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7A_1_Multi-scale visualization of inbound and outbound traffic delays in london
- 1. Dr Tao Cheng, Andy Emmonds, Garavig Tanaksaranond, and Oluwadamilola O. Sonoiki University College London Multi-Scale Visualization of Inbound and Outbound Traffic Delays in London
- 7. How do we create contour map? 10.0 7.7 5.1 2.3 0
- 8. Saturday 9:00-10:00 16/01/2010 Inbound 10.0 7.7 5.1 2.3 0 Delay (mins/km)
- 9. 12:00-13:00 10.0 7.7 5.1 2.3 0 Delay (mins/km) Saturday 16/01/2010 Inbound
- 10. 18:00-19:00 10.0 7.7 5.1 2.3 0 Delay (mins/km) Saturday 16/01/2010 Inbound
- 11. 21:00-22:00 10.0 7.7 5.1 2.3 0 Delay (mins/km) Saturday 16/01/2010 Inbound
- 12. 9:00-10:00 18:00-19:00 21:00-22:00 Saturday 16/01/2010 Inbound road 12:00-13:00 10.0 7.7 5.1 2.3 0 Delay (mins/km)
- 14. Inbound Outbound Friday 15 Jan 2010 9:00-10:00 am
- 15. Weekday Morning vs Evening
- 16. 17:00-18:00 8:00-9:00 Friday 15 Jan 2010 inbound
- 18. Non-Bus lane users Bus lane users Inbound road Friday 15/01/2010 8:00 am 10.0 7.7 5.1 2.3 0 Delay (mins/km)
- 19. Bi directional thematic map
- 20. Data: Friday 15/01/2010 8:00 am non-bus lane (Inbound ) Contour map Thematic map Conclusion
- 21. Future Works + Time?
- 22. 10.0 7.7 5.1 2.3 0 Isosurface
- 23. 10.0 7.7 5.1 2.3 0
- 24. Stripe map 10.0 7.7 5.1 2.3 0
- 25. THANK YOU ANY QUESTIONS? Please visit http://standard.cege.ucl.ac.uk This work is supported by: EPSRC (Grant EP/G023212/1) Transport for London
Editor's Notes
- EXPLAIN WHO YOU ARE, SPONSORS AND THE PROJECT YOU’RE PART OF My name is Garavig. I’m gonna talk about multiscale visualization of inbound and outbound traffic delays in London. This research is a part of STANDARD project supported by Transport for London and EPSRC.
- You can see that congestion is still a problem in large cities and London is one of them. Now we have a lot of traffic monitoring devices on the road and we obtained a large amount of data but we still don’t really understand how and why traffic congestion still exists and the solution is still not very satisfactory. So, this study tried to employ visualization to get insight into such a large amount of data.
- Previous researches visualized travel time, speed, or traffic count, but there were no excess travel time or what we might called ‘delay’. For example, this picture is congestion visualization in Google map. They visualized velocity but not the delay. The contour map below shows the travel time from the selected point here…(point). In this research, we tried to visualize multi perspective and multi-scale which means we tried to give both general view and specific link view. This research is a part of visualization of traffic congestion in space-time. The previous researches still lack of visualization of traffic congestion in relation to space-time. For example, the development of congestion, how congestion spread out over the area. So, I’m trying to depict these progression and relationships.
- The first thing I’m gonna talk about is the data that I used in this research. Then I’m gonna talk about 2 visualization techniques that I employed: the contour map and the thematic map. For the contour map, I will talk about how I created the contour map. Then, to give examples how contour map are used, I will give examples by 3 types of comparison. For the thematic map, I’m gonna talk about the comparison between bus lane and non bus lane. Then, the bi directional thematic map will be discussed.
- We define travel time as the time a vehicle took to travel between the first traffic camera and the second traffic camera. The first and the second camera recorded the capture time when a car passed. The difference between both captured time is the travel time. The data is acquired from 539 core road links. The data we obtained from Transport for London was the 5 minute aggregated average travel time. We define the excess travel time as the difference between the average journey time and the free flow journey time. Free flow journey time is the travel time between 2 in the morning and 6 in the morning. There are very few traffic at that time. Therefore, we use this free flow journey time for the base line. You may ask why do we need this base line. It’s because of we don’t have this base, we are unable to compare congestion with no congestion. Therefore, this base line is really when there is no congestion. We divided the difference by length of each links so that the journey time can be compared between links. If we didn’t do this, long link will have high journey time and short link will have low journey time.
- I will move to the first visualization, the contour map. Contour map gives us general view of congestion– where the congestion severe. We may call it the congestion hotspots.
- This is how we create contour map. First, we take points from all beginning points of each links. Then we attach the delay data with each point. Next, we interpolate and create the contour map. The result will be shown next page.
- This is contour map of Saturday data. We can see there was no congestion in the morning around 9:00 am until 10:00 am.
- Then, the congestion increased in the afternoon between 12 and 1 pm because people started to go out for lunch, shopping, etc.
- I didn’t show the congestion after 1 pm until 6 pm because the congestion is not severe. The congestion began to concentrate within the inner city in Saturday evening when people came to the city to pubs and nightclubs.
- The severity dropped off at 9 pm when people got into nightclubs and their place of entertainment venue.
- In summary, you can see that the congestion on Saturday started to increase quite late. Then, the congestion is severe again in the evening when people went out to nightclubs and pubs. However, there is not much of a contrast because it’s a weekend.
- I will move to the comparison between inbound and outbound
- This slide shows the comparison between inbound and outbound. These are from the data on Friday 9 am. The picture on the left hand side is inbound and the right hand side is outbound. We can see that the inbound have more congestion than outbound because it was during the Friday morning when people came into the city center more than going out from the city.
- The next slide shows the comparison on weekday between morning and evening.
- This slide shows the comparison between Friday morning and Friday evening. We can see that during Friday evening the severity of traffic congestion was very high compared to Friday morning in the left picture. There was a lot of contrast because Friday evening people work done by weekend and they were going out for the evening.
- Now I will move to the thematic map. You will see that thematic map gives information of each links.
- This slide shows thematic map. It gives us information of each links. We can see that non-bus lane had problems here... And here... but bus lane can flow easily. It was because limited type of vehicles can use bus lane and bus lane has privilege on the road. Anyway from this thematic map, we can check what was happening on non-bus lane users. Non bus lane may have some problems like accident so that non bus lane had severe congestion while bus lane has no congestion on the same road.
- Because the contour map just give general information where the congestion happened, but the contour map cannot tell exactly which roads have severe delay, we will use thematic map to see which roads have severe traffic congestion. You can see the red spot on the contour map comes from the severe delay of road….. You can see on the thematic map.
- This are my future works. As we can see the contour map and the thematic map can represent where congestion happened and which area, which roads the congestions were severe, they are not good at presenting the congestion progress. So,I am trying to present time dimension using 3D visualization
- This is what I’m working on now. I added time dimension in my visualization. This is called isosurface. You can see the process of the congestion from the shape of the volume surface. This is the top view of the isosurface. You can see hot spots here. Actually, you can turn, move this picture around and see different perspective. But I just took snap shots to give example.
- This is the 3D stripe map. It can show the progress of the congestion on each link.