Analysis and adaptive optimization of vehicular safety message communications at intersections

Abstract

Safety-related applications in Vehicular Ad-hoc Networks (VANETs) can help to reduce the number of traffic accidents by periodically broadcasting Basic Safety Messages (BSMs). But considering that the density and topology of VANET change frequently, the Quality of Service (QoS) of safety applications with the fixed transmission parameters would not always meet the requirements of safety-related applications. In this paper, we firstly propose an analytical model to evaluate the performance of the BSM broadcast in VANET at the intersections. The effect of the traffic light is also taken into account by introducing the non-homogeneous Poisson process (NHPP) vehicle distribution, which is simulated by microscopic traffic simulator SUMO and validated by Kolmogorov-Smirnov (K-S) test. Secondly, the number of vehicles in the hidden terminal area and the concurrent transmission area need to be computed by complex integral computations for the proposed analytical model for evaluating the QoS of the safety applications, while the vehicle BSMs provide the vehicle location, speed, and transmission parameters, and these BSMs could be measured and collected in a timely manner to integrate into the analytical model to save the complex integral calculations. Based on the cross-validation QoS metrics between the NS2 (Network Simulator-ns-2) simulation and the analytical model, we employ the vehicle entity of the NS2 simulation model to represent the actual vehicle BSMs, to obtain the number of vehicles in the hidden terminal area and the concurrent transmission area. Finally, to maximize the transmission capacity and minimize the delay under the constraint of maintaining a high application-level QoS of safety applications, a multi-objective optimization scheme with Bare Bones Particle Swarm Optimization (BBPSO) is proposed to dynamically adjust multi transmission parameters. The accuracy of the proposed analytical model is validated by the NS2 simulation. The experimental results also show that the optimized ones could get better results compared with the real test-bed used transmission parameters. Furthermore, the comparisons with slotted-p(or 1)-persistent protocol and CSMA/CA with retransmission strategy show that the proposed solution could make VANET work with better performance at various vehicle densities.

Introduction

Vehicular Dedicated Short Range Communication (DSRC) system has been proposed to facilitate VANETs [1], [2], exchanging safety-related messages among vehicles to prevent potential traffic accidents. According to the US Department of Transportation (DOT), vehicle-to-vehicle (V2V) communication based on DSRC can address 79% of all crashes in the United States involving unimpaired drivers, which could save thousands of lives and billions of dollars [3]. Two classes of safety-related messages in VANETs have been designed to support various safety-related applications: BSMs in the US or cooperative awareness messages (CAMs) in Europe, and event-driven safety messages (ESMs) in the US or decentralized environmental messages (DENMs) in Europe. Vehicles periodically generate and transmit BSMs carrying the current state information of vehicles, such as position, velocity, direction, and so on. ESMs are generated when an abnormal or emergency event occurs, which is subject to the Poisson process.

Through BSMs, some safety-related applications could be enabled in VANETs, e.g., Cooperative Collision Warning (CCW) [4], Slow Vehicle Indication (SVI) [5], and Rear-end Chain Collision Warning (RCW) [6], etc. Since these applications on the road are about life and death, it is very critical for VANETs to support all safety applications with required reliability and performance under all possible vehicular environments and traffic loads. While BSMs and ESMs could get similar performance and reliability when they have the same average message generation intervals [7], the research method and conclusion based on BSMs in this paper can be further extended to ESMs.

VANETs communication could not guarantee a successful broadcast because of the imperfect channel and collision problem. Considering the hidden terminal problem, concurrent transmission and channel fading, various approaches have been deployed to investigate the reliability of VANETs (see Table 1) and formed some commonly used MAC-level QoS metrics, such as Packet Reception Probability (PRP), Packet Delivery Ratio (PDR) [8], and so on. However, the MAC-level QoS metrics may not be suitable for evaluating the safety-related applications, since different safety-related applications often have their own enabling areas and stringent QoS requirements [9]. To handle this, some general application-level (APP-level) metrics, such as awareness probability in the region of interest (ROI) [10] and APP-level delay [11], were developed to promote a rich VANETs evaluation system [12], [13], [14] that is closer to the users and facilitate designing and testing new performance improvement solutions [15], [16], [17]. The transmission capacity [18], [19] is another critical VANETs metric which could reflect the capability that the DSRC communication system could provide to the users [20]. A better transmission capacity could support more vehicles and a higher awareness update ratio. Currently the combination of the transmission capacity and the APP-level reliability has not been well studied in various VANETs scenario, including the signalized intersection, where almost half of all accidents occur each year [21].

In this paper, we propose an analytical and optimization framework for VANETs at a signalized rural intersections, aiming at meeting the QoS requirements of safety-related applications and maximizing transmission capacity and lower the application delay. There are mainly three challenges overcoming in order to apply our analytical and optimization framework for VANET to the actual scene. The first challenge here for building the model is to make the vehicle distribution close to the actual vehicle intersection scene. The Poisson point process of the vehicle locations is always used in the research on the highway scenario who is the most studied (see Table 1). However, it may not a suitable assumption at a traffic lights controlled intersection since the density of vehicles in different sections of the road may vary with the phases of the traffic lights. So we adopted the NHPP assumption of vehicle locations in the proposed analytical model. The intersection vehicle distribution is furthermore simulated by the microscopic traffic simulator SUMO [22] and the theoretical NHPP assumption has been verified to be reasonable via the K-S test.

The second challenge is to minimize the execution time with the help of real-time vehicle BSMs collection. In the analytical model, several critical intermediate parameters, which represent the number of vehicles used to evaluate the impact of the hidden terminal problem and the concurrent collisions, are obtained by the time-consuming operation of integrating the density in the piecewise integral region as shown in the Section 3.1 and the Section 3.2. Considering that the number of vehicles can be directly calculated according to the vehicle BSMs in an actual measurement system, hence the vehicle BSMs of simulation model could also be used to inject into the analytical model to replace the complex integral computations due to the cross-validations between the NS2 and the proposed analytical model. We extend the idea to be a combined measurement and analytical (CMA) model given in the Section 3.4, and the characteristics of fast operation as shown in the Section 5.3 pave the way to apply our proposed optimization scheme in the real-world system.

The third challenge we faced is that the fixed transmission parameters may not always meet the requirements of QoS of safety-related applications because the VANETs topology (e.g. vehicle density, vehicle position) could change frequently. We build the optimization problem aiming at maximizing the transmission capacity of VANETs and maintaining the QoS to meet the requirement of safety-related applications by adaptively adjusting the transmission parameters. There are a couple of parameters that could be adjusted, and the number of their combinations would be enormous, so it is feasible to apply a heuristic algorithm to solve the problem. We apply BBPSO [23] algorithm because no parameters need to be predefined, which could introduce less influence of human factor compared with other heuristic-based algorithms when the hyper-parameters are tuning (such as, simulated annealing, ant colony optimization and so on).

Our proposed analytical and optimization framework could be utilized to analyze the QoS of VANET, reduce the execution time by combining measurements with the analytical model, and ensure the QoS at topology changing environment by multi-parameter optimization. The proposed model and optimization method are general and fit for many actual scenes. There are several popular approaches proposed in the literature to improve the reliability and performance of broadcast, such as retransmission [24], [25], [26], [27], slotted-1-persistent, and slotted-p-persistent [28]. We compare these approaches by the Network Simulator NS2 2.35 [29] with the modified wireless model provided by Chen et al. [30]. For each solution, the APP-level reliability metrics and delay are calculated from the trace file. The details of the simulation set up and the results will be presented in Section 5.6. The major contributions of this paper are three-fold:

• We propose an analytical model to evaluate the MAC-level and APP-level performance of BSM-based safety-related services at the signalized intersection by considering the impact of the hidden terminal, concurrent collisions, and the fading channel. The effect of the traffic light is considered by giving a more general non-homogeneous Poisson point (NHPP) distribution.

• The microscopic traffic simulator SUMO is adopted to mimic the vehicle intersection scene, and the analytical model NHPP assumption is verified via the K-S test accordingly. The BSMs in the communication measurement system could be used to replace the complex integration process for obtaining the QoS metrics, and reduce the optimization time of the analytical model, thus make our analytical optimization model more adaptable to the practical vehicle DSRC system.

• To maintain the reliability of safety-related applications in a highly dynamically changed vehicular environment, we propose a multi-objective adaptive optimization scheme based on BBPSO to adjust transmission parameters with the QoS constraint transmission capacity according to the topology of VANETs.

The remainder of this paper is organized as follows. The related works and background knowledge are introduced in Section 2. In Section 3, an analytical model and its implementation in the real scenario are proposed to characterize the MAC-level and APP-level broadcast reliability of IEEE 802.11p based VANETs at intersections with a non-homogeneous Poisson process (NHPP) vehicle distribution. The definition of QoS constraint transmission capacity and the bare bones PSO based multi-objective optimization scheme are given in Section 4. The experiments and the comparison with other protocols or strategies are shown in Section 5 and the paper is concluded in Section 6.