor
ning
and
even
ing
peak
perio
ds.F
igur
e2.
6be
low
com
pare
sth
em
odal
split
ofm
orni
ngpe
ak(0
8:00
-09:
00)a
ndev
enin
gpe
ak(1
7:00
-18:
00)v
ehic
ular
traffi
cby
year
sinc
e20
07.T
hem
orni
ng(A
M)p
eak
perio
dha
sha
da
sign
ifica
ntly
larg
erpr
opor
tion
ofgo
ods
and
serv
ices
traffi
c(L
GVs
and
OG
Vs)
whi
leth
eev
enin
g(P
M)
peak
perio
dha
sha
da
com
para
tivel
yla
rger
prop
ortio
nof
car
and
taxi
traffi
c.Th
isis
inco
ntra
stto
the
rela
tivel
yco
mpa
rabl
epr
opor
tions
ofcy
cles
,mot
orcy
cles
,and
buse
sco
unte
din
the
two
peak
perio
ds.
Thes
eob
serv
atio
nssu
gges
tsth
atw
hile
the
tota
lvol
ume
ofm
otor
vehi
cle
traffi
cha
sde
crea
sed
year
over
year
(as
desc
ribed
inpr
evio
usfig
ures
),th
ere
lativ
epr
opor
tions
ofpe
akm
otor
vehi
cle
traffi
cha
vere
mai
ned
fairl
yco
nsis
tent
sinc
e20
07,w
ithsi
gnifi
cant
lym
ore
good
san
dse
rvic
eve
hicl
esco
unte
din
the
mor
ning
peak
and
mor
eca
rsan
dta
xis
coun
ted
inth
eev
enin
gpe
ak.
2 Tra
ffic C
ompo
sitio
n Sur
vey T
rend
Dat
a
Figu
re 2
.6 C
ompa
rison
of A
M p
eak
(08:
00-0
9:00
) and
PM
pea
k (1
7:00
-18:
00) m
odal
spl
it by
yea
r
9
0%10
%20
%30
%40
%50
%60
%70
%80
%90
%10
0%
2007
PM
2007
AM
2010
PM
2010
AM
2012
PM
2012
AM
2014
PM
2014
AM
2016
PM
2016
AM
2017
PM
2017
AM
Car
Taxi
LGV
OG
VM
CC
ycle
PSV
Tren
dsin
Traf
ficC
ompo
sitio
nAs
disc
usse
dpr
evio
usly
,cy
clin
gha
sse
ena
sign
ifica
ntin
crea
sein
volu
me
over
the
last
two
deca
des.
The
rate
ofgr
owth
incy
clin
gac
ross
the
city
betw
een
1999
and
2012
was
onav
erag
eov
er20
perc
ent
per
year
,w
ithso
me
year
sre
achi
ngov
er50
perc
enty
ear-o
n-ye
argr
owth
.
How
ever
,gr
owth
incy
clin
gbe
gan
tosl
owin
2012
.Fi
gure
2.7
(righ
t)sh
ows
the
year
lych
ange
inve
hicl
eco
unts
inde
xed
to19
99va
lues
.Acu
rve
ofbe
stfit
adde
dto
the
cycl
ing
curv
e(h
ashe
dgr
een
line)
show
sa
peak
in20
16.
Whi
leth
isis
not
aex
trapo
lato
ryex
erci
se,
itdo
esap
pear
that
the
City
coun
tsha
vere
ache
d‘p
eak
cycl
e’ov
erth
ela
stfiv
eye
ars,
sugg
estin
gth
atsi
gnifi
cant
chan
ges
incy
clin
gin
frast
ruct
ure
prov
isio
nan
d/or
trave
lbe
havi
ourm
aybe
need
edto
spur
furth
ergr
owth
incy
clin
gon
City
stre
ets.
2 Tra
ffic C
ompo
sitio
n Sur
vey T
rend
Dat
a
Figu
re 2
.7 C
hang
e in
day
-tim
e (1
2hr;
07:
00-1
9:00
) veh
icle
cou
nts
acro
ss th
e C
ity, i
ndex
ed to
199
9 va
lues
10
050100
150
200
250
300
350
400
450
19
99
20
02
20
04
20
05
20
07
20
10
20
12
20
14
20
16
20
17
INDEX 1999=100
Car
& T
axi
LGV
OG
VM
CC
ycle
Poly
. (C
ycle
)
3TC
S20
17 D
ata A
naly
sis
12
8328
138
322
3068
0
8388
4408
814
51610
051
4135
71
0%20
%40
%60
%80
%10
0%
Car
sTa
xiLG
VO
GV
Cyc
leM
CPS
VPe
dest
rian
3 201
7 Dat
a Ana
lysis
Figu
re 3
.1 2
017
all-d
ay tr
affic
com
posi
tion
(with
out [
abov
e] a
nd w
ith [b
elow
] pe
dest
rian
coun
ts)
050
0010
000
1500
020
000
2500
030
000
3500
040
000
4500
0
New
Brid
ge S
treet
New
Cha
nge
Que
en S
treet
Que
en V
icto
ria S
treet
King
Willi
am S
treet
Gra
cech
urch
Stre
etBe
ech
Stre
etLo
ndon
Wal
lG
resh
am S
treet
Poul
tryC
anno
n St
reet
Upp
er T
ham
es S
treet
Mar
k La
neO
ld B
road
Stre
etLo
ng L
ane
Car
sTa
xis
LGV
OG
VPS
VM
CC
ycle
2017
Traf
ficC
ompo
sitio
nTh
e20
17TC
Sco
unte
dm
ore
than
642,
000
indi
vidu
alve
hicl
ean
dpe
dest
rian
mov
emen
tsov
erth
e24
hour
(‘all-
day’
)obs
erva
tion
perio
don
Nov
embe
r16
thac
ross
all1
5co
unt
site
s.Ap
prox
imat
ely
185,
000
mot
orve
hicl
es,4
4,00
0cy
cles
,and
413,
000
pede
stria
nsw
ere
coun
ted
(Fig
ure
3.1,
right
).Th
e20
17TC
Sis
the
first
time
that
pede
stria
nsha
vebe
enin
clud
edin
coun
ts.
The
brea
kdow
nof
the
coun
tdat
aof
all1
5si
tes
surv
eyed
ispr
esen
ted
inFi
gure
3.2
belo
w(e
xclu
ding
pede
stria
ns).
The
thre
ebu
sies
tsi
tes
coun
ted
wer
eU
pper
Tham
esSt
reet
,N
ewBr
idge
Stre
et,
and
Gra
cech
urch
Stre
et.N
oin
cide
nts
orse
vere
wea
ther
cond
ition
sw
ere
obse
rved
onth
eco
unt
day
and
thus
the
resu
ltspr
esen
ted
here
are
cons
ider
edin
dica
tive
ofa
neut
rall
ate-
autu
mn
day
inth
eC
ity.
Figu
re 3
.2 2
017
all-d
ay tr
affic
com
posi
tion
by s
ite (e
xclu
ding
ped
estr
ians
)
NU
MBE
R O
F VE
HIC
LES
13
3 201
7 Dat
a Ana
lysis
Figu
re 3
.3 C
ompa
rison
of m
otor
veh
icle
, cyc
le, a
nd p
edes
tria
n co
unts
at e
ach
site
2017
Pede
stria
nFl
ows
Incl
udin
gpe
dest
rian
coun
tsal
ongs
ide
vehi
cle
coun
tsal
low
sa
mor
eco
mpr
ehen
sive
anal
ysis
ofpe
ople
mov
emen
tson
City
stre
ets
bybo
thm
otor
ised
and
non-
mot
oris
edm
odes
.
Figu
re3.
3be
low
com
pare
sth
eto
taln
umbe
rofc
ount
edm
otor
vehi
cles
(car
s,ta
xis,
LGVs
,OG
Vs,m
otor
cycl
esan
dm
oped
s,an
dPS
Vs),
cycl
es,a
ndpe
dest
rians
atea
chsi
te(o
rder
edby
tota
lmov
emen
tcou
nted
)ove
rthe
24ho
urpe
riod.
Atm
osts
ites
the
num
bero
fped
estri
ans
coun
ted
was
atle
aste
qual
toth
enu
mbe
rof
mot
orve
hicl
esan
dcy
cles
coun
ted
(with
the
exce
ptio
nsof
Lond
onW
alla
ndU
pper
Tham
esSt
reet
).In
som
eca
ses,
the
num
bero
fped
estri
ans
coun
ted
was
upto
six
times
grea
ter
than
the
num
ber
ofve
hicl
esco
unte
d(e
xclu
ding
Mar
kLa
new
hich
ispr
edom
inan
tlya
pede
stria
nth
orou
ghfa
re).
Furth
eran
alys
isof
the
estim
ated
num
bero
fpeo
ple
mov
ing
bydi
ffere
ntm
odes
isex
plor
edat
the
end
ofth
isC
hapt
er.
NU
MBE
R O
F VE
HIC
LES
010
000
2000
030
000
4000
050
000
6000
070
000
8000
090
000
Gra
cech
urch
Stre
et
New
Brid
ge S
treet
Old
Bro
ad S
treet
Upp
er T
ham
es S
treet
Poul
try
Can
non
Stre
et
King
Willi
am S
treet
New
Cha
nge
Beec
h St
reet
Que
en V
icto
ria S
treet
Gre
sham
Stre
et
Lond
on W
all
Que
en S
treet
Long
Lan
e
Mar
k La
ne
Car
s/Ta
xis
and
MC
sG
oods
and
Ser
vice
s Ve
hicl
esC
ycle
sPu
blic
Ser
vice
Veh
icle
sPe
dest
rians
2017
Vehi
cula
rCou
nts
byH
ouro
fDay
(Tim
ePr
ofile
s)Th
eho
ur-b
y-ho
urpr
ofile
ofth
e20
17ve
hicu
lar
coun
ts(e
xclu
ding
pede
stria
ns)
issh
own
inFi
gure
3.4
belo
w.M
otor
ised
mod
es(s
how
nbe
low
inth
ick-
colo
ured
bars
;inc
lude
sca
rs,t
axis
,LG
Vs,O
GVs
,mot
orcy
cles
and
mop
eds,
and
buse
s)ar
eob
serv
edto
reac
ha
leve
lofa
ppro
xim
atel
y88
00co
unte
dm
ovem
ents
alto
geth
erat
07:0
0an
dre
mai
nat
orar
ound
this
leve
lfor
the
rest
ofth
e‘d
ay-ti
me’
perio
d(0
7:00
to19
:00)
and
thro
ugh
part
ofth
eni
ght-t
ime
perio
d(1
9:00
-23:
59).
Goo
dsan
dse
rvic
esve
hicl
esm
ake
upa
sign
ifica
ntpo
rtion
ofm
otor
ised
traffi
cdu
ring
the
mor
ning
and
thro
ugho
utth
eda
yan
dth
enbe
gin
tode
clin
ein
toth
eev
enin
g-tim
e.Th
e‘s
pare
’cap
acity
freed
upby
the
grad
uald
eclin
ein
good
san
dse
rvic
esve
hicu
lar
traffi
cw
asla
rgel
yut
ilised
byth
ein
crea
sing
num
bero
fcar
san
dta
xis
obse
rved
onC
ityst
reet
s,pa
rticu
larly
inth
eev
enin
gho
urs.
Cyc
ling,
inco
ntra
stto
mot
orve
hicl
es,
isob
serv
edto
have
two
dist
inct
peak
s–
from
08:0
0to
10:0
0in
the
mor
ning
and
from
17:0
0to
19:0
0in
the
even
ing.
Thes
eob
serv
atio
nssu
gges
ttha
tmot
orve
hicl
etra
ffic
isle
ssre
late
dto
‘pea
k-tim
e’co
mm
utin
gan
dm
ore
asso
ciat
edw
ithot
herp
urpo
ses.
3 201
7 Dat
a Ana
lysis
Figu
re 3
.4 2
017
vehi
cula
r cou
nts
by h
our o
f day
(exc
ludi
ng p
edes
tria
ns)
14
0
2000
4000
6000
8000
1000
0
1200
0
1400
0
1600
0
1800
0
01
23
45
67
89
1011
1213
1415
1617
1819
2021
2223
Car
& T
axi
LGV
OG
VPS
VM
CC
ycle
NUMBER OF VEHICLES
2017
Vehi
cula
rand
Pede
stria
nC
ount
sby
Hou
rofD
ayAd
ding
pede
stria
nsto
Figu
re3.
4(p
revi
ous
page
)sig
nific
antly
chan
ges
the
hour
lypr
ofile
ofco
unte
dtra
ffic.
Figu
re3.
5be
low
show
sth
epe
rcen
tage
ofal
l-day
traffi
cco
unte
dby
hour
ofda
yan
din
clud
esal
lveh
icul
arm
odes
(thic
kco
lour
edba
rs)a
ndpe
dest
rians
(hol
low
bars
).Th
ree
dist
inct
peak
sar
eno
wob
serv
ed,c
orre
spon
ding
toAM
(08:
00-1
0:00
),lu
ncht
ime
(12:
00-1
4:00
),an
dPM
(17:
00-1
9:00
)ped
estri
anvo
lum
epe
aks.
Sign
ifica
ntpe
dest
rian
traffi
cis
also
obse
rved
outs
ide
ofth
ese
perio
dsan
din
toth
eev
enin
gof
f-pea
kpe
riod
(19:
00-2
3:59
)whi
chw
illbe
look
edat
furth
erla
teri
nth
isch
apte
r.O
vera
ll,th
ere
was
mor
epe
dest
rian
traffi
cth
anve
hicu
lart
raffi
cco
unte
dfo
rthe
maj
ority
ofth
eda
y(0
7:00
to20
:00)
.
3 201
7 Dat
a Ana
lysis
15
0%2%4%6%8%10%
01
23
45
67
89
1011
1213
1415
1617
1819
2021
2223
Car
& T
axi
LGV
OG
VPS
VM
CC
ycle
Pede
stria
n
Figu
re 3
.5 A
ll m
odes
cou
nts
by h
our o
f day
and
per
cent
age
of d
aily
traf
fic
Tim
ePr
ofile
sof
Each
Mod
eEa
chm
ode
oftra
velw
asob
serv
edto
have
adi
stin
cttim
epr
ofile
.Fig
ure
3.6
belo
wsh
ows
the
all-d
aytim
epr
ofile
sof
each
mod
e(n
ote:
diffe
rent
scal
esar
eus
edfo
reac
hgr
aph)
.Thr
eem
odes
–m
otor
cycl
es,c
ycle
s,an
dpe
dest
rians
–w
ere
obse
rved
toha
vepe
aks
durin
gth
eco
mm
uter
peak
perio
ds.M
otor
cycl
esw
ere
less
‘pea
ky’t
han
cycl
es,
sugg
estin
gth
atm
any
mot
orcy
cle
mov
emen
tsw
ere
bein
gm
ade
durin
gda
ytim
eho
urs
for
non-
com
mut
ing
purp
oses
.G
oods
and
serv
ices
vehi
cles
,par
ticul
arly
LGVs
,wer
esh
own
tope
akin
the
mor
ning
and
afte
rnoo
nan
dst
eadi
lyde
clin
eov
erth
eda
y,re
flect
ing
the
gene
ralp
rofil
eof
freig
htde
liver
ies
obse
rved
acro
ssLo
ndon
.Pub
licse
rvic
eve
hicl
esw
ere
show
nto
have
are
lativ
ely
flatp
rofil
edu
ring
dayt
ime
hour
s.Fi
nally
,car
s(in
clud
ing
priv
ate
hire
vehi
cles
)an
dta
xis
wer
eob
serv
edto
peak
muc
hla
teri
nth
eev
enin
g,su
gges
ting
thes
em
odes
did
notr
epre
sent
man
ytra
ditio
nalc
omm
utin
gtri
ps.
3 201
7 Dat
a Ana
lysis
0
1000
2000
3000
4000
5000
6000
7000
Car
Taxi
0
100
200
300
400
500
600
700
PSV
0
500
1000
1500
2000
2500
3000
LGV
OG
V
0
200
400
600
800
1000
1200
1400
1600
Mot
orcy
cle
0
1000
2000
3000
4000
5000
6000
7000
8000
Cyc
le
0
1000
0
2000
0
3000
0
4000
0
5000
0
6000
0Pe
dest
rian
Figu
re 3
.6 2
4 ho
ur ti
me
prof
iles
of a
ll m
odes
(diff
eren
t sca
les
used
)
NUMBER OF VEHICLES NUMBER OF VEHICLES
16
17
3 201
7 Dat
a Ana
lysis
Figu
re 3
.7 C
ompa
rison
of d
aytim
e (li
ght b
ar) a
nd n
ight
-tim
e (d
ark
bar)
traf
fic a
nd p
edes
tria
n co
unts
3754
0
2275
42229
5
5771
6522
1102
0
3548
4
3541
51
4574
1
1556
8
8385
2617
3529
349686
045942
0
0%25
%50
%75
%10
0%
Car
Taxi
LGV
OG
V
PSV
MC
Cyc
le
Pede
stria
n
025
000
5000
075
000
1000
0012
5000
1500
00
Day
Nig
ht
Car
Taxi
LGV
OG
VC
ycle
MC
PSV
Figu
re 3
.8 C
ompa
rison
of t
otal
day
time
and
nigh
t-tim
e ve
hicu
lar t
raffi
c by
mod
e (e
xcl.
pede
stria
ns)
Day
time
and
Nig
ht-ti
me
Cou
ntVo
lum
eC
ompa
rison
sAs
the
2017
TCS
was
cond
ucte
dov
era
24-h
our
perio
dit
was
poss
ible
toex
amin
ean
dco
mpa
re‘d
aytim
e’(d
efin
edas
07:0
0-18
:59)
and
‘nig
ht-ti
me’
(def
ined
as19
:00-
23:5
9an
d00
:00-
06:5
9)tra
ffic.
Ove
rall,
appr
oxim
atel
y38
perc
ent
ofal
lco
unte
dve
hicu
lar
traffi
cw
asre
cord
eddu
ring
nigh
t-tim
eho
urs,
sugg
estin
gth
ere
isst
illco
nsid
erab
letra
vel
dem
and
inof
f-pea
kho
urs
and
parti
cula
rlyfro
m19
:00
to23
:59.
The
prop
ortio
nof
dayt
ime
vers
usni
ght-t
ime
traffi
cva
ries
cons
ider
ably
betw
een
mod
es.
Car
sha
veth
egr
eate
stpr
opor
tion
ofni
ght-t
ime
toda
ytim
etra
ffic
atov
er55
perc
ent.
Asi
gnifi
cant
num
ber
ofbu
ses
wer
eal
soco
unte
ddu
ring
the
nigh
t-tim
epe
riod
acro
ssth
eC
ity,
with
over
aqu
arte
rof
all
bus
mov
emen
tsre
cord
eddu
ring
this
time
(like
lyre
pres
entin
gth
esi
gnifi
cant
num
ber
ofni
ght
bus
rout
esth
atpa
ssth
roug
hth
eC
ity).
Furth
eran
alys
isof
nigh
t-tim
ejo
urne
ysis
mad
eon
the
follo
win
gtw
opa
ges
for
cars
,ta
xis,
cycl
es,
and
pede
stria
ns.
38%
62%
NU
MBE
R O
F VE
HIC
LES
18
3 201
7 Dat
a Ana
lysis
Figu
re 3
.9 N
ight
-tim
e tim
e pr
ofile
s of
car
s, ta
xis,
cyc
les,
and
ped
estr
ians
(d
iffer
ent s
cale
s)
0
1000
2000
3000
4000
5000
6000
7000
12:0013:0014:0015:0016:0017:0018:0019:0020:0021:0022:0023:0000:0001:0002:0003:0004:0005:0006:0007:0008:0009:0010:0011:00
0
1000
2000
3000
4000
5000
6000
7000
8000
12:0013:0014:0015:0016:0017:0018:0019:0020:0021:0022:0023:0000:0001:0002:0003:0004:0005:0006:0007:0008:0009:0010:0011:00
0
1000
0
2000
0
3000
0
4000
0
5000
0
6000
0
12:0013:0014:0015:0016:0017:0018:0019:0020:0021:0022:0023:0000:0001:0002:0003:0004:0005:0006:0007:0008:0009:0010:0011:00
Car
Taxi
Cyc
le
Pede
stria
n
20%
or8
,600
mov
emen
ts a
t nig
ht
14%
or5
9,40
0 m
ovem
ents
at n
ight
55/4
1% o
r45,
700/
15,5
00 m
ovem
ents
at n
ight
Nig
ht-ti
me
Cou
ntVo
lum
eC
ompa
rison
sFi
gure
3.9
(righ
t)sh
ows
the
tota
lni
ght-t
ime
coun
tvo
lum
esof
cars
,tax
is,c
ycle
s,an
dpe
dest
rians
byho
ur.A
bove
each
char
tis
the
prop
ortio
nof
nigh
t-tim
eco
unt
volu
mes
ofal
l-day
volu
mes
alon
gsid
eab
solu
teni
ght-t
ime
coun
tvo
lum
es(a
lso
repr
esen
ted
onth
ech
artb
yth
eco
lour
edar
eaun
dere
ach
time
prof
ilelin
e).
Asm
entio
ned
prev
ious
ly,
the
maj
ority
ofca
rtri
psan
dov
er40
perc
ento
ftax
itrip
sw
ere
mad
edu
ring
the
nigh
t-tim
epe
riod.
Car
sin
parti
cula
rpe
akat
appr
oxim
atel
y23
:00.
This
sugg
ests
ther
eco
uld
besi
gnifi
cant
priv
ate
hire
and
taxi
activ
ityin
the
City
inof
f-pe
akho
urs.
Des
pite
the
dark
erco
nditi
ons,
appr
oxim
atel
y20
perc
ent
ofal
lco
unte
dcy
clin
gtri
psw
ere
mad
edu
ring
the
nigh
t-tim
epe
riod,
with
cycl
ing
volu
mes
stay
ing
rela
tivel
yhi
ghun
til22
:00.
Ther
ew
ere
appr
oxim
atel
yth
esa
me
num
bero
fcyc
lists
coun
ted
acro
ssth
eC
ityfro
m21
:00
to22
:00
asfro
m11
:00
to12
:00.
Excl
udin
gpe
dest
rians
,cyc
lists
wer
eth
eth
irdm
ostc
omm
onst
reet
user
inth
eni
ght-t
ime
perio
d.
Pede
stria
nsw
ere
the
sing
lela
rges
tstre
etus
ergr
oup
inth
eni
ght-
time
perio
d,ac
coun
ting
for
over
40pe
rcen
tof
all
coun
ted
mov
emen
t.W
hile
only
14pe
rcen
toft
otal
pede
stria
ntra
ffic
was
obse
rved
inth
eni
ght-t
ime
perio
dth
enu
mbe
rof
pede
stria
nsco
unte
dw
asgr
eate
rtha
nth
eto
taln
umbe
roft
axis
,LG
Vs,O
GVs
,PS
Vs,m
otor
cycl
esan
dm
oped
s,an
dcy
cles
coun
ted
com
bine
d.
NUMBER OF VEHICLES NUMBER OF VEHICLES NUMBER OF VEHICLES
19
3 201
7 Dat
a Ana
lysis
Nig
ht-ti
me
Cou
ntVo
lum
eC
ompa
rison
sFi
gure
3.10
(bel
ow)c
ompa
res
the
volu
mes
ofco
unte
dca
r,ta
xi,c
ycle
,and
pede
stria
ntra
ffic
over
the
nigh
t-tim
epe
riod.
Ther
ear
em
ore
pede
stria
nsco
unte
don
City
stre
ets
betw
een
19:0
0an
d23
:00
than
any
othe
rsin
gle
mod
e,su
gges
ting
that
asi
gnifi
cant
prop
ortio
nof
peop
lem
ovin
gar
ound
the
City
atni
ghta
redo
ing
soon
foot
.The
rear
eal
som
ore
cycl
esth
anta
xis
onC
ityst
reet
sfro
m19
:00
to20
:00,
sugg
estin
gth
atcy
cle
trave
lis
also
asi
gnifi
cant
off-p
eak
trave
lmod
eon
City
Stre
ets.
0
2000
4000
6000
8000
1000
0
1200
0
1400
0
1600
0
1800
0
19:0
020
:00
21:0
022
:00
23:0
000
:00
01:0
002
:00
03:0
004
:00
05:0
006
:00
Car
Taxi
Cyc
lePe
dest
rian
Figu
re 3
.10
Nig
ht-ti
me
time
prof
iles
of c
ars,
taxi
s, c
ycle
s, a
nd p
edes
tria
ns
NUMBER OF VEHICLES
21%
19%
53%
6%
6%
26%
7%
5%
4%
2%
19%
9%
64%
51%
9%
0%10
%20
%30
%40
%50
%60
%70
%80
%90
%10
0%
Cou
nts
Peop
le
Spac
e
Car
s/Ta
xis
and
MC
sG
oods
and
Ser
vice
s Ve
hicl
esC
ycle
sPu
blic
Ser
vice
Veh
icle
sPe
dest
rians
3 201
7 Dat
a Ana
lysis
Figu
re 3
.11
Com
paris
on o
f est
imat
ed s
tree
t spa
ce u
tilis
atio
n, e
stim
ated
peo
ple
mov
ed, a
nd c
ount
ed v
ehic
les/
pede
stria
ns b
y ty
pe
Peop
leM
oved
and
Spac
eU
tilis
edby
Mod
alG
roup
The
tota
lstre
etsp
ace
take
nan
dnu
mbe
rof
peop
lem
oved
byea
chm
ode
wer
eap
prox
imat
edus
ing
coun
tdat
aan
dPr
ivat
eC
arU
nit(
PCU
)co
nver
sion
san
doc
cupa
ncy
estim
ates
.Fig
ure
3.11
show
sdi
ffere
ntm
odal
grou
ps’s
treet
spac
eut
ilisat
ion,
estim
ated
peop
lem
ovem
ent,
and
coun
ted
volu
mes
asa
prop
ortio
nof
allt
raffi
c.
Priv
ate
vehi
cles
–ca
rs,t
axis
,and
mot
orcy
cles
/mop
eds
–ut
ilised
the
mos
tstre
etsp
ace
ofan
ym
ode
–ov
er53
perc
ent–
whi
leon
lyca
rryi
ngan
estim
ated
quar
tero
fall
peop
letra
vellin
gon
City
stre
ets.
Whi
lebu
ses
only
mad
eup
two
perc
ento
fall
coun
ted
vehi
cles
,the
yca
rried
anes
timat
ed19
perc
ento
fall
peop
letra
vellin
gon
City
stre
ets
(com
pare
dto
21an
d19
perc
entf
orpr
ivat
eve
hicl
esre
spec
tivel
y).B
uses
and
priv
ate
vehi
cles
carri
edap
prox
imat
ely
the
sam
enu
mbe
rofp
eopl
ein
the
City
whi
lem
akin
gup
anes
timat
ed9
and
53pe
rcen
toft
otal
stre
etsp
ace
usag
ere
spec
tivel
y.
Peop
leon
foot
also
mad
eup
anes
timat
ed9
perc
ento
ftot
alst
reet
spac
eus
age
whi
lem
akin
gup
anes
timat
edon
e-ha
lfof
tota
lpeo
ple
mov
emen
ts.T
his
sugg
ests
that
the
City
’spa
vem
ents
–w
hich
ofte
nm
ake
uple
ssth
an25
perc
ento
fto
tals
treet
spac
e–
mov
eth
em
ajor
ityof
peop
letra
vellin
gon
City
stre
ets.
20
Taxi
Taxi Taxi