Panichpapiboon, Sooksan
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Panichpapiboon, Sooksan
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sooksan.pa@kmitl.ac.th
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Item type:Publication, Irresponsible forwarding under general inter-vehicle spacing distributions(2011-08-12)Typically, vehicles in a self-organizing traffic information system distribute the information by rebroadcasting. Rebroadcasting results in redundant retransmission of the same information packet, leading to a useless occupation of the radio channel. Minimizing redundancy, while still guaranteeing complete reachability throughout the network, is a challenging task in multi-hop broadcasting. In our previous work, we introduced a new probabilistic-based broadcasting scheme, called Irresponsible Forwarding (IF), which could reduce the redundancy effectively. However, in the previous work, we only considered the scenario where the inter-vehicle spacing was exponentially distributed. In this paper, we generalize the concept of IF such that it can be applied to any inter-vehicle spacing distribution. © 2011 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A review of information dissemination protocols for vehicular ad hoc networks(2012-01-01); Pattara-Atikom, WasanWith the fast development in ad hoc wireless communications and vehicular technology, it is foreseeable that, in the near future, traffic information will be collected and disseminated in real-time by mobile sensors instead of fixed sensors used in the current infrastructure-based traffic information systems. A distributed network of vehicles such as a vehicular ad hoc network (VANET) can easily turn into an infrastructure-less self-organizing traffic information system, where any vehicle can participate in collecting and reporting useful traffic information such as section travel time, flow rate, and density. Disseminating traffic information relies on broadcasting protocols. Recently, there have been a significant number of broadcasting protocols for VANETs reported in the literature. In this paper, we classify and provide an in-depth review of these protocols. © 2012 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Time-headway distributions on an expressway: Case of bangkok(2015-01-01)Traffic flow modeling is one of the fundamental keys to solving a traffic engineering problem. Among many parameters, time headway is frequently used to model traffic flow characteristics. A statistical analysis of time headways is immensely important to both theoretical traffic modeling and simulation-based traffic modeling. Basically, it allows researchers to describe an inherently random pattern of traffic flows. Past studies have mainly focused on the time headways of vehicles on highways, freeways, and arterials. However, studies of time headways on urban expressways are rather limited and still need further investigation. In this paper, the author investigates and characterizes the time-headway distributions of vehicles traveling on an urban expressway in Bangkok, Thailand. Particularly, the exponential distribution, the lognormal distribution, and the generalized extreme value (GEV) distribution are used to model the time headways. It is found that the GEV distribution is most effective in modeling time headways. In fact, the GEV distribution can describe more than 90% of the empirical distributions on most lanes and sections of the expressway. On the other hand, the exponential distribution is the least effective distribution. It can only describe the empirical distributions during the periods when the traffic is extremely light. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Irresponsible forwarding under real intervehicle spacing distributions(2013-01-01); Cheng, LinOne approach to the distribution of traffic information in a self-organizing traffic information system is multihop broadcasting. In this approach, each vehicle may simply rebroadcast an information packet that it receives from the others. However, rebroadcasting results in redundant retransmissions of the same information, leading to a useless occupation of the radio channel. Minimizing redundancy, while still guaranteeing reachability in the network, is a challenging task in multihop broadcasting. In our previous work, we introduced a new probabilistic-based broadcasting scheme, i.e., Irresponsible Forwarding (IF) , which could effectively reduce the redundancy. However, in the previous work, we only considered the scenario where the intervehicle spacing was exponentially distributed. In this paper, we generalize the concept of IF such that it can be applied to any intervehicle spacing distribution. In addition, we evaluate the performance of the IF protocol when it is applied in a realistic scenario (i.e., using real traffic traces). This paper shows that the IF protocol is able to limit packet redundancy all hours of the day effectively. © 1967-2012 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Effective variables for urban traffic incident detection(2016-01-18); Chaovalit, PimwadeePast studies on automatic traffic incident detection have mainly focused on the incidents on freeways, which are controlled-access roads. There are not many works on urban traffic incident detection. In addition, the traffic data used in detecting an incident are still mostly collected from fixed sensors such as loop detectors. With the advances in mobile sensing and vehicular technology, it is foreseeable that mobile sensors will be used increasingly in the near future. In fact, traffic data will be collected directly by vehicles. Detecting traffic incidents in an urban road network with the traffic data collected by mobile sensors poses several challenges. First, the urban roads are uncontrolled-access roads, which are typically full of flow-disruptive entities such as traffic signals, intersections, crossings, bus stops, etc. These entities can disrupt the traffic flow in a similar way that an incident does, making it more difficult to detect an incident. Second, it is still not clear which traffic variables, collected by mobile sensors, can be used in detecting an incident in an urban environment. In this paper, we investigate and identify the traffic variables that are effective in detecting an incident in an urban road network. Particularly, speed, acceleration, lane-change ratio and travel time are studied. The results show that these four traffic variables are generally effective for traffic incident detection. However, among the four variables, the least effective one is the travel time. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Exploiting wireless communication in vehicle density estimation(2011-07-01); Pattara-Atikom, WasanVehicle density is one of the main metrics used for assessing road traffic condition. High vehicle density indicates that traffic is congested. Currently, most vehicle density estimation approaches are designed for infrastructure-based traffic information systems. These approaches require detection devices such as inductive loop detectors or traffic surveillance cameras to be installed at various locations. Consequently, they are not appropriate for an emerging self-organizing vehicular traffic information system, where vehicles have to collect and process traffic information without relying on any fixed infrastructure. In this paper, we consider a few methods for estimating vehicle density based on the number of vehicles in the vicinity of the probe vehicle and the number of vehicles in a communication cluster. © 2011 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Effects of intervehicle spacing distributions on connectivity of VANET: A case study from measured highway traffic(2012-10-11) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Incidents detection through mobile sensing(2016-09-06); Chaovalit, PimwadeeCurrently, most automatic traffic incident detection systems rely heavily on data collected from fixed sensors such as inductive loop detectors and surveillance cameras. However, fixed sensors are difficult to install and maintain. Moreover, it is quite costly to deploy a large number of fixed sensors to cover a broad area. It is potentially more efficient to use vehicles as mobile sensors to collect traffic data. In this paper, we introduce a new traffic incident detection algorithm which takes advantage of mobile sensors. This algorithm assesses the likelihood of an incident based on the speed data collected by the mobile sensors. Its performance is evaluated thoroughly, in terms of detection rate, false-alarm ratio, and mean time-to-detection, at various combinations of penetration rates and data sampling periods. The results show that the proposed detection algorithm is potentially promising. For a practical scenario with 10% penetration rate and 30-second sampling period, the algorithm is able to achieve around 80% detection rate. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Clearance Estimation through Mobile Sensing(2018-08-21) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Speed estimation through mobile sensing(2015-01-26)