GreenSwirl: Combining Traffic Signal Control and Route Guidance for Reducing Traffic Congestion
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Jiaxing Xu, Weihua Sun, Naoki Shibata and Minoru Ito : "GreenSwirl: Combining Traffic Signal Control and Route Guidance for Reducing Traffic Congestion," in Proc. of IEEE Vehicular Networking Conference 2014 (IEEE VNC 2014), pp. 179-186. Serious traffic congestion is a major social problem in large cities. Inefficient setting of traffic signal cycles, especially, is one of the main causes of congestion. GreenWave is a method for controlling traffic signals which allows one-way traffic to pass through a series of intersections without being stopped by a red light. GreenWave was tested in several cities around the world, but the results were not satisfactory. Two of the problems with GreenWave are that it still stops the crossing traffic, and it forms congestion in the traffic turning into or out of the crossing streets. To solve these problems, we propose a method of controlling traffic signals, GreenSwirl, in combination with a route guidance method, GreenDrive. GreenSwirl controls traffic signals to enable a smooth flow of traffic through signals times to turn green in succession and through non-stop circular routes through the city. The GreenWave technology is extended thereby. We also use navigation systems to optimize the overall control of the city's traffic. We did a simulation using the traffic simulator SUMO and the road network of Manhattan Island in New York. We confirmed that our method shortens the average travel time by 10%-60%, even when not all cars on the road are equipped to use this system.
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GreenSwirl: Combining Traffic Signal Control and Route Guidance for Reducing Traffic Congestion
- 1. Jiaxing Xu†1 , Weihua Sun†2, Naoki Shibata†1, Minoru Ito†1 †1 Nara Institute of Science and Technology, Japan †2 Shiga University, Japan
- 2. We combine Traffic Signal Control and Route Guidance so that Reduce traffic congestion Vehicles likely encounter green lights Minimize the travel time of vehicles Proposed method consists of two parts GreenSwirl: traffic signal control method ▪ Enable smooth-flowing traffic on many circular routes GreenDrive: route guidance method ▪ Guide of the shortest time path for individual drivers 2 The whole traffic Vehicles
- 3. Background and Related Study Proposed Method Evaluation and Results Conclusion and Future Work 3
- 4. Serious traffic congestion The lack of carefully planned traffic signals is one of the major reasons 4 Air pollution caused by vehicle emissions 25% of PM2.5 pollution in Beijing comes from exhaust gas from vehicles In order to reduce traffic congestion Traffic Signal Control GreenWave Dynamic Route Guidance
- 5. Coordinating a series of traffic lights to enable continuous traffic flow over several intersections in one main direction Principle: control the time period for green lights by predicting the arrival time of vehicles GreenWave Direction 5
- 6. GreenWave cannot be created at crossing traffic 6 GreenWave GreenWave GreenWave GreenWave
- 7. Often red light at opposite lane 10 traffic lights were tested in Nanjing City, China (May 19, 2014) GreenWave GreenWave GreenWave 7 4km GreenWave Direction : 4 minutes Opposite Direction: 9 minutes
- 9. Control traffic signals on many direction roads Control the traffic and guide the vehicles to the optimal route Priority in a single direction Low capacity of roads connecting to main roads Easily causing congestion Entering excessive vehicles Gridlock
- 10. Background and Related Study Proposed Method Evaluation and Results Conclusion and Future Work 10
- 11. Traffic Signal Control GreenSwirl Route Guidance GreenDrive To reduce traffic congestion To minimize the travel time of vehicles 11
- 12. GreenWave is formed on many roads like huge swirls throughout one city A swirl is a single loop of the multiple GreenWaves formed by GreenSwirl Vehicles can run at the legal speed limit on a swirl without stopping unless there is traffic congestion 12 Priority Direction PriorityDirection Priority Direction PriorityDirection Swirls No Stopping City Center Smoothly running even in crossing road Control the entering traffic Control the entering traffic Optimize each vehicle
- 13. Guiding each vehicle to the shortest time path Estimate the travel time of each road segment Guide some vehicles to the swirls for dispersing traffic 13 PriorityDirection Priority Direction PriorityDirection PriorityDirection PriorityDirection Priority Direction PriorityDirection PriorityDirection 90s 130s Resolve the problem in opposite lane 160s
- 14. 1. Set the initial travel time for all road segments 2. Guide each vehicle to the shortest time path 3. Collect travel time from all road segments and output result 4. Increase travel time by 1% for the top 1% congested road 5. Until the result ( average travel time of all vehicles) becomes stable, output the best recommend route to vehicles Traffic volume balance Congestion 14
- 15. Traffic data Speed of vehicles on road segments Two ways to collect traffic data 1. Deploy speed-detecting sensors in all road segments 2. Deploy sensors in some road segments and part of vehicles report their speed and position to the server via communication 15 Static Data GreenSwirl Swirls Road Network GreenDrive Server TrafficData Route
- 16. 16 Current Swirls are formed manually CenterCenter Park Main Area 2 Determine main roads High traffic capacity Multi-Lane Detect the area crowded with vehicles Main area City center Form the swirls To disperse Vehicles 3 1
- 17. Background and Related Study Proposed Method Evaluation and Results Conclusion and Future Work 17
- 18. Experiment Purposes Evaluate the performance of GreenSwirl and GreenDrive Evaluate the proposed method in scenarios where a part of road segments has sensor installed for obtaining traffic data Simulator SUMO (Simulation of Urban Mobility) 18
- 19. Manhattan in New York Map data is taken from OpenStreetMap Many one-way streets 4km×20km Number of streets : 870 Number of vehicles: 5000/10000/15000/20000 19
- 20. Synchronized Method Default signal control method implemented in SUMO 20 GreenWave GreenWave is used for main streets with a high traffic capacity The default synchronized method is used for other streets Same time
- 21. Shortest-Path Method Vehicles are guided along paths of the shortest distance DUA (dynamic user assignment) Method[1] It works by running simulations to discover travel times and assigning alternative routes to vehicles Vehicles are guided along routes selected according to calculated probabilities, to distribute all the traffic Problems ▪ This method does not optimize the travel time for each user ▪ Some users are guided along detour paths 21 [1] Krajzewicz, Daniel, Michael Behrisch, and Yun-Pang Wang. "Comparing performance and quality of traffic assignment techniques for microscopic road traffic simulations." DTA2008 International Symposium on Dynamic Traffic Assignment. No. EPFL-CONF-154987. 2008.
- 22. 800 1300 1800 2300 2800 5000 10000 15000 20000 AverageTravelTime(s) Number of vehicles Synchronized GreenWave GreenSwirl Reduce average travel time by 21% compared with GreenWave Reduce average travel time by 10% compared with GreenWave GreenDrive 22
- 23. GreenDrive 100% penetration is the best 800 1300 1800 2300 2800 3300 3800 4300 5000 10000 15000 20000 AverageTravelTime(s) Number of vehicles Shortest Path 100% DUA 100% GreenDrive 25% GreenDrive 50% GreenDrive 75% GreenDrive 100% Reduce 55% compared to Shortest-path Reduce 23% compared to DUA GreenSwirl 23
- 24. 800 1300 1800 2300 2800 3300 3800 4300 5000 10000 15000 20000 AverageTravelTime(s) Number of vehicles DUA 100% GreenDrive 50% GreenDrive 100% GreenSwirl 24 GreenDrive 100% penetration is the best DUA 100% penetration ≈ GreenDrive 50% penetration
- 25. Sensor 30% Traffic data can be obtained from 30% of the streets Sensor 30% + Feedback 1% Traffic information can be obtained from 30% of the streets and 1% of the all vehicles report their travel information Sensor 70% Traffic data can be obtained from 70% of the streets Sensor 100% Traffic data can be obtained from all the streets 25
- 26. 0 500 1000 1500 2000 2500 5000 10000 15000 20000 AverageTravelTime(s) Number of vehicles GreenDrive_Sensor30% GreenDrive_Sensor30%+Feedback1% GreenDrive_Sensor70% GreenDrive_Sensor100% 26 Less travel time as the ratio of sensors increases Sensor 30% + Feedback 1% ≈ Sensor 70%
- 27. Proposed Method GreenSwirl: traffic signal control method GreenDrive: route guidance method Reduce the average travel time by 10%-60% compared with the existing methods Future works Evaluate the proposed method for maps of other cities Automatic generation algorithm for GreenSwirl according to traffic data 27 center center center Beijing Boston Vehicles:50,000 Vehicles:80,000
- 28. Jiaxing Xu, Weihua Sun, Naoki Shibata and Minoru Ito : "GreenSwirl: Combining Traffic Signal Control and Route Guidance for Reducing Traffic Congestion," in Proc. of IEEE Vehicular Networking Conference 2014 (IEEE VNC 2014)(23% acceptance rate), pp. 179-186, 2014-12-15. DOI:10.1109/VNC.2014.7013337 [ PDF ] 28
Editor's Notes
- I am Xu Jiaxing , coming from Nara Institute of Science and Technology. Today I’d like to present our work about GreenSwirl: Combing traffic signal control and route guidance for reducing traffic congestion
- As we all know Serious traffic congestion and associated air pollution caused by vehicle emissions are major social problems in many countries The lack of carefully planned traffic signals ,especially, is one main cause for traffic congestion. And it was found that 25% of PM2.5 pollution in Beijing comes from vehicle exhaust gas. At present, There have been many ways for reducing traffic congestion such as Traffic Signal Control and Dynamic Route Guidance. Especially, GreenWave is a traffic signal control method which was used in many countries.
- GreenWave is a method for coordinating a series of traffic lights to enable continuous traffic flow over several intersections in one main direction Principle is to control the time period for lights to be green by predicting the arrival time of vehicles. GreenWave was tested in several cities in China, but the results were not satisfactory. Next I will introduce the problems of GreenWave
- The first problem is that GreenWave interferes with the crossing traffic . In this illustration, GreenWave is created at the one direction road, so the cars can smoothly travel on the GreenWave roads. However GreenWave cannot be created at crossing road, crossing traffic is will be interfered when run on crossing road.
- As the same with just problem , GreenWave also interferes with the opposite lane. The cars on the GreenWave lane can always encounter the Green Light. However The cars on the oppsite lane always encounter the red light. This problem is confirmed by 10 traffic lights in Nanjing city of China. The tested street is 4km and on one direction was formed the GreenWave. The result is that vehicles can take 4 minutes to pass the street on GreenWave Direction, on the Opposite Direction will take 9 minutes. So we can see that the vehicle will travel twice time on the Opposite Direction. http://jiangsu.china.com.cn/html/jsnews/around/289798_1.html
- The last problem , Traffic congestion may be caused at both entry and exit to main roads. First it is a matter of the Entry Congestion When the GreenWave to generate only on the main road, so many vehicles come together to the main road. And the roads connecting the main road always can not receive so much vehicles as the main road When theses vehicles is about to enter the main road. The congestion occurs at the entry. As the same reason, there is also a problem of exit congestion. When a lot of vehicles get off the main road to normal street , at exit will cause the congestion, in addition this congestion will also spread to the main road. Just we know problem by these examples , next I will summary the drawbacks of GreenWave and how to resolve the problem
- Briefly, there are two drawbacks, the first is that GreenWave is only priority in a single direction, in order to solve it ,we can control traffic signals on many direction roads like GreenWave . The second is the traffic flow. In the normal roads connecting to the main roads has low capacity of receiving traffic . So it is easy to cause the congestion and Even the main roads formed GreenWave will also be congestion when entered excessive vehicles. What’s worse, it can cause the serious congestion Gridlock. in order to avoid the congestion by traffic flow, we can control the traffic and guide the vehicles to the optimal route. According to the two solutions, our proposed method is born at this right moment
- We propose the Traffic signal control method GreenSwirl, combination with the Route Guidance method GreenDrive. The goals are to reduce traffic congestion and minimize the travel time of vehicles. I will introduce what is GreenSwirl
- the traffic signal control method GreenSwirl is that GreenWave is formed on many roads like huge swirls throughout one city. a swirl is a single loop of the multiple GreenWavs fromed by GreenSwirl. On a swirl , vehicles can run with out stopping unless there is traffic congestion. And the cars can also smoothly run even in crossing road. We use another method to control the entering traffic and optimize each vehicle.
- That is the rout guidance method GreenDrive. It can guide each vehicle to the shortest time path by estimation of the travel time passing through each road segment. So that it can guide some vehicles to the swirls for dispersing traffic. We provide two illustrations to help you to understand the image of GreenDrive. On the left, the car want to arrive to the top-right destination, GreenDrive will guide it to route by the outside swirl. On the right, the car want to arrive the destination on the opposite lane. This car can be provided some route by Swirls. The travel time of these routes is estimated and GreenDrive guides the car to the shortest time path so that it can resolve the problem in opposite lane. This is a simple image of GreenDrive, how operate the GreenDrive to control traffic and guide the shortest time path for each vehicles. Next I will introduce the details of GreenDrive illustration
- The details of GreenDrive The first step , we set the initial travel time for all road segments, and the second step, guide each vehicle to the shortest time path by simulation. And at the third step, when the vehicles running on the roads, the travel time of all road segments will be collected. at the fourth step, We can detect the congestion roads and in order to balance the traffic ,we increase the travel time by 1% for the top 1% congested road. And repeat the number of iterations until the average travel time of vehicles becomes stable, output the best recommend route to vehicles. We already know the image of two methods, next I will introduce how to combine them in real traffic network.
- First we should have a database to save the previous traffic data also called static data and collect it regularly from road network. Second, according the static data we will form the swirls by GreenSwirl and implement it on the road network. After that, the GreenDrive Server dose the simulation by the real-time traffic data and guide the optimal route for vehicles. These vehicles will run on the road network and generate the traffic data to the static data. The traffic data is the speed of vehicles on road segments, there are two ways to collect traffic data. One is to deploy speed-detecting sensors in all road segments, another one will deploy sensors in some road segments and part of vehicles report their speed the position to the server via communication. In our proposed method is assumed to use firest way. The second way will be evaluated that if it can effect the performance of proposed method.