Dynamic Traffic Environment Research Articles

Cloud Computing for Agent-Based Urban Transportation Systems

Agent-based traffic management systems can use the autonomy, mobility, and adaptability of mobile agents to deal with dynamic traffic environments. Cloud computing can help such systems cope with the large amounts of storage and computing resources required to effectively use of traffic strategy agents and mass transport data. This article reviews the history of the development of traffic control and management systems within the evolving computing paradigm and shows the state of traffic control and management systems based on mobile multiagent technology. An intelligent transportation cloud could provide services such as decision support, a standard development environment for traffic management strategy, and so on. Moreover, the cloud can generate, store, manage, test, optimize, and use mobile traffic strategy agents to maximize advantages of cloud computing and agent technology to effectively control and manage urban-traffic systems.

Research and Development on Individual Virtual Intelligent Vehicles

Aimed at the individual virtual intelligent vehicles, the individual vision behavior and decision-making behavior of virtual intelligent vehicles are mainly studied. The vision perception picture and fuzzy neural networks decision-making picture are developed and the virtual intelligent vehicles on the platform of dynamic intelligent traffic environment have been built by use of the EONSDK. It not only has improved the reality of traffic environment, and but also can make out the different traffic environment and can simulate various road accident circumstances.

Dynamic accessibility analysis in location-based service using an incremental parallel algorithm

Accessibility analysis usually requires finding the closest facility within a certain category—for example, the nearest hotel, hospital, or gas station. Along with the development of location-based services, users also wish to find the optimal route to the closest facility, based on network distance. Furthermore, the best route should be adjusted in a dynamic traffic environment. Most traditional methods solve the nearest-neighbor (facility) problem using Euclidian distance or network distance without consideration of dynamic traffic conditions. In this paper we propose a novel incremental parallel Dijkstra's algorithm, IP-Dijkstra, to construct and maintain a dynamic network Voronoi diagram for time-dependent traffic networks. The experimental results demonstrate that the proposed IP-Dijkstra's algorithm considerably outperforms the traditional methods, which recompute the shortest path from scratch without utilization of the previous search results. Consequently, this algorithm is capable of accommodati...

A function-centred approach to joint driver-vehicle system design

Throughout the history of human-machine systems design has had a technological bias in the sense that design for technology came first with design for humans as a distant second. Over the years this situation became untenable because the growing system complexity made a decomposition approach to design inadequate. Seeing that technology-centred design had failed, the pendulum swung to the other side taking the human as the centre of things. Yet human-centred design is just as inadequate as machine-centred design, since it implies a dichotomy where one part of the system is seen as opposed to the other. This applies not least to the case of automotive environments, where the interaction has a clear purpose, namely safety to negotiate the traffic. Design should therefore embrace a function-centred view where the focus is the joint driver-vehicle system. Design should serve to further the purposes or goals of the joint system, i.e., to be in control vis-a-vis the dynamic traffic environment, by taking the relative strengths and limitations of the components into account and by describing the system on multiple levels.

TOPOLOGY CONTROL IN AD HOC NETWORKS: A MAC LAYER SOLUTION

In ad-hoc networks the need for a distributed topology control algorithm is being widely recognized. In this paper we propose TC-ADHOC MAC, a medium access algorithm with topology control capabilities. The proposed algorithm aims at maintaining the minimum number of bidirectional neighbors of any wireless terminal very close to a certain connectivity threshold. The correctness of the algorithm is evaluated through detailed simulation and several test on the impact of different algorithm parameters are carried out in static network scenarios. Furthermore, the ability of TC-ADHOC MAC of reusing the radio resources is assessed by a detailed simulation in a dynamic traffic environment. Our results show that the topology control solution integrated at the MAC layer helps increasing the channel reuse and, consequently, the network efficiency.

Optimal Resource Allocation and Adaptive Call Admission Control for Voice/Data Integrated Cellular Networks

Resource allocation and call admission control (CAC) are key management functions in future cellular networks, in order to provide multimedia applications to mobiles users with quality of service (QoS) guarantees and efficient resource utilization. In this paper, we propose and analyze a priority based resource sharing scheme for voice/data integrated cellular networks. The unique features of the proposed scheme are that 1) the maximum resource utilization can be achieved, since all the leftover capacity after serving the high priority voice traffic can be utilized by the data traffic; 2) a Markovian model for the proposed scheme is established, which takes account of the complex interaction of voice and data traffic sharing the total resources; 3) optimal CAC parameters for both voice and data calls are determined, from the perspective of minimizing resource requirement and maximizing new call admission rate, respectively; 4) load adaption and bandwidth allocation adjustment policies are proposed for adaptive CAC to cope with traffic load variations in a wireless mobile environment. Numerical results demonstrate that the proposed CAC scheme is able to simultaneously provide satisfactory QoS to both voice and data users and maintain a relatively high resource utilization in a dynamic traffic load environment. The recent measurement-based modeling shows that the Internet data file size follows a lognormal distribution, instead of the exponential distribution used in our analysis. We use computer simulations to demonstrate that the impact of the lognormal distribution can be compensated for by conservatively applying the Markovian analysis results.

Wavelength routing with spare reconfiguration for all-optical WDM networks

This study presents a wavelength-routing scheme with spare reconfiguration (SR) to construct dependable all-optical wavelength-division-multiplexing (WDM) networks. Path protection using shared spare lightpaths is a general wavelength-routing method for reducing blocking probability while minimizing demand for spare resources. However, in a dynamic traffic environment, this method may still yield a poor performance because a wavelength on a link is very likely to be continuously held by a spare lightpath and to be unable to be assigned to the working lightpath of a new connection. This study develops a spare reconfiguration mechanism with wavelength reassignment (SR/spl I.bar/WR) and path reassignment (SR/spl I.bar/PR) to make the spare dynamic and thus further reduce the blocking probability. The proposed wavelength routing with SR proceeds in three stages and has polynomial time complexity. Extensive simulation experiments were conducted on the NSFNET and the K5 fully connected network to investigate the performance of the proposed wavelength routing with SR. Results of this study show that the proposed wavelength routing with SR can reduce the blocking probability compared with the general wavelength routing with just shared spare lightpaths by choosing a positive tuning cost. In addition, the improvement of the blocking performance is maximized when using SR/spl I.bar/WR followed by SR/spl I.bar/PR.

Exploring Drivers' Situation Awareness in a Dynamic Traffic Environment

The change detection paradigm was used in a single-monitor driving simulator to study drivers' awareness of other vehicles on the roadway. While driving, a moving or parked vehicle ahead (30 or 60 m) would occasionally change location (30% or 60% nearer or farther away), color, or identity during a 150 ms blank-out period. The results showed that only for moving vehicles with a very large location displacement (60%) can the participants detect changes as well as with the color or identity change. We also examined how the driving task itself influences the formation of this representation; overall, the detection performance was better in the non-driving condition. We argue that vehicle location is coarsely represented in drivers' memory, and that this, together with vehicle features, is used to visually monitor more finegrained location information. This helps explain why drivers often fail to notice a decreasing distance to the car ahead, resulting in rear-end collisions.

Influence of a Driver Support System on Situation Awareness and Information Processing in Response to Lead Vehicle Braking

Situation Awareness (SA) is critical to safe driving in a dynamic traffic environment. SA is predicated on the timely sampling of information in the driving environment. Distraction from secondary tasks can interrupt this sampling resulting in increased traffic conflicts and crashes. It is hypothesized that SA may be improved if sampling is augmented with (redundant) non-visual feedback about relevant information in the driving scene. The current study examined a Driver Support System (DSS) based on continuous haptic feedback communicated through the gas pedal. This system was evaluated in a driving simulator with participants distracted by a secondary task utilizing the CD player. The results indicate that this DSS improved reaction time, response time, and response appropriateness (safety margin) despite an apparent increase in the transition period between pedals. Various mechanisms to explain these effects are posited.

A comprehensive study on next-generation optical grooming switches

This paper investigates the characteristics and performance of different optical grooming switches, i.e., optical cross-connects (OXCs) capable of traffic grooming, under a dynamic traffic environment. We present four optical grooming-OXC architectures, namely, single-hop grooming OXC, multihop partial-grooming OXC, multihop full-grooming OXC, and light-tree-based source-node grooming OXC. After exploring their grooming capabilities, we propose three grooming schemes and two corresponding algorithms, grooming using auxiliary graph and grooming using light-tree. Through the algorithms, we evaluate the performance of different optical grooming OXCs in a dynamic traffic environment under different connection bandwidth-granularity distributions. Our investigation uncovers the following results: (1) the multihop full-grooming OXC can achieve the best network performance, but it may encounter cost and scalability constraints; (2) by using significantly less low-granularity electronic processing and intelligent traffic-grooming algorithms, the multihop partial-grooming OXC shows reasonable network performance and, hence, can be viewed as a cost-effective alternative when a network node does not require full-grooming capability; (3) the single-hop grooming OXC may cause a large amount of capacity waste and lead to poor network performance; and (4) through its multicast capability, a light-tree-based source-node grooming OXC can significantly out-perform the performance of a single-hop grooming OXC in terms of network throughput and network resource efficiency. From our results, we also observe that the connection bandwidth-granularity distribution has a large impact on network throughput and network resource efficiency and, therefore, should be carefully considered for network design and traffic provisioning.

동적 교통 시스템의 인지공학적 평가에 관한 연구

The road sign in dynamic traffic system is an important element which affects on human cognitive performance on driving. Web-based vision system simulator was developed to examine the cognition time of the road sign in dynamic environment. This experiment was designed in within-subject design with two factors: vehicle speed and the amount of information of the traffic sign. It measured the cognition time of the road sign through two evaluation methods: the subjective test with vision system simulator and computational cognitive model. In these two evaluations of human cognitive performance under the dynamic traffic environment. It demonstrated that subject`s cognition time was affected by both the amount of information of traffic sign and driving speed.

Toward vision-based intelligent navigator: its concept and prototype

Proposes a novel concept of an intelligent navigator that can give a driver timely advice on safe and efficient driving. From both the current traffic conditions obtained from visual data and the driver's goals and preferences in driving, it autonomously generates advice and gives it to the driver. Not only can operational-level advice be generated, such as emergency braking due to an abrupt deceleration of the vehicle in front, but also tactical-level advice, such as lane changing due to a congested situation ahead. Two main components of the intelligent navigator - the advice generation system and the road scene recognition system - are explained. A three-level reasoning architecture is proposed for generating advice in dynamic and uncertain traffic environments. Online experiments using the prototype system show the potential feasibility of the proposed concept.

On the use of stochastic estimator learning automata in time division multiple access systems: A methodology

Due to its fixed assignment nature, the well-known TDMA protocol suffers from poor performance when the offered traffic is bursty. In this paper, a new time division multiple access protocol which is capable of operating efficiently under bursty traffic conditions is introduced. According to the proposed protocol, the station which grants permission to transmit at each time slot is selected by means of stochastic estimator learning automata. The system which consists of the automata and the network is analyzed and it is proved that the probability of selecting an idle station asymptotically tends to be minimized. Therefore, the number of idle slots is drastically reduced and consequently, the network throughput is improved. Furthermore, due to the use of a stochastic estimator, the automata are capable of being rapidly adapted to the sharp changes of the dynamic bursty traffic environment. Extensive simulation results are presented which indicate that the proposed protocol achieves a significantly higher performance than other well-known time division multiple access protocols when operating under bursty traffic conditions.