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The current autonomous driving vehicles cannot collaborate with each other due to the disconnection of sensors between vehicles, which leads to poor performance in traffic efficiency and safety. Recently, with the development of wireless intelligent sensors, vehicular sensor network (VSN) is emerging to provide information sharing between vehicles, so that cooperative autonomous driving (CAD) can be enabled. This paper especially investigates the VSN-assisted straight-going CAD at urban intersections under the rule of traffic signals. First, the function of VSN is presented, and the information sharing mechanism is designed. Then distributed stop-and-go strategies with maintaining the optimal safety spacing between adjacent vehicles are proposed for multiple traffic cases. With the proposed strategies, every vehicle can get an exact time to decelerate or accelerate at signalized intersections. Finally, we use the model predictive control (MPC) scheme to actuate our strategies, and it is demonstrated that vehicles perform well in both passage safety and efficiency as expected. [ABSTRACT FROM AUTHOR]

The vehicular sensor network (VSN) is a bright candidate for many applications owing to its particular advantages. Such an application is air pollution monitoring, a critical issue associated directly with public health. We also notice that public transports are well-suited to deploy the network for this type of application. In this article, we propose a practical approach that leverages public buses to build the vehicle network with attached sensors for air pollution monitoring toward minimizing the deployment cost. Therefore, we hereafter call this problem vehicular sensor deployment (VSD). We first convert the VSD issue to a flow network described by a directed graph. Then, based on air sampling requirements, capacity constraints, and flow conservation of the flow network, we formulate the problem as an integer linear programming (ILP) model that yields the optimal solution. In addition, we suggest an approximation algorithm implemented by the linear programming relaxation technique combined with the randomized rounding algorithm (LPR-RRA), which provides approximate solutions to large-scale VSD problems. We also propose a greedy-based algorithm (GBA) to solve the problem against the most effective sampling in each iteration. Finally, we conduct experiments to evaluate the performance of the proposed algorithms as well as the influences of associated factors on the deployment cost. Simulation results show that the approximation algorithm approaches the optimal and outperforms the greedy. [ABSTRACT FROM AUTHOR]

In this article, we propose a cooperative fleet cruise control (CFCC) framework for collision avoidance and lane changing based on vehicular sensor networks. The proposed CFCC framework is designed for fleets to reduce the recovery time to get the intended speed back after sudden braking, which can improve the driving efficiency of fleets. In addition, CFCC can determine the critical safety spaces of car following and lane changing for fleet vehicles to avoid the accident of rear-end and side collisions due to emergency braking. Furthermore, fleet lane changing can be coordinated between fleet vehicles in the original lane and neighboring vehicles in the target lane for ensuring safety and improving efficiency. According to our review of relevant research, CFCC is the first fleet cruise control system to provide the following features: 1) extending the car following risk of individual vehicles to the fleet following risk of fleet vehicles; 2) minimizing the acceleration and deceleration of fleet vehicles to reduce the speed recovery time; and 3) coordinating individual cars and fleet vehicles to provide the sufficient lane changing space as soon as possible. Simulation results show that our framework outperforms existing car following and lane changing methods and can significantly improve the driving safety and recovery efficiency of fleets as emergency events occur. [ABSTRACT FROM AUTHOR]

In this paper, an integrity-oriented content offloading (ICO) problem with variable modulation and coding schemes is proposed for relay-assisted vehicular sensor network. To accurately describe the link duration properties, a finite-state Markov chain-based model is built by jointly considering the mobility and radio propagation characteristics. Considering the ICO problem is NP-hard, our solution divides it into two offloading sub-problems with direct link and relay-assisted path, respectively. These two sub-problems are solved heuristically, and the corresponding results are combined to achieve a near-optimal result as the ICO scheme. While the analytical model is validated by Monte Carlo simulations and chi-square goodness fit test, the performance of our proposed ICO scheme is verified through simulations and comparisons, showing that our ICO solution can reduce the integral content offloading time compared with two other selected schemes and an upper performance bound.

Vehicular sensor networks have been widely applied in intelligent traffic systems in recent years. Because of the specificity of vehicular sensor networks, they require an enhanced, secure and efficient authentication scheme. Existing authentication protocols are vulnerable to some problems, such as a high computational overhead with certificate distribution and revocation, strong reliance on tamper-proof devices, limited scalability when building many secure channels, and an inability to detect hardware tampering attacks. In this paper, an improved authentication scheme using certificateless public key cryptography is proposed to address these problems. A security analysis of our scheme shows that our protocol provides an enhanced secure anonymous authentication, which is resilient against major security threats. Furthermore, the proposed scheme reduces the incidence of node compromise and replication attacks. The scheme also provides a malicious-node detection and warning mechanism, which can quickly identify compromised static nodes and immediately alert the administrative department. With performance evaluations, the scheme can obtain better trade-offs between security and efficiency than the well-known available schemes. [ABSTRACT FROM AUTHOR]

Information dissemination in current Vehicular Sensor Networks (VSN) depends on the physical location in which similar data is transmitted multiple times across the network. This data replication has led to several problems, among which resource consumption (memory), stretch, and communication latency due to the lake of data availability are the most crucial. Information-Centric Networking (ICN) provides an enhanced version of the internet that is capable of resolving such issues efficiently. ICN is the new internet paradigm that supports innovative communication systems with location-independent data dissemination. The emergence of ICN with VSNs can handle the massive amount of data generated from heterogeneous mobile sensors in surrounding smart environments. The ICN paradigm offers an in-network cache, which is the most effective means to reduce the number of complications of the receiver-driven content retrieval process. However, due to the non-linearity of the Quality-of-Experience (QoE) in VSN systems, efficient content management within the context of ICN is needed. For this purpose, this paper implements a new distributed caching strategy (DCS) at the edge of the network in VSN environments to reduce the number of overall data dissemination problems. The proposed DCS mechanism is studied comparatively against existing caching strategies to check its performance in terms of memory consumption, path stretch ratio, cache hit ratio, and content eviction ratio. Extensive simulation results have shown that the proposed strategy outperforms these benchmark caching strategies.

Owing to the rising awareness of environmental protection and health, people put a high premium on air pollution in their living environment. It thus draws considerable attention to air quality monitoring in cities. The paper suggests using a vehicular sensor network (VSN) to tactically monitor metropolitan air quality and develops an efficient data gathering and estimation (EDGE) mechanism on VSN. EDGE has an objective to adaptively change data sampling rates of cars, such that the tradeoff between monitoring accuracy and communication cost is balanced. The monitoring accuracy is measured by the formal air quality index (AQI), whereas the communication cost considers the amount of sampling data and the monetary reward given to drivers. To do so, EDGE proposes dynamic grid partition based on the variation of pollutant concentration and computes the sampling rate by consulting car traffic in each grid. With the help of probabilistic reporting, it allows cars to collect air quality on more different positions and alleviate potential network congestion. Furthermore, EDGE applies the Delaunay triangulation to infer AQIs of the positions without any sensing data. Through simulation of urban mobility and industrial source complex, simulations are conducted based on practical metropolitan traffic and pollutant dispersion models. Experimental results demonstrate the significant effectiveness of the EDGE mechanism, under various scenarios. [ABSTRACT FROM AUTHOR]

Vehicular sensor networks have been widely applied in intelligent traffic systems in recent years. Because of the specificity of vehicular sensor networks, they require an enhanced, secure and efficient authentication scheme. Existing authentication protocols are vulnerable to some problems, such as a high computational overhead with certificate distribution and revocation, strong reliance on tamper-proof devices, limited scalability when building many secure channels, and an inability to detect hardware tampering attacks. In this paper, an improved authentication scheme using certificateless public key cryptography is proposed to address these problems. A security analysis of our scheme shows that our protocol provides an enhanced secure anonymous authentication, which is resilient against major security threats. Furthermore, the proposed scheme reduces the incidence of node compromise and replication attacks. The scheme also provides a malicious-node detection and warning mechanism, which can quickly identify compromised static nodes and immediately alert the administrative department. With performance evaluations, the scheme can obtain better trade-offs between security and efficiency than the well-known available schemes.

This paper proposes a lane-level beacon-less, infrastructure-less, and GPS-less cooperative collision avoidance (BIG-CCA) framework for preventing rear-end collisions. The BIG-CCA framework applies vehicular sensor networks to prevent chain vehicle collisions, which are common road accidents that occur when vehicles make sudden stops. BIG-CCA enables vehicles equipped with only onboard sensors to prevent such accidents. Based on extensive research, BIG-CCA is the first lane-level CCA solution that provides the following features: 1) BIG-CCA does not maintain a list of neighboring vehicles through beacons and, thus, the overall signaling overhead can be reduced to conserve bandwidth; 2) BIG-CCA does not use the GPS positions of vehicles to facilitate collision avoidance and, thus, the inaccuracy and unavailability of a GPS can be avoided; and 3) BIG-CCA does not rely on costly roadside infrastructures but employs only vehicle-to-vehicle communications to form warning groups for vehicles driving along in the same lane. BIG-CCA consists of a distributed grouping mechanism and a receiver-based forwarding scheme. Vehicles join or leave a warning group through only single-hop transmissions with the low overhead of group maintenance. When sudden braking occurs in a warning group, the proposed receiver-based forwarding scheme can specify a single forwarder without message contention. The performance of BIG-CCA is evaluated by conducting mathematical analysis and computer simulations, which outperform existing methods. An Android-based prototype is also implemented to verify the feasibility of BIG-CCA. [ABSTRACT FROM AUTHOR]

Constructing intelligent and efficient transportation systems for modern metropolitan areas has become a very important quest for nations possessing metropolitan cities with ever-increasing populations. A new trend is the development of smart vehicles with multiple sensors able to dynamically form a temporary vehicular ad hoc network (VANET) or a vehicular sensor network (VSN). Along with a wireless-enabled roadside unit (RSU) network, drivers in a VSN can efficiently exchange important or urgent traffic information and make driving decisions accordingly. In order to support secure communication and driver privacy for vehicles in a VSN, we develop a new identity-based (ID-based) signature based on the elliptic curve cryptosystem (ECC) and then adopt it to propose a novel conditional privacy-preserving authentication scheme based on our invented ID-based signature. This scheme provides secure authentication process for messages transmitted between vehicles and RSUs. A batch message verification mechanism is also supported by the proposed scheme to increase the message processing throughput of RSUs. To further enhance scheme efficiency, both pairing operation and MapToPoint operation are not applied in the proposed authentication scheme. In comparison with existing pseudo-ID-based authentication solutions for VSN, this paper shows that the proposed scheme has better performance in terms of time consumption. [ABSTRACT FROM PUBLISHER]

Information dissemination in current Vehicular Sensor Networks (VSN) depends on the physical location in which similar data is transmitted multiple times across the network. This data replication has led to several problems, among which resource consumption (memory), stretch, and communication latency due to the lake of data availability are the most crucial. Information-Centric Networking (ICN) provides an enhanced version of the internet that is capable of resolving such issues efficiently. ICN is the new internet paradigm that supports innovative communication systems with location-independent data dissemination. The emergence of ICN with VSNs can handle the massive amount of data generated from heterogeneous mobile sensors in surrounding smart environments. The ICN paradigm offers an in-network cache, which is the most effective means to reduce the number of complications of the receiver-driven content retrieval process. However, due to the non-linearity of the Quality-of-Experience (QoE) in VSN systems, efficient content management within the context of ICN is needed. For this purpose, this paper implements a new distributed caching strategy (DCS) at the edge of the network in VSN environments to reduce the number of overall data dissemination problems. The proposed DCS mechanism is studied comparatively against existing caching strategies to check its performance in terms of memory consumption, path stretch ratio, cache hit ratio, and content eviction ratio. Extensive simulation results have shown that the proposed strategy outperforms these benchmark caching strategies. [ABSTRACT FROM AUTHOR]