A procedure for computing shaded pictures of curved surfaces is presented. The surface is approximated by small polygons in order to solve easily the hidden-parts problem, but the shading of each polygon is computed so that the discontinuities of shade are eliminated across the surface and a smooth appearance is obtained. In order to achieve speed efficiency, the technique developed by Watkins is used which makes possible a hardware implementation of this algorithm.

Continuous shading of curved surfaces

Ant Colony Optimization (ACO) is a stochastic local search method that has been inspired by the pheromone trail laying and following behavior of some ant species [1]. Artificial ants in ACO essentially are randomized construction procedures that generate solutions based on (artificial) pheromone trails and heuristic information that are associated to solution components. Since the first ACO algorithm has been proposed in 1991, this algorithmic method has attracted a large number of researchers and in the meantime it has reached a significant level of maturity. In fact, ACO is now a well-established search technique for tackling a wide variety of computationally hard problems.

Ant Colony Optimization

Cooperative adaptive cruise control (CACC) is a promising technology to improve traffic efficiency and enhance road safety. In this paper, a modified CACC control model considering the communication time delay is proposed, which is used to investigate the longitudinal safety impacts of the communication time delay to the CACC platoon. Then, the communication time delay model is integrated into the CACC model to simulate the realistic information transfer process in the CACC platoon. Then a microscopic CACC platoon simulation is designed and conducted to verify the feasibility and reliability of the modified CACC control algorithm. The obtained results reveal that the modified CACC control algorithm can not only reduce about 96.6% of inter-vehicle spacing error, but also enhance the vehicles’ ability to sense the upstream traffic changes. Furthermore, to quantitatively analyze the longitudinal safety influence of the time delay caused by representative communication systems, sensitivity analysis experiments of headway time were designed and conducted. In the sensitivity analysis, the time exposed time-to-collision (TET) and the time-integrated time-to-collision (TIT) were introduced as the key performance indicators (KPIs) to quantify the rear-end collision risks. Sensitivity analysis results demonstrate that the performance of the CACC platoon is strictly related to the applied wireless communication style. Furthermore, the CACC system supported by the 5th generation (5G) communication system shows great advantages in narrowing the minimal headway time gap and reducing the rear-end collision risks.

https://www.mdpi.com/2071-1050/12/18/7568/pdf

Safety Analysis of a Modified Cooperative Adaptive Cruise Control Algorithm Accounting for Communication Delay

Applications and services which run on top of vehicular ad hoc networks range from human safety and traffic management to assisted driving and real time battlefield communication. Many of these applications may have low-elasticity QoS requirements. Characteristics like high mobility of vehicles, dynamic topology, inherent distributed nature and consequent lack of central coordination make it challenging to provide QoS support in such networks. Since, QoS provisioning and path finding can be potentially handled together, this work aims at exploiting such a possibility. Consequently, an attempt has been made to solve the multi-constraint QoS optimal path problem by using an innovative combination of swarm intelligence based optimization strategies and an especially designed cost function. This work also presents a detailed theoretical as well as experimental analysis of the proposed algorithms, probably first of its kind. Additionally, the analysis part also investigates the applicability issues and related solutions considering select algorithms in view of solving the given problem for vehicular ad hoc networks. Meta-heuristics derived in this process have been applied on realistic modelled vehicular ad hoc network topology and as the presented analysis would indicate results are encouraging.

Swarm intelligence inspired meta-heuristics for solving multi-constraint QoS path problem in vehicular ad hoc networks

Connected and autonomous vehicles (CAVs) could reduce emissions, increase road safety, and enhance ride comfort. Multiple CAVs can form a CAV platoon with a close inter-vehicle distance, which can further improve energy efficiency, save space, and reduce travel time. To date, there have been few detailed studies of self-driving algorithms for CAV platoons in urban areas. In this paper, we therefore propose a self-driving architecture combining the sensing, planning, and control for CAV platoons in an end-to-end fashion. Our multi-task model can switch between two tasks to drive either the leading or following vehicle in the platoon. The architecture is based on an end-to-end deep learning approach and predicts the control commands, i.e., steering and throttle/brake, with a single neural network. The inputs for this network are images from a front-facing camera, enhanced by information transmitted via vehicle-to-vehicle (V2V) communication. The model is trained with data captured in a simulated urban environment with dynamic traffic. We compare our approach with different concepts used in the state-of-the-art end-to-end self-driving research, such as the implementation of recurrent neural networks or transfer learning. Experiments in the simulation were conducted to test the model in different urban environments. A CAV platoon consisting of two vehicles, each controlled by an instance of the network, completed on average 67% of the predefined point-to-point routes in the training environment and 40% in a never-seen-before environment. Using V2V communication, our approach eliminates casual confusion for the following vehicle, which is a known limitation of end-to-end self-driving.

https://www.mdpi.com/1424-8220/21/4/1039/pdf

Multi-Task End-to-End Self-Driving Architecture for CAV Platoons.

This paper present: (i) an experimental study for performance evaluation of IEEE 802.11p vehicular communications and (ii) creation of dataset for IEEE 802.11p vehicular communications, while transmitting Basic Safety Messages. Two relevant metrics Latency and Received Signal Strength Indicator have been used for both performance evaluation and creation of dataset. However, the dataset also contains other information like position of the vehicle, packet receiving time, transmitting power etc., while transmitting each such packet. The physical experiments were performed using IEEE 802.11p compliant communication devices. The conducted experiments disclosed many important insights related to the performance of IEEE 802.11p. To the best of knowledge, the data set created and the measurements taken for considered parameters presented in this paper are first of their kinds. These results and dataset would be helpful in future research works in the relevant area.

Measurement of IEEE 802.11p Performance for Basic Safety Messages in Vehicular Communications

Applications of VANETs, as used in Intelligent Transportation Systems may have requirements of robust network and robust route for communication over it. This work aims at modeling robustness as a significant measure of QoS for the effective use in VANETs, first of its kind. Here, robustness has been defined as a qualitative QoS parameter of communication links that depends on link lifetime and error rate over the link. The forms of robustness considered here include Link-Robustness and Route-Robustness. Modeling and quantification of Link-Robustness has been carried out by synthesizing temporal, spatial and environmental dependencies of the network. It is so because these dependencies are responsible for variation of link-lifetime and link-error rate in VANETs environment. Similarly, Route-Robustness has been defined and modeled as a part of the overall network environment. Moreover, quantification of Link-Robustness and Route Robustness has been proposed and illustrated with the help of an example scenario. Based upon the proposed model and robustness as the QoS measure in VANETs a route selection strategy has been proposed that is an important and integral component of any routing protocol. Subsequently, an algorithm has been presented that involves route selection and route request procedures. Finally, validation and analysis of the proposed model and consequent route selection strategy have been carried out the basis of results obtained from the associated simulations of AoDV and AoDV-R in addition to that of proposed model.

A new model for effective use of robustness as a measure of QoS in vehicular ad-hoc networks

Vehicular Ad-hoc Networks may be used for multitude of services including those related to human safety, traffic management and providing comfort to the users as applicable to Intelligent Transportation Systems, Smart Communication Systems, Internet-of-Things etc. In most scenarios, vehicles are owned by different entities and therefore it may not be in the best of interest of VANETs nodes to forward data belonging to different entities indiscriminately. This is so because it involves absorbing the incurred cost in terms of available resources. Such strategy may lead to packet drops and consequent delays leading to overall performance of the VANET-in-question. On the other hand if vehicles are readily agrees to forward any data that they receives, it would lead to a complete cooperation scenario, but might prove costly in terms of resources for the involved nodes. Both of these described conditions represents extreme scenarios and are thus undesirable. This opens up an opportunity for devising a new solution that could be built upon a balanced cooperation enforcement scheme involving all the participating nodes in a resource constrained VANET. In this paper, we present an approach for mathematical modeling of VANETs in form of non-cooperative game. Using this model probability by which a particular vehicular node would accept the relay request of other vehicular nodes has been calculated by involving a combination of an available degree of resource and a resilient reciprocating strategy that we call V-TFT i.e. Vehicular-Tit-for-Tat. The presented simulation result demonstrates that the V-TFT converges to pareto-optimal solution. In addition, it is capable to perform so in presence of non-cooperative nodes and variable sized network.

A game-theoretic strategy for pareto-optimal cooperation in resource constrained vehicular ad-hoc networks

Vehicular Ad-hoc Networks are dynamic and temporary network of on-the-fly vehicles with contemporaneous connectivity. Such a network is suitable for a range of applications; starting with those concerning entertainment to improved traffic negotiation to those aimed at human safety and emergency assistance. By its very nature, such a network has higher node mobility, ever-changing topology, varying environmental conditions and error-prone communication links. Such constraints impose challenges on maintaining robust connectivity among nodes. Therefore, the solution lies in creation of such a mechanism that could enable an acceptable performance even in presence of transient disruptions due to link errors, transmission errors as well as failures of one or more links, routers or nodes. This is precisely what the present work tries to achieve. The principal component of this work is an efficient, adaptive and robust protocol that is capable of such effective data communications. Based on temporal, spatial and environmental dependencies of the network, robust links and routes has been found and effectively used for route selection. Probabilistic modeling techniques have been exploited to serves the purpose. Awareness of the movement of nodes gets reflected in adaptive selection of route. Experimental results suggest that the resulting e-ARP protocol is efficient and leads to significant improvement in network performance.

Nitin Singh Rajput

Papers

Measurement of IEEE 802.11p Performance for Basic Safety Messages in Vehicular Communications

Swarm intelligence inspired meta-heuristics for solving multi-constraint QoS path problem in vehicular ad hoc networks

A new model for effective use of robustness as a measure of QoS in vehicular ad-hoc networks

A game-theoretic strategy for pareto-optimal cooperation in resource constrained vehicular ad-hoc networks

e-ARP: An efficient, adaptive and robust protocol for effective data communication in VANETs