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Intelligent Transportation Systems, Inter-Vehicle Communication, Navigation

Inter-Vehicle Communication

Collecting Congestion Information through Inter-Vehicle Communication

In this research, we proposed a method for cars to autonomously and cooperatively collect traffic jam statistics to estimate arrival time to destination for each car using inter-vehicle communication. In this method, the target geographical region is divided into areas, and each car measures time to pass through each area. Traffic information is collected by exchanging information between cars using inter-vehicle communication. In order to improve accuracy of estimation, we introduce several mechanisms to avoid same data to be repeatedly counted. Since wireless bandwidth usable for exchanging statistics information is limited, the proposed method includes a mechanism to categorize data, and send important data prior to other data. In order to evaluate effectiveness of the proposed method, we implemented the method on a traffic simulator NETSTREAM developed by Toyota Central R&D Labs, conducted some experiments and confirmed that the method achieves practical performance in sharing traffic jam information using inter-vehicle communication.

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Long Range Information Dissemination by Communication between Navigation Systems

In this research, we proposed a method which efficiently collects, retains and propagates traffic information using intervehicle communication with “message ferrying” technique used in vehicular ad hoc network (VANET). In the proposed method, we use buses as message ferries which travel along regular routes. In order to improve information propagation efficiency in lowdensity areas, buses collect as much traffic information as possible from cars in their proximity, and periodically disseminate the collected information to neighboring cars. We have implemented the proposed system on the traffic simulator NETSTREAM and compared information propagation efficiency between our proposed method and a method which uses inter-vehicle communication among only ordinary cars. In the simulation, the proposed method improved the efficiency up to 50%.

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GVgrid - Multi-hop Inter-vehicle Communication Protocol

In this research, we present a QoS routing protocol called GVGrid for multi-hop mobile ad hoc networks constructed by vehicles, i.e., vehicular ad hoc networks (VANETs). GVGrid constructs a route on demand from a source (a fixed node or a base station) to vehicles that reside in or drive through a specified geographic region. The goal of GVGrid is to maintain a high quality route, i.e. a robust route for the vehicles’ movement. Such a route can be used for high quality communication and data transmission between roadsides and vehicles, or between vehicles. The experimental results have shown that GVGrid could provide routes with longer lifetime, compared with an existing routing protocol for VANETs.

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  • Shibata, N., Terauchi, T., Kitani, T., Yasumoto, K., Ito, M., Higashino, T.: A Method for Sharing Traffic Jam Information Using Inter-Vehicle Communication, Proc. of V2VCOM2006 (2006). [ PDF ]
  • Kitani, T., Shinkawa, T., Shibata, N., Yasumoto, K., Ito, M., and Higashino, T.: Efficient VANET-based Traffic Information Sharing using Buses on Regular Routes, Proc. of 2008 IEEE 67th Vehicular Technology Conference (VTC2008-Spring), pp. 3031-3036, DOI:10.1109/VETECS.2008.326 (May 2008). [ PDF ]
  • Kitani, T., Shinkawa, T., Shibata, N., Yasumoto, K., Ito, M., and Higashino, T.: Efficient VANET-based Traffic Information Sharing using Buses on Regular Routes, Proc. of VTC2008-Spring, pp. 3031-3036 (2008).[ PDF ]
  • Weihua Sun, Hirozumi Yamaguchi, Koji Yukimasa and Shinji Kusumoto : "GVGrid: A QoS Routing Protocol for Vehicular Ad Hoc Networks", Proceedings of the 14th IEEE Int. Workshop on Quality of Service (IWQoS 2006), pp.130-139 (June 2006).[ PDF ]

Collaborative Sensing for Hazard Detection

Pedestrian Position Estimation through Inter-Vehicle Communication

In this research, we proposed a method for detecting the positions of pedestrians by cooperation of multiple cars with directional antennas to support drivers for pedestrian safety. In the method, each pedestrian carries a device which periodically transmits a beacon with a unique ID, and each car passing near the pedestrian receives the beacon by a directional antenna and measures the distance and the angle of arrival. We assume the distribution of the measurement errors to be a normal distribution, and the system calculates the existence probabilities of each pedestrian at each point. By exchanging information of the probabilities between cars, the area with high existence probability is narrowed down. In this paper, we first describe the situations where detecting positions of pedestrians greatly contribute to pedestrian safety, and then we describe the probability model used in our method, the method for calculating existence probabilities from information from multiple cars, and the protocol for exchanging the probability information between cars. We evaluated our method on QualNet simulator, and confirmed that the positions can be detected accurately enough for practical uses.

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Cooperatively Capturing and Sharing Intersection Video

For accident prevention at intersections, it is useful for drivers to grasp the position of vehicles in blind spots. This can be achieved without infrastructure if some vehicles passing near the intersection capture and share live video of the intersection through inter-vehicle communications. However, such video streaming requires a congestion control mechanism. In this paper, aiming to let a driver grasp the situation at an intersection, we propose a method to select vehicles that send a video in order to generate a live bird’s-eye-view video of the intersection. In our method, each vehicle at an intersection exchanges information with others, such as the sub-areas of the intersection it captures, the quality of its video, and its position and speed. Based on the exchanged information, each vehicle autonomously judges whether it should send its video or not. Through simulation with a QualNet simulator, we confirm that our method achieves a good video arrival rate and video quality sufficient for practical use.

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  • Sawa, Y., Kitani, T., Shibata, N., Yasumoto, K., Ito, M.: A Method for Pedestrian Position Estimation using Inter-Vehicle Communication, Proc. of AutoNet2008 (2008). [ PDF ]
  • Kotani, K., Sun, W., Kitani, T., Shibata, N., Yasumoto, K., Ito, M.: Inter-Vehicle Communication Protocol for Cooperatively Capturing and Sharing Intersection Video, Proc. of 2nd IEEE Intelligent Vehicular Communications System Workshop (IVCS'10), (CD-ROM), DOI:10.1109/CCNC.2010.5421635 (Jan. 2010).[ PDF ]

Navigation System

Car Navigation

Parking Navigation for Alleviating Congestion in Multilevel Parking Facility

Traffic congestion is a big social problem. Emission of the carbon dioxide by waste of fuel gives a bad influence to environment, and stagnation of the social activity by traffic congestion has a bad influence on economy. We focus on multilevel parking facility, and propose a navigation system in a parking facility that minimizes the parking time based on real-time occupancy information.

Finding a vacant parking space in a large crowded parking facility takes a long time. Many navigation methods are proposed for alleviating traffic congestion and/or shortening parking waiting time in a parking facility. However, most of these methods still have problems in practical effectiveness and installation. Moreover, in real environment, most of the methods do not work due to the low penetration ratio. For example, some well-known methods that detect the condition of parking facility by sensors and show the information to drivers by a billboard are utilized at some parking facilities. However, these methods provide the same information to all drivers and this leads to the situation where drivers make the same decision and go to the same parking zone, resulting in congestion of the zone.

In this research, we propose a navigation system taking installation cost and a penetration ratio into consideration. In the proposed method, a pre-installed �server in the parking facility collects data from the cars and estimates the occupancy of each parking zone. Then, the server sends the estimation to the cars in the parking facility. Based on this estimation, the cars that implement the proposed method provide drivers with a recommended route in the parking facility that minimizes the expected parking time. We conducted simulation-based evaluation of the proposed method using a realistic model representing a real parking facility in Nara, and a trace data taken at the facility. As a result, we confirmed that the proposed method reduced parking waiting time by 20%-70% even with low system penetration.


Tourism Navigation

P-Tour is our research project for a series of tourism scheduling and navigation methods.

The Original Version of P-Tour

In this research, we proposed a personal navigation system for tourism called P-Tour. When a tourist specifies multiple destinations with relative importance and restrictions on arrival/staying time, P-Tour computes the near-best schedule to visit part of those destinations. In addition to the map-based navigation, P-Tour provides temporal guidance according to the schedule, and automatically modifies the schedule when detecting the situation that the tourist cannot follow the schedule. We have developed a route search engine as a Java Servlet which can compute a semi-optimal schedule in reasonable time using techniques of genetic algorithms.

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Making Tour Schedule From Multiple Conflicting Preferences

In order to allow tourists to travel multiple destinations efficiently, we need a personal navigation system which computes and shows the best route to the next destination and facilitates composition of a schedule for visiting those destinations taking account of various requirements such as relative importance among destinations, time restrictions, travel expenses, and so on. There is sometimes a tradeoff between these requirements. In this paper, we extend our existing personal navigation system called P-Tour in the following two ways: (1) allowing users to optimize their tour schedules under multiple conflicting criteria such as total expenses and satisfaction degrees; and (2) navigating users to the next destination in more efficient way. We have implemented the above extensions and integrated them into P-Tour. Through some experiments, we show the effectiveness of the proposed extensions.

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Making Tour Schedule Considering Weather Forecast

People do sightseeing in their spare time to relax, and sightseeing is an important industry for some regions. The satisfaction of tourists critically depends on weather during their tours. In order to give people maximum satisfaction, we have to take care of the weather when planning a schedule. However, if there are many possible patterns for weather changes, the number of possible schedules will be very large, and in this case, it is difficult to find a good schedule. In this paper, we formulate the problem to compose schedules for probabilistically changing weather when the probability of future weather is given. We also propose an approximation algorithm for this problem based on the greedy search and the neighborhood search techniques. To evaluate the proposed method, we compare our method with Brute force method and a greedy method for an instance of Beijing sightseeing. As a result, the proposed method found the optimal solution in 6 sec, while the Brute force method took 16 hours. The proposed method composed a schedule whose expected satisfaction is 17.9% higher than that composed by the greedy method, for an instance with 20 destinations.

Implementation of P-Tour with Google Maps


P-Tour is a personal navigation system for sightseeing which automatically plans a tour schedule from information including time constraint and importance of each sightseeing spot input by users. It also has a function to navigate the user according to the schedule through a portable computing device. In this paper, we design and implement a web interface utilizing Google Maps API for P-Tour’s automatic schedule planning. With this interface, each user can intuitively select his/her favorite sightseeing spots and see the computed tour schedule through web browser. We also design and implement a function to automatically select a recommended accommodation. We report details of our design and implementation of P-Tour on Google Maps, and show better usability of our new interface.


  • Maruyama, A., Shibata, N., Murata, Y., Yasumoto, K. and Ito, M.: P-Tour: A Personal Navigation System for Tourism, Proc. of 11th World Congress on ITS (2004). [ PDF ]
  • Shiraishi, T., Nagata, M., Shibata, N., Murata, Y., Yasumoto, K. and Ito, M.: A Personal Navigation System with Functions to Compose Tour Schedules based on Multiple Conflicting Criteria, IPSJ Digital Courier, Vol.1, pp. 528-536 (2005). [ PDF ]
  • Kinoshita, T., Nagata, M., Shibata, N., Murata, Y., Yasumoto, K. and Ito, M.: A Personal Navigation System for Sightseeing across Multiple Days, Proc. of the 3rd Int'l. Conf. on Mobile Computing and Ubiquitous Networking (ICMU2006), pp. 254-259 (2006).[ PDF ]
  • Nagata, M., Shibata, N., Murata, Y., Yasumoto, K. and Ito, M.: A Method to Plan Group Tours with Joining and Forking, Proc. of SEAL2006, pp. 881-888 (2006) .[ PDF ]
  • Wu, B., Murata, Y., Shibata, N., Yasumoto, K., Ito, M.: A Method for Composing Tour Schedules Adaptive to Weather Change, Proc. of IEEE IV'09, pp. 1407-1412 (2009). [ PDF ]
  • Kenmotsu, M., Sun, W., Shibata, N., Yasumoto, K. and Ito, M. : "Parking Navigation for Alleviating Congestion in Multilevel Parking Facility," to appear in Proc. of 2012 IEEE 76th Vehicular Technology Conference (VTC2012-Fall).