1. background examining daily commuting...
TRANSCRIPT
25/10/13
1
EXAMINING DAILY COMMUTING PATTERNS USING GIS
Bart Dewulf 25/10/’13
Dewulf Bart1,2,3, Tijs Neutens1,2, Mario Vanlommel1,4, Steven Logghe4, Philippe De Maeyer1, Yves De Weerdt3, Nico Van de Weghe1
1Department of Geography, Ghent University, Krijgslaan 281, S8, B-9000, Ghent, Belgium
2Research Foundation Flanders, Egmontstraat 5, B-1000, Brussels, Belgium 3VITO, Boeretang 200, B-2400, Mol, Belgium
4BeMobile, Technologiepark 12b, B-9052, Ghent, Belgium
1. Background
¨ Flanders ¤ At the heart of Europe ¤ Polycentric structure (Brussels, Antwerp) à Large traffic pressure
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Oslo
Köln
Roma
Bern
Lyon
Paris
BerlinBremen
London
Dublin
Torino
Monaco
Milano
Madrid
Hamburg
München
Bordeaux
København
AntwerpenBruxelles
AmsterdamRotterdam
Marseille
Barcelona
Luxembourg
San Marino
±" Large cities
Flanders
Countries
1. Background
¨ 80% of passenger trips (car, bus, train, tram, metro) by car ¤ Congestion à time loss ¤ Air pollution ¤ High fuel costs
¨ Brussels and Antwerp ¤ Top 2 congested cities in the world
(OECD, 2013)
2. Objectives
¨ Examine daily commuting patterns in Flanders
¤ Where is congestion a major problem? ¤ Travel times with public transport ¤ Comparison of car and public transport à where is
public transport a decent alternative?
3. Data and methods
¨ Flanders ¤ Data available per Traffic Analysis Zone (TAZ)
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GENK
GENT
AALST
BRUGGE
LEUVENHASSELT
OOSTENDE
KORTRIJK
TURNHOUT
MECHELEN
ROESELARE
ANTWERPEN
SINT-NIKLAAS
±" Large cities
Traffic Analysis Zones (TAZs)
Brussels
3. Data and methods
¨ Origin-destination matrices between all TAZs ¤ Number of simulated commuting trips (Multi Modal Model) ¤ Actual travel times with floating car data (BeMobile)
n Car off-peak, car on-peak, public transport
TAZ1
TAZ2
- Number of trips - Travel time
TAZ3 - Number of trips - Travel time
- Number of trips - Travel time
25/10/13
2
3. Data and methods
¨ GIS ¤ Spatial analysis of car congestion and potential time
gain with public transport
¨ Circular statistics ¤ Circular mean ¤ Index of circular spread
¨ Two scale levels ¤ Flanders ¤ Large cities
4. Results – Flanders
¨ Commuting directions
4. Results – Flanders
¨ Average time per departing commuting trip
!"#$%&#!!"#$!!"#!!"#$ = !! .!!!!!!
!!!!!!
! 4. Results – Flanders
¨ Relative time loss in congestion Relative!time!loss!per!trip!"#$%&'("# = !
!"#$!"!!"#$ − !"#$!""!!"#$!"#$!""!!"#$ !
4. Results – Flanders
¨ Relative time loss with public transport
Relative!time!loss!per!trip!"#$%&!!"#$%&'"! = !!"#$!"#$%&!!"#$%&'"! − !"#$!"!!"#$
!"#$!"!!"#$ !
4. Results – Large cities
¨ More in detail for 13 large cities à radar charts
0"
500"
1000"
1500"
2000"
2500"
3000"
3500"
4000"
4500"
5000"0(5"
5(10" 10(15"15(20"20(25"
25(30"30(35"
35(40"40(45"
45(50"
50(55"
55(60"
60(65"
65(70"
70(75"
75(80"
80(85"
85(90"
90(95"
95(100"
100(105"
105(110"
110(115"
115(120"
120(125"
125(130"
130(135"
135(140"140(145"
145(150"150(155"
155(160"160(165"
165(170"170(175"175(180"180(185"
185(190"190(195"195(200"200(205"
205(210"210(215"
215(220"220(225"
225(230"
230(235"
235(240"
240(245"
245(250"
250(255"
255(260"
260(265"
265(270"
270(275"
275(280"
280(285"
285(290"
290(295"
295(300"
300(305"
305(310"
310(315"
315(320"320(325"
325(330"330(335"
335(340"340(345"
345(350"350(355"355(360"
TotRi2en"
WoWeRi2en"
0"
500"
1000"
1500"
2000"
2500"0&5"
5&10" 10&15"15&20"20&25"
25&30"30&35"
35&40"40&45"
45&50"
50&55"
55&60"
60&65"
65&70"
70&75"
75&80"
80&85"
85&90"
90&95"
95&100"
100&105"
105&110"
110&115"
115&120"
120&125"
125&130"
130&135"
135&140"140&145"
145&150"150&155"
155&160"160&165"
165&170"170&175"175&180"180&185"
185&190"190&195"195&200"200&205"
205&210"210&215"
215&220"220&225"
225&230"
230&235"
235&240"
240&245"
245&250"
250&255"
255&260"
260&265"
265&270"
270&275"
275&280"
280&285"
285&290"
290&295"
295&300"
300&305"
305&310"
310&315"
315&320"320&325"
325&330"330&335"
335&340"340&345"
345&350"350&355"355&360"
TotRi2en"
WoWeRi2en"
Ghent as origin Ghent as destination
Brussels
Antwerp
Number of trips
Total
Commuting Total
Commuting
Ghent
Ghent
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4. Results – Large cities
¨ Average time per trip
0"
500"
1000"
1500"
2000"
2500"
3000"
3500"
4000"
4500"0(5"
5(10" 10(15"15(20"20(25"
25(30"30(35"
35(40"40(45"
45(50"
50(55"
55(60"
60(65"
65(70"
70(75"
75(80"
80(85"
85(90"
90(95"
95(100"
100(105"
105(110"
110(115"
115(120"
120(125"
125(130"
130(135"
135(140"140(145"
145(150"150(155"
155(160"160(165"
165(170"170(175"175(180"180(185"
185(190"190(195"195(200"200(205"
205(210"210(215"
215(220"220(225"
225(230"
230(235"
235(240"
240(245"
245(250"
250(255"
255(260"
260(265"
265(270"
270(275"
275(280"
280(285"
285(290"
290(295"
295(300"
300(305"
305(310"
310(315"
315(320"320(325"
325(330"330(335"
335(340"340(345"
345(350"350(355"355(360"
WoWeDalSec"
WoWeSpitsSec"
Ghent as origin
Brussels Off-peak On-peak
!"#$%&#!!"#$!!"#!!"#$ = !! .!!!!!!
!!!!!!
!with!!!=!destination!TAZs,!!! !=!travel!time!to!TAZ!!,!!!=!number!of!trips!from!origin!TAZ!to!TAZ!!.!
Antwerp
Ghent
4. Results – Large cities
¨ Time loss ¤ Relative time loss in congestion and with public transport
0"
0,05"
0,1"
0,15"
0,2"
0,25"
0,3"
0,35"
0,4"
0,45"0)5"
5)10"10)15"15)20"20)25"25)30"
30)35"35)40"
40)45"45)50"
50)55"55)60"60)65"
65)70"
70)75"
75)80"
80)85"
85)90"
90)95"
95)100"
100)105"
105)110"
110)115"
115)120"
120)125"125)130"
130)135"135)140"
140)145"145)150"
150)155"155)160"
160)165"165)170"170)175"175)180"180)185"
185)190"190)195"195)200"200)205"205)210"
210)215"215)220"
220)225"225)230"
230)235"235)240"
240)245"
245)250"
250)255"
255)260"
260)265"
265)270"
270)275"
275)280"
280)285"
285)290"
290)295"
295)300"
300)305"305)310"
310)315"315)320"
320)325"325)330"
330)335"335)340"
340)345"345)350"350)355"355)360"
WoWeVerliesRelat,
WoWeVerliesRelat"
0"
0,5"
1"
1,5"
2"
2,5"
3"
3,5"
4"
4,5"0)5"
5)10"10)15"15)20"20)25"25)30"
30)35"35)40"
40)45"45)50"
50)55"55)60"60)65"
65)70"
70)75"
75)80"
80)85"
85)90"
90)95"
95)100"
100)105"
105)110"
110)115"
115)120"
120)125"125)130"
130)135"135)140"
140)145"145)150"
150)155"155)160"
160)165"165)170"170)175"175)180"180)185"
185)190"190)195"195)200"200)205"205)210"
210)215"215)220"
220)225"225)230"
230)235"235)240"
240)245"
245)250"
250)255"
255)260"
260)265"
265)270"
270)275"
275)280"
280)285"
285)290"
290)295"
295)300"
300)305"305)310"
310)315"315)320"
320)325"325)330"
330)335"335)340"
340)345"345)350"350)355"355)360"
WoWeVerliesOV*
WoWeVerliesOV"
Ghent as origin, congestion time loss Ghent as origin, public transport time loss
Brussels Brussels
Antwerp Antwerp
Relative!time!loss!per!trip!"#$%&'("# = !!"#$!"!!"#$ − !"#$!""!!"#$
!"#$!""!!"#$ !
Relative!time!loss!per!trip!"#$%&!!"#$%&'"! = !!"#$!"#$%&!!"#$%&'"! − !"#$!"!!"#$
!"#$!"!!"#$ !
Ghent Ghent
5. Conclusion
¨ Combination of simulated commuting trips and accurate travel times à detailed view
¨ Congestion ¤ Brussels and Antwerp ¤ Highways to these cities
¨ Public transport as alternative ¤ Mainly to Brussels and Antwerp!
6. Strengths
¨ Policy makers: where action needs to be taken
¨ Traditionally: on what road segments congestion occurs ¤ Now: from which areas people experience most time loss
6. Strengths
¨ Previous literature: focus on potential accessibility (e.g. to jobs), without commuting flows and travel times ¤ Now: modeled commuting flows + accurate travel times
¨ Travel times: often freeflow data ¤ Floating car data: very accurate ¤ Off-peak, on-peak à congestion
¨ Combination with public transport data THANK YOU