Chetan Belagal Math

Data Rate based Congestion Control in V2V communication for traffic safety applications

Vehicle-to-Vehicle (V2V) communication systems intend to increase safety and efficiency of the transportation networks. At high vehicle density, the communication channel may become congested, impairing the reliability of the safety applications. As a counter measure, the European Telecommunications Standard Institute (ETSI), proposes the Decentralized Congestion Control (DCC) framework to control the channel load, by tuning message transmission parameters, such as message rate and transmitting power. In this paper, we analyze a congestion control scheme that follows the DCC framework known as Data Rate-DCC (DR-DCC) for various traffic densities. DR-DCC adjusts the data rate based on channel load measurements thus controlling the air time of packets to avoid congestion. Although tuning the data rate has been proposed before we are not aware of any reported work, where its full potential has been investigated in detail. In this paper we intend to provide more insight on the benefits of this approach by analyzing schemes that aim at optimum data rate for various traffic density cases. The objective is not only to avoid congestion but also to provide optimal support to safety applications. We compare the performance of DR-DCC to another DCC approach based on adjusting transmit power for various traffic density cases. DR-DCC outperforms at various traffic densities providing better support to safety applications.

Fair decentralized data-rate congestion control for V2V communications

Channel congestion is one of the most critical issues in IEEE 802.11p-based vehicular ad hoc networks because congestion may lead to unreliability of applications. As a counter measure, the European Telecommunications Standard Institute (ETSI), proposes a mandatory Decentralized Congestion Control (DCC) framework to control the channel load. DCC algorithms are proposed to tune parameters such as message-rate, data-rate, etc. to avoid congestion. An important requirement for DCC algorithms is fairness, which ensures that vehicles experiencing similar channel loads are entitled to similar transmission parameters, in particular, message-rate and data-rate. Message-rate DCC (LIMERIC) ensures a fair message-rate selection, while data-rate DCC (DR-DCC) might end up with different data-rates, creating unfairness among the vehicles: vehicles with lower data-rate have a larger communication range than those using higher data-rates. Therefore some vehicles are less visible than others, which is detrimental to the reliability of the safety applications. To avoid this, the paper defines a novel packet-count based decentralized data-rate congestion control algorithm (PDR-DCC), which enforces fairness and hence improves the application-reliability. Simulation studies are performed to demonstrate that PDR-DCC avoids congestion in a fair manner. We also show the effect of fairness on the application-reliability by comparing the performance of PDR-DCC with message-rate (LIMERIC) and data-rate (DR-DCC) congestion control algorithms for a stationary vehicle warning application in a synthetic highway scenario and for various vehicular densities. We conclude that PDR-DCC outperforms LIMERIC, and DR-DCC in terms of application-reliability.

Risk Assessment for Traffic Safety Applications with V2V Communications

Vehicle-to-others (V2X) communication systems intend to increase safety and efficiency of our transportation networks. However, wireless communication imperfections such as missed messages due to collisions and fading in the wireless channel, may affect safety application reliability and lead to risky situations. Thus metrics are required to evaluate the impact of communication inadequacies on the safety applications. In this paper we perform analyses of various existing safety application reliability metrics and conclude that they do not reflect safety application risk and vulnerability of individual nodes effectively. We propose a new metric called Effective Risk Factor (ERF), which quantifies the risk at a node for each link, to identify dangers due to poor awareness of their neighbors. The ERF evaluation considers links of its neighbors, thus detecting risky situations over existing neighbor links on runtime making the ERF assessment realistic. The ERF metric is evaluated and compared with other reliability metrics for a stationary vehicle warning application in a simulated highway scenario. The results show that the ERF evaluation performed at each node on runtime is able to capture a fine time scale fluctuations in the risk experienced by an application precisely. The ERF also enables prediction of higher risk situations. The results also demonstrate that the ERF captures application risk experienced by nodes effectively compared to other reliability metrics.

V2X Application-Reliability Analysis of Data-Rate and Message-Rate Congestion Control Algorithms

Intelligent transportation systems (ITS) require vehicle-to-everything communication. In dense traffic, the communication channel may become congested, impairing the reliability of the ITS safety applications. Therefore, the European Telecommunications Standard Institute demands decentralized congestion control (DCC) to control the channel load. Our objective is to investigate whether message-rate or data-rate congestion control provides better application reliability. We compare LIMERIC and PDR-DCC as representatives of the two principles. We analyzed the application reliability of LIMERIC with different data-rates and PDR-DCC with different message-rates for varying traffic densities and application requirements. We observed that, for applications with demanding requirements and in a large variety of vehicular densities, PDR-DCC (data-rate) provides more reliable communication support than LIMERIC (message-rate). Furthermore, this letter hints that a combined message-rate and data-rate congestion control can improve reliability further.

Design and analysis of control strategies for vehicle platooning

This paper presents a novel vehicle platoon control algorithm using Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) wireless communications between platoon members. A platoon forms a chain of vehicles (e.g., trucks) for improved traffic and fuel efficiency. Platooning algorithms aim to maintain small inter-vehicular distance between vehicles under dynamic driving conditions like acceleration and deceleration. The random delay and dropped messages have a pronounced impact on the control algorithm especially in a congested communication network. In this work, a decentralized platooning control strategy is proposed such that each vehicle can independently switch between multiple controller strategies dependent on communication topologies or the pattern of information exchange from vehicles in-front. The control strategy takes into account V2V communication delay of up to 100ms. In order to overcome the impact of dropped messages a predictive control scheme is proposed. We show the existence of well-known Common Quadratic Lyapunov Function (CQLF), to prove the stability of this switched system. Simulation results show that the proposed control algorithm maintains stability and can keep the inter-vehicle gap deviation less than ±6.3% under imperfect communication conditions for a sinusoidal acceleration input between ±2m/s2.

An integrated V2X simulator with applications in vehicle platooning

One of the most exciting applications of V2X technologies, that is envisioned, is the platooning of a series of autonomous vehicles led by a manually driven vehicle. However, the realization of this application depends entirely on the efficacy of a platoon control algorithm and the communication channel amongst the platoon members. There are many different control algorithms that are being considered to maintain a constant distance/time Gap amongst the platoon members based on the speed and acceleration profile of the other vehicles in the platoon. However, before a particular control algorithm can be deployed, it needs to be thoroughly analysed to see if it can indeed produce the desired effect under all sorts of traffic conditions and with varying penetration rates of V2X technology. In addition, one would also need to collect data on data packet delivery rate and the amount of delay, using different platoon management protocols. This information can then be utilized as a feedback to fine tune both the protocol and the control algorithm itself. This work aims to provide a holistic platform which integrates three simulators VISSIM (Traffic Simulation), NS-3 (Network Simulation) and MATLAB (Platoon control algorithm) that allows testing control algorithm stability in the presence of realistic communication constraints. To illustrate the usability of this co-simulation framework, we have presented results on velocity tracking of leader by follower vehicles while maintaining a specified inter-vehicular gap, for a small platoon along with results on data packet delivery for larger platoons.