Zhexin Xu

Bio: Zhexin Xu is an academic researcher from Fujian Normal University. The author has contributed to research in topics: Vehicular ad hoc network & Time division multiple access. The author has an hindex of 4, co-authored 12 publications receiving 74 citations.

Research on car-following model based on SUMO

Abstract: Vehicular Ad Hoc Network (VANET) is a promising platform for the Intelligent Transportation System (ITS). Car-following theory is a significant research direction in the field of VANET, it describes the one-by-one following process of vehicles on the same lane in traffic flow. The paper analyzed Krauss car-following model and proposed a new model based on the speed safe and Krauss model in SUMO 0.21.0 platform to improve the authenticity of model. We implement it on the SUMO platform. This model considers the movement state of the car and the gradual process of deceleration in vehicles braking. Simulation experimental results show the superiority of new model over other ones in simulation that models real streets. It achieves good results in wait time, travel time, lane-change number and safe speed.

Adaptive multichannel MAC protocol based on SD‐TDMA mechanism for the vehicular ad hoc network

Abstract: In this study, the design of an adaptive medium access control (MAC) protocol based on the space-division–time-division multiple access (SD-TDMA) mechanism is presented to improve the utilisation and fairness of the time-slot allocation scheme in the vehicular ad hoc network. The SD-TDMA mechanism dynamically allocates time-slots owing to a dynamic topology. This protocol reduces transmission collisions through user detection procedures. Most users can thus access the service channel (SCH) without conflict and acquire time slots according to the mapping between geographic locations and time slots. Users failing to access the channel in user detection procedures can send request access packets in security channels to again participate in SCH time-slot allocation during the SCH interval. Simulations are conducted to evaluate the performance of the proposed method in urban scenarios. The SD-TDMA mechanism is compared with an SDMA-based MAC protocol, the IEEE 802.11p distributed coordination function and an MAC protocol based on transmission sequences. Owing to the decreased rate of transmission collisions and the dynamic time-slot allocation scheme, it is shown that the SD-TDMA mechanism provides a significantly higher utilisation of time slots and better fairness of data transmission than existing approaches.

AODV-PNT: An improved version of AODV routing protocol with predicting node trend in VANET

Abstract: In this paper, According to the topology characteristics of VANET, We proposed a new routing protocol that is suitable for VANET communications within the cluster based on AODV: AODV with predicting node trend (AODV-PNT). There are two major improvements in AODV-PNT: (1) Routing metric improvements and calculate Total Weight of the Route (TWR). (2) Predict node's future TWR and calculate stable threshold W in a bid to choose a suitable relay node. Finally, we simulated AODV-PNT using ns2. The simulation results show that AODV-PNT is able to achieve better routing performances in packet deliver ratio, average end-to-end delay and routing overheads as compared to AODV.

Improved lane-changing model for vanets in SUMO

Abstract: As an important branch of mobile Ad Hoc network technology, Vehicular Ad hoc Network (VANET) is a promising technology in Intelligent Transportation Systems (ITS). It is required to evaluate any VANET design which the simulator with vehicular mobility model should be more realistic. In order to improve the authenticity of vehicular mobility model, the paper analyzed JE2013 lane-changing model in SUMO and proposes a new model based on the JE2013 model. The new model takes into account motorway scene, and analyzes the change of vehicle velocity and calculates the position coordinate after lane-changing which based on speed limitation per lane on motorway. By implementing the new model in SUMO platform and carrying out experiments for the two models under the same situation. Simulation experimental results indicate that the new model is more reality and has better performance on several parameters, such as travel time of vehicle and the lane-changing times, etc.

A novel MAC protocol for VANET based on Improved Generalized Prime Sequence

Abstract: Protocol sequences are used for multiple access in the collision channel without feedback In order to increase inter-cluster packet delivery radio in cluster-based VANETs, a MAC protocol based on Improved Generalized Prime Sequence (IGPS) is proposed in this paper Extra transmitting time slots are inserted in Generalized Prime Sequence (GPS) of cluster heads while the corresponding positions in GPS of cluster members are inserted with extra receiving time slots Compared to the MAC protocol based on GPS, the proposed MAC protocol guarantees the inter-cluster data transmission when the conflict occurred between inner-cluster and inter-cluster communication Numerical results illustrate that the performance of IGPS-based scheme is superior to GPS-based one in terms of packet delivery ratio and throughput in the inter-cluster communication

Trajectory planning and tracking control for autonomous lane change maneuver based on the cooperative vehicle infrastructure system

Abstract: Autonomous lane change maneuver was developed using cooperative strategy.Proposed system can be potential to prevent lane change crashes and thus reducing injuries and fatalities.A trajectory planning method based on polynomial was developed.A trajectory tracking controller with global convergence ability was designed.Simulations and experimental results were presented to validate the method. Lane change maneuver is one of the most conventional behaviors in driving. Unsafe lane change maneuvers are key factor for traffic accidents and traffic congestion. For drivers' safety, comfort and convenience, advanced driver assistance systems (ADAS) are presented. The main problem discussed in this paper is the development of an autonomous lane change system. The system can be extended applied in intelligent vehicles in future. It solves two crucial issues - trajectory planning and trajectory tracking. Polynomial method was adopted for describing the trajectory planning issue. Movement of a host vehicle was abstracted into time functions. Moreover, collision detection was mapped into a parameter space by adopting infinite dynamic circles. The second issue was described by backstepping principle. According to the Lyapunov function, a tracking controller with global convergence property was verified. Both the simulations and the experimental results demonstrate the feasibility and effectiveness of the designed method for autonomous lane change.

Big Data Analytics for Emergency Communication Networks: A Survey

Abstract: Disaster management is a crucial and urgent research issue. Emergency communication networks (ECNs) provide fundamental functions for disaster management, because communication service is generally unavailable due to large-scale damage and restrictions in communication services. Considering the features of a disaster (e.g., limited resources and dynamic changing of environment), it is always a key problem to use limited resources effectively to provide the best communication services. Big data analytics in the disaster area provides possible solutions to understand the situations happening in disaster areas, so that limited resources can be optimally deployed based on the analysis results. In this paper, we survey existing ECNs and big data analytics from both the content and the spatial points of view. From the content point of view, we survey existing data mining and analysis techniques, and further survey and analyze applications and the possibilities to enhance ECNs. From the spatial point of view, we survey and discuss the most popular methods and further discuss the possibility to enhance ECNs. Finally, we highlight the remaining challenging problems after a systematic survey and studies of the possibilities.

Smart vehicle monitoring and assistance using cloud computing in vehicular Ad Hoc networks

Abstract: The increasing number of on road vehicles has become a major cause for congestion, accidents and pollution. Intelligent Transportation Systems (ITS) might be the key to achieve solutions that help in reducing these problems significantly. The connected vehicular networks stream is a rapidly growing field for research and development of various real-time applications. In this paper, novel techniques have been proposed to serve the speed based lane changing, collision avoidance and time of arrival (TOA) based localization in Vehicular Ad Hoc Networks (VANETs). As GPS requires clear line-of-sight for accurate services of positioning and localization applications, we designed a Time of Arrival (ToA) based algorithm for areas where strong GPS signals are unavailable. Collision avoidance using automatic braking and camera-based surveillance are a few other applications that we addressed. The feasibility and the viability of the algorithms were demonstrated through simulations in Simulation of Urban Mobility (SUMO) and Network Simulator-2 (NS-2). We prototyped a working hardware and tested it on actual vehicles to assess the effectiveness of the proposed system. We designed a mobile app interface for the on-board unit for smart, efficient and remote traffic monitoring. The integrated VANET Cloud Computing architecture acts as the platform for the proposed applications.

Matching-Based Task Offloading for Vehicular Edge Computing

Abstract: Vehicular edge computing has emerged as a promising technology to accommodate the tremendous demand for data storage and computational resources in vehicular networks. By processing the massive workload tasks in the proximity of vehicles, the quality of service can be guaranteed. However, how to determine the task offloading strategy under various constraints of resource and delay is still an open issue. In this paper, we study the task offloading problem from a matching perspective and aim to optimize the total network delay. The task offloading delay model is derived based on three different velocity models, i.e., a constant velocity model, vehicle-following model, and traveling-time statistical model. Next, we propose a pricing-based one-to-one matching algorithm and pricing-based one-to-many matching algorithms for the task offloading. The proposed algorithm is validated based on three different simulation scenarios, i.e., straight road, the urban road with the traffic light, and crooked road, which are extracted from the realistic road topologies in Beijing and Guangdong, China. The simulation results confirm that significant delay decreasing can be achieved by the proposed algorithm.