Conceptual clarifi cation, micro-level individual attributes and residential
3.5 Multimodal trip profi le
is section presents a multimodal trip profi le based on the NTS data set. Trip duration and trip lengths for multimodal trips are analysed (and compared with car trips) and the daily travel time and distance of multimodal users are presented. e section also presents those typical mode chain combinations that occur most frequently. Based on this information the diagrammatic outline of a multimodal trip, introduced in Figure -, is further elaborated. e section is concluded with a more in-depth discussion of the relationship between trip (and stage) distances and the choice for multimodal transportation.
.. Typical mode chain combinations
Table - list the access and main mode combinations while Table - cross tabulates egress and main mode combinations for multimodal trips originating from home. Row totals show the share of the mode in all access or egress stages. For example, referring to Table -, the bicycle (access mode) was chained to a train (main mode) in . of all multimodal trips while the row total show that cycling was used in . of the cases as access mode.
Table -: Variables used
Descriptor Operational variables Description
Multimodal travel variables
Mode chain combinations Most frequently occurring mode chain combinations.
Number of trips All the trips per day of a person involved in multimodal trips
Travel duration Travel time per trip as well as total daily travel time Travel distance Distance per multimodal trip and total daily distance
travelled for multimodal travellers
Age 1 = 0-17; 2 = 18-24; 3 = 25-40; 4 = 40-65; 5 = 65 +
Gender 1 = Male; 2 = Female
Car Availability 1 = Drivers license + car; 2 = Drivers license + family car;
3 = Non-drivers license but family car; 4 = Drivers license and no car; 5 = No drivers license and no-family car.
Employment Status 1 = Full time employed (< 30 hours + students); 2 = Part Time employed (> 30 Hours); 3 = Unemployed; 4 = Pensioned
Socio- demographic variables
Income 1 = No income; 2 = < fl 18 000 (+/- $ 7 500); 3 = 18 000-27 000 (+/- $ 11 250); 4 = 27 000-34 000 (+/- $14 200); 5 = 34 000-42 000 (+/- $ 17 500) ; 6 = 42 000-58 000 (+/- $25 000); 7 = 58 000 <
Household Size 1 = 1 HH member; 2 = 2 HH members; 3 = 3 HH members; 4 = 4 HH members, 5 = 5 HH members; 6 = 6 HH members
Age of Children in household
1 = Child(ren) 0-5; 2 = Child(ren) 6-11; 3 = Child(ren) 12-17;
4 = No Children
Position within household 1 = Single; 2 = Household Head; 3 = Spouse of Head / Partner of Head; 4 = Live-in child; 5 = Other
Residential environment variable
Urban development intensity
Very strongly urbanized, Strongly urbanized, Moderately urbanized, Slightly urbanized, Non-urbanized
Column totals show the share of main mode given the distribution over access modes. Referring to Table -, the train was used in . as a main mode given the distribution of access modes.
Due to missing access and egress modes (i.e. -stage trips in particular), column totals for Table
- and - do not correspond.
... Access modes
Four modes are primarily used as access mode (Table -): walking, cycling, car (driver and passenger) and bus in descending order of frequency. Slow modes i.e. walking and cycling are the preferred access mode and accounts for over of all access stages. e car (driver and passenger) accounts for approximately of all access modes while bus accounts for roughly
. Walking is generally used to access a range of connecting, public transport main modes whilst the car is used mainly to access the train. e bicycle serves mostly the train and bus.
is illustrates the importance of walking as a continues, fl exible access mode requiring few auxiliary infrastructure. Other access modes generally require storage facilities and specialised infrastructure.
... Egress modes
Contrary to the access trip, travellers do not have all the private modes available to them at the destination location. Private cars and bicycles are normally only present at the origin location.
Looking at egress, the problem with asymmetric mode availability is evident. Cycling now only Table -: Mode chain combinations: home origin
Main mode (%)
Access Car (Driver) Car (Pass) Bus Tram/Metro Train Other Total
Walk 0.1 0.2 20.6 6.8 21.9 0.2 49.9
Bicycle 0.0 0.1 7.5 0.8 24.1 0.1 32.6
Car (Driver) 0.0 0.0 0.4 0.3 4.5 0.0 5.2
Car (Pass) 0.0 0.0 0.7 0.2 4.3 0.0 5.3
Bus 0.0 0.1 0.0 0.9 4.1 0.1 5.3
Motorbike 0.0 0.0 0.2 0.0 0.5 0.0 0.7
Tram/Metro 0.0 0.0 0.2 0.0 0.8 0.0 1.1
Train 0.0 0.0 0.0 0.0 0.0 0.0 0.1
Total 0.2 0.4 29.6 9.1 60.2 0.5 100.0
Table -: Mode chain combination: destination end Main mode (%)
Egress Car (Driver) Car (Pass) Bus Tram/Metro Train Other Total
Walk 0.2 0.1 17.6 4.4 35.8 0.1 58.2
Bicycle 0.0 0.0 1.0 0.1 7.2 0.0 8.3
Car (Driver) 0.0 0.0 0.0 0.0 0.2 0.0 0.2
Car (Pass) 0.0 0.0 0.3 0.0 1.9 0.0 2.3
Bus 1.0 0.7 0.9 0.8 11.6 0.3 15.2
Tram/Metro 0.8 0.7 5.1 0.0 6.7 0.2 13.6
Train 0.6 0.5 0.6 0.1 0.2 0.2 2.1
Total 2.6 2.0 25.5 5.4 63.7 0.7 100.0
accounts for of trips while walking accounts for of all egress trips. Public transport (bus, tram/metro and train combined) accounts for .
... Main modes
As mentioned above, main mode totals diff er between Tables - and - due to missing stages.
Considering all -,- and -stage multimodal trips originating from home, the most frequent main mode is the train () followed by bus () and tram/metro (). It is evident that most multimodal trips are still oriented towards the train as main mode.
.. Trip motives, trip lengths, trip duration and number of trips
Figure - compares the motives for car trips with the -, - and -stage multimodal trips. As shown, an increase in the number of stages is correlated with an increase in the share of routine number of stages is correlated with an increase in the share of routine number of stages trips, i.e. education and work. Infrequent trips such as shopping trips, decline with in increase in the number of stages.
Trip Duration (min)
Number of Stages Number of Stages
Trip Distance (km)
250 200 150 100 50 0 250
200 150 100 50 50
0 6243
Car trips 2-Stages 3-Stages 4-Stages
Median 1st Quartile 3rd Quartile
Minimum Value Maximum Value
Car trips 2-Stages 3-Stages 4-Stages
Figure -: Trip duration and lengths for multimodal and car trips
100 90 80 70 60 50 40 30 20 10 0
%
Car 2-Stages 3-Stages 4-Stages 6243
Work Relation Work Relation W Tours/W Tours/W Tours/Walksours/Walks Other Recreation/Sport Shopping Social Visits Education Work Work W
Figure -: Trip motives for multimodal and car trips
e box plots shown in Figure summarize the key statistics of multimodal and car trips, for trip duration and trip lengths, respectively. Some important conclusions can be drawn from this fi gure.
Both box plots confi rm a positive relationship between an increasing number of stages and longer trip duration and distance. In total, multimodal users spend approximately min/day travelling compared to min/day for car users. min/day for car users. min/day
Considering number of trips per day, multimodal transportation users undertake fewer trips on average: . trips per day compared to . trips for others. It should be noted that more than
of all multimodal transportation users are involved in or less multimodal trips per day, mostly a trip to a destination and back. e remaining trips are most likely to be unimodal and, more specifi cally, cycling or walking trips originating from home.
.. Stage distance and distance decay
Figure - shows the cumulative (percentage) distribution of users per mode over increasing distance for access, main and egress stages respectively (for trips originating from home). e total-curve shows the cumulative percentage of all users for that stage over increasing distance.
e dotted vertical line represents mean stage length. Mean stage distance for the main mode of a multimodal trip is km (median, km). Figure -C shows that the tram/metro is used over shorter distances followed by bus while the train is only really used for stages longer than
km’s.
In total, approximately of people travel less than km to the transportation node on the access side (mean access distance is . km and median is km). e diff erent modes, however, refl ect markedly diff erent distance profi les for the access distance. Figure -A shows that approximately of users that walk, do so over distances shorter than , km while of the people cycle less that km. Considering that most people either walk or use the bicycle as access mode (more than ), it is clear that an increasing access distance will negatively infl uence multimodal transportation.
e mean egress distance is . km (median, . km) – Figure -B – that is slightly longer than the mean access distance (. km). In addition, of people travel shorter than . km to their fi nal destination. It is furthermore interesting to note that bus and the tram/metro have very similar distance decay curves on the egress side.
Access and egress distance represents, combined, of total trip distance for all multimodal trips. is diff ers slightly for diff erent trip motives (access and egress share of total trip distance in brackets): work (.), education (), social visits (.), sport (.) and shopping ().
Following Keijer and Rietveld () it is believed that each mode serves a particular distance range. Assuming that the modes ‘complement’ each other on the access side, a problem occurs on the egress side. Keijer and Rietveld showed that on the access side walking trips mostly fall within the range -. km, cycling within -. km and public transport within - km.
At the egress stage, those trips suited for cycling (i.e. -. km) would now either rely on
walking or public transport (Keijer & Rietveld, ). Both of these modes imply severe negative time, distance and cost penalties for the user (i.e. longer travelling time through slower speeds, particularly walking, additional waiting/transfer times and fares associated with public transport). It seems plausible, therefore, to assume that egress distance is of particular importance for the potential use of multimodal transportation and that this importance can be attributed, largely, to transport mode availability (Blom, ; Van den Enden & Van Lohuizen, ). is assumption is supported by fi ndings from the Nationwide Personal Transportation Survey undertaken in the United States of America. Asked why people do not use ‘multimodal transportation’, indicated that it is not available at work destinations (Polzin, Rey & Chu, ).
100 90 80 70 60 50 40 30 20 10 0 100 90 80 70 60 50 40 30 20 10 0
100 90 80 70 60 50 40 30 20 10 0
6243
%
<0.5 <1 <2.5 <3.7 <5 <7.5 <10 <15 <20 <30 <40 <50 >50
Main mode
Distance (km)
C
%
<0.5 <1 <2.5 <3.7 <5 <7.5 <10 <15 <20 <30 <40 <50 >50
Egress Stage
Distance (km)
B
%
<0.5 <1 <2.5 <3.7 <5 <7.5 <10 <15 <20 <30 <40 <50 >50
Access Stage
Distance (km)
A
Walking Walking W Car (Driver) Car (Pass) Bicycle Bus
Total Total T Tram/Metro Tram/Metro T Train Train T
Figure -: Cumulative distribution of users over distance
Based on the above information, the schematic outline of a multimodal trip introduced in Figure - is further developed and shown in Figure -. Figure - shows the profi le for trips originating from home. e width of the bars provide an indication of the share of the mode in the diff erent stages while the length provides an indication of the mean length of the stage with the particular mode. Also shown is the mean and th percentile access and egress distance ranges (dotted arches).
e above section provided a conceptual framework of multimodal transportation (trips) and extended this framework with empirical fi ndings based on the Dutch National Travel Survey. Conclusions were drawn regarding the use of multimodal transportation and it was investigated how the characteristics of the access, egress and main mode, i.e. mode choice and distance, infl uence the use and possibly the potential for multimodal transport. e following section focuses more on personal and household characteristics of multimodal transportation users using the same NTS data set.