URBDP 576
Name: Simin Xu
Travel Log Data Analysis / Evaluation Report Travel Data Comparison This report compares the travel patterns of student A (student number 5916) and student B (student number 5928) during four days. Student A recorded the days from April 16 to April 19, while student B recorded April 15, 16, 19 and 22, both including 3 week day and 1 weekend.
Number of Trips Taken by Mode and Duration of Travel This part presents statistics on how they travelled during the four days. The statistics include a breakdown of trips by mode and duration of travel (hour, day of week, week day/weekend).
7%
8%
22%
70%
93% bus
auto/truck/van
walk
walk
bus
Figure 1 - Percent of Trips by Mode (Left: Student A, Right: Student B) Student A: Within total 29 trips, 93% are by walk and 7% by bus. Student B: Within total 27 trips, 70% are by walk, 23% by bus, and only 7% by car.
14%
15% 38%
48% 37%
48%
0-10min
11-20min
21-30min
0-10min
11-20min
21-30min
Figure 2 - Percent of Trips by Travel Time (Left: Student A, Right: Student B) Student A: 38% are within 10 minutes, 48% are within 11-20 minutes, 14% are more than 20 minutes. Student B: 48% are within 10 minute, 37% are within 11-20minutes, only 15% more than 20 minutes.
1
URBDP 576
Name: Simin Xu 16 14 12 10 8 6 4 2 0
14 9
9 6
2
7
4
3
4/15(Tue.) 4/16(wed.) 4/17(Thur.) 4/18(Fri.) 4/19(Sat.) 4/22(Tue.) studentA
studentB
Figure 3 - The Amount of Trips Taken Each Day Among the four record days of student A, most trips taken on Friday, then followed by Saturday, Wednesday and Thursday. For student B, the number of trips are equal on Tuesday and Wednesday, but less on Saturday, and Tuesday had only 2 trips. During the same record day (Wednesday and Saturday), student B took more trips compared to student A.
studentB
studentA 5.5
6
Saturday
6.5
7
7.5
Average weekday
Figure 4 - The Amount of Trips Taken on Saturday and Average Weekday For student A, trips taken more on average week day but less on Saturday, but student B is contrary. 10 8 6 4 2 0
studentA
studentB
Figure 5 - The Amount of Trips in Different Time 2
URBDP 576
Name: Simin Xu
For both student A and B, the peak time of trips taken is from 12:00 AM- 4:00PM. Another two small peak happened during 8:00 AM-10:00 AM and 6:00PM-22:00PM.
The “Places� Visited by Type
studentB
HOME
SCHOOL
FOOD SHOOPING
MAJOR SHOPPING
EXERCISE
0
0
0
1
3
4
5
3
4
5
7
8
studentA
OTHER PLACES
Figure 6 - "Places" Visited by Type The most frequent places both students visited are home, school as well as food shopping (including restaurant). Student A visited home and school more, and visited food shopping the same time as student B. While student B more often visited exercise places, student A did not.
The Time and Origin/Destination Characteristics of Trips by Mode Total Travel Time by Mode (minute) studentA
Average Trip Travel Time by Mode (minute)
studentB
studentA
studentB
-
10
auto/truck/van
-
20
bus
60
108
bus
30
18
walk
345
159
walk
12.8
8.4
Summary
405
287
Average
21.4
12.1
auto/truck/van
During the 4 days, student A made most trips by walk which consume more travel time than student B who made some of trips by bus and cars. In addition, the average travel time per trip of student A is more than student B no matter by bus or walk. For student A, walk is the dependent travel mode which links almost every origins and destinations. The only two trips by bus links from the origin of home to destination of major shopping or vice versa. For student B, if his origin or destination is home, he always uses bus. The only trip by car is from home to food shopping.
3
URBDP 576
Name: Simin Xu
The Time and Origin/Destination Characteristics of Trips by day of the week Total Travel Time by Day (minute) studentA
studentB
4/15(Tue.)
-
20
Average trip travel time by day (minute) studentA
studentB
4/15(Tue.)
-
10
15.7
11.5
4/16(wed.)
47
103
4/16(wed.)
4/17(Thur.)
60
-
4/17(Thur.)
15
-
4/18(Fri.)
205
-
4/18(Fri.)
12.8
-
4/19(Sat.)
93
72
4/19(Sat.)
15.5
10.3
4/22(Tue.)
-
92
4/22(Tue.)
-
10.2
The largest total travel time for student A is on Friday, then followed by Saturday. However, Wednesday is the largest for student B. On the day with their largest total travel time, student A’s origin and destination are diversity, including trips from home to school, home to major shopping, home to other places etc., student B’s trip is typical, but a trip stopped midway at food shopping and exercise, thus forming a chained trip. The average trip travel time of student A is between 12-16 minutes, more than 10-12 minutes of student B.
The Patterns of Trip Chaining in Terms of Time Spent Traveling, and Recurring Origins and Destinations of Trips Primary Trip Chaining student A home-transit stop-major shopping
Travel Time (minutes) 57
student B home-transit stop-school
32
school-exericise-transit stop-home
150
exercise-food shopping-transit stop-home
74
home-transit stop-food shopping-school
59
Time spend on chaining trip is much more than non-chaining trip. In student A’s trip chaining, the origin is from home and the destination is major shopping, one stop taken at transit stop. For student B, the home-transit stop-school and school-transit stop-home are typical chaining trip, which happens a lot during the four days. The recurring origin/destination is always home or school.
Similarities and Differences of Travel Behavior Because the environmental factors affects people’s behavior, the similarities and differences of travel behavior between different people is largely depends on the environment. Therefore, it is viable to use social-ecological model to discuss the similarities and differences between the two students. From the household environment, the two person are both students and has no work, thus most of their origin/destination are home or school during weekdays. Just like the origin and 4
URBDP 576
Name: Simin Xu
destination, the amount of time spent has similarity between the two students, they spent much time in school. Also, the peak time is very similar, a feasible explanation is because they took the same classes on Wednesday and both went to library on Saturday. However, student A is a female whose trip including a major shopping for clothes. Student B is a male who likes exercise, therefore he made several trips to IMA. A frequent “place” visited by both the two students is food shopping (restaurant) mainly because they have similar diet habits and both go to market once a week. From the social environment, the two students have no peers and siblings, thus their trips are less likely to be disturbed by others, like drop-off or pick-up a family member. A trip made by student B is by car, however student A have not, which means number of cars is also a variable which influence travel behavior. From the built environment, student A lives in U-district, the walkable street, suitable lot size provides a pleasant walk environment for student A. Also, the place she live is very close to school, thus her trips are mostly by walk. However, student B lives near Green Lake where less accessible to school, so his trips from/to home are mostly depends on bus. Most typical chaining trip of student B is like that, leaving home, walk several minutes, made a short stay at transit stop, took bus, walk several minutes to school. This means the transit stops less than 0.5 mile from the student B’s home or to school, as well as the short waiting time is an important reason of his travel behavior. Despite their modes are different, the average trip travel time for the two students are quite similar, both within or around 15min. Student B who took bus more has a relatively smaller average trip travel time than student A who walk-depends, which means travel time is an important element affects people to choose different mode. In addition, even though student B could use car as his travel mode, the cost of parking may prevent he to do so. The mixed use and high density in U-districts provides a lot of restaurants and markets as well as walkable streets for them, therefore most of their food shopping happens in U-district and by foot. The well designed tracks in University of Washington let students B walk from school to IMA.
Discussion of Collecting Travel Data by Using Travel Log Using travel log as an instrument to collect population-level travel data has a lot of advantages: first, it is cheap and relatively easy for everyone; second, it can record when, where, and why to travel; third, it is likely to give decent estimates when used correctly. But it also has some drawbacks: 1) Burdensome. Some participants may feel troublesome of doing it. Some may write down their travel behaviors once they remember, but do not record if they forget. Even some remember, if they are busy with something, they are less likely to do. 2)Potential biases. ①The one is recall bias that participants forget at that time they made the trip but estimate after a while, thus the time they record is not accurate. ②The second is from different personal style to record time, e.g., some may record 10:00 am, some may record 10:02 am, this minor difference would affects its accuracy. ③The third is from intentionally concealing that people may let their data looks modest or just remove some data if they don’t want others to know. ④The fourth is from intentionally forge data if they don’t travel a lot, or travel more than they used to be in order to provide more data. Because of these potential biases, travel log becomes less accuracy and reliable as a way to collect data. 5