“…The fundamental physical components of autonomous cars, depicted in Fig. 1 (Kuhr, 2017), are as follows: (1) Camera: It provides real-time obstacle detection of facilitate lane departure and track roadway information, (2) Radio Detection and Ranging (RADAR): It detects short and long-range depth, also the presence of an object at a certain distance and usually something that moves like a vehicle, (3) Light Detection and Ranging (LIDAR): It measures distance by illuminating target with pulsed laser light and measuring reflected pulses with sensors to create 3D map of area in more discrete and densely-spaced increments, (4) Global Positioning System (GPS): It triangulates position of car using satellites becomes the critical link for autonomous car to determine their location as they move, (5) Sensors: Odometry for monitoring vehicle distance travel and speed, whereas Ultrasonic for calculating distance using high-frequency sound waves and bounces-back, (6) Central Processing Unit (CPU): The "Brain" of the system is in charge of receiving and processing information from various components to direct the vehicle, 7 (Darwish et al, 2018). To be able to communicate, the vehicle must have a wireless network device called On-Board Units (OBU) installed on the vehicle that functions as a transceiver as well as a router.…”
The autonomous cars are considered as a tremendous disruptive innovation in the coming years. They enable a driving automation system to replace human drivers to control the vehicle with better recognition, decision and driving skills and ultimately enhance the road users' experience and traffic safety. They can communicate with other cars as they are ready with the Vehicle to Vehicle (V2V) communication technology based on Vehicular Ad hoc Networks (VANETs). One of the objectives of V2V communication is for the safety of all road users. Adequate reliability of routing protocol is subject of concern and must be taken into account to reach an immense standard of road safety accurately and timely. Having no reliability the critical road safety messages will be useless; consequently, the accident that might happen is unable to prevent or avoid. The purpose of this research is to investigate and analyze the quantitative measure of reliability. The reliabilities of a reactive single-path AODV and a multipath AOMDV routing protocols that comply with road safety requirements in various traffic conditions are studied. The traffic conditions that may impact the internetworking of autonomous cars include node density, size of road area and speed of the nodes. The methods used in this study are based on simulations by using Network Simulator version-2 (NS2) as a network simulator and Simulation of Urban Mobility (SUMO) as a mobility simulator. The simulation results show that both routing protocols, a single-path AODV and a multi-path AOMDV, satisfy the road safety requirements in some conditions. AODV is better in packet delivery, whereas AOMDV has a better performance on average end to end delay. This study is expected to contribute to the determination of the appropriate protocol for use in road safety applications under certain traffic conditions. In conclusion, the reliability of routing protocol is an essential factor to consider in the operation of VANET-based autonomous cars so that the safety and comfort of road users can be guaranteed.
“…The fundamental physical components of autonomous cars, depicted in Fig. 1 (Kuhr, 2017), are as follows: (1) Camera: It provides real-time obstacle detection of facilitate lane departure and track roadway information, (2) Radio Detection and Ranging (RADAR): It detects short and long-range depth, also the presence of an object at a certain distance and usually something that moves like a vehicle, (3) Light Detection and Ranging (LIDAR): It measures distance by illuminating target with pulsed laser light and measuring reflected pulses with sensors to create 3D map of area in more discrete and densely-spaced increments, (4) Global Positioning System (GPS): It triangulates position of car using satellites becomes the critical link for autonomous car to determine their location as they move, (5) Sensors: Odometry for monitoring vehicle distance travel and speed, whereas Ultrasonic for calculating distance using high-frequency sound waves and bounces-back, (6) Central Processing Unit (CPU): The "Brain" of the system is in charge of receiving and processing information from various components to direct the vehicle, 7 (Darwish et al, 2018). To be able to communicate, the vehicle must have a wireless network device called On-Board Units (OBU) installed on the vehicle that functions as a transceiver as well as a router.…”
The autonomous cars are considered as a tremendous disruptive innovation in the coming years. They enable a driving automation system to replace human drivers to control the vehicle with better recognition, decision and driving skills and ultimately enhance the road users' experience and traffic safety. They can communicate with other cars as they are ready with the Vehicle to Vehicle (V2V) communication technology based on Vehicular Ad hoc Networks (VANETs). One of the objectives of V2V communication is for the safety of all road users. Adequate reliability of routing protocol is subject of concern and must be taken into account to reach an immense standard of road safety accurately and timely. Having no reliability the critical road safety messages will be useless; consequently, the accident that might happen is unable to prevent or avoid. The purpose of this research is to investigate and analyze the quantitative measure of reliability. The reliabilities of a reactive single-path AODV and a multipath AOMDV routing protocols that comply with road safety requirements in various traffic conditions are studied. The traffic conditions that may impact the internetworking of autonomous cars include node density, size of road area and speed of the nodes. The methods used in this study are based on simulations by using Network Simulator version-2 (NS2) as a network simulator and Simulation of Urban Mobility (SUMO) as a mobility simulator. The simulation results show that both routing protocols, a single-path AODV and a multi-path AOMDV, satisfy the road safety requirements in some conditions. AODV is better in packet delivery, whereas AOMDV has a better performance on average end to end delay. This study is expected to contribute to the determination of the appropriate protocol for use in road safety applications under certain traffic conditions. In conclusion, the reliability of routing protocol is an essential factor to consider in the operation of VANET-based autonomous cars so that the safety and comfort of road users can be guaranteed.
“…From the literature study, it is found that the high-speed [57]. The existing direction-based greedy protocols bridge this gap to certain extent, however, these protocols also experience performance degradation in bidirectional traffic where topological changes are intense and path variations are experienced even during the transmission of a single packet.…”
Vehicular ad hoc networks play a pivotal role in the enrichment of transportation systems by making them intelligent and capable of avoiding road accidents. For transmission of warning messages, direction-based greedy protocols select the next hop based on the current location of relay nodes towards the destination node, which is an efficient approach for uni-directional traffic. However, such protocols experience performance degradation by neglecting the movement directions of nodes in bi-directional traffic where topological changes occur dynamically. This paper pioneers the use of movement direction and relative positions of source and destination nodes to cater to the dynamic nature of bi-directional highway environments for efficient and robust routing of warning messages. A novel routing protocol, namely, Direction Aware Best Forwarder Selection (DABFS), is presented in this paper. DABFS takes into account directions and relative positions of nodes, besides the distance parameter, to determine a node's movement direction using Hamming distance and forwards warning messages through neighbor and best route discovery. Analytical and simulation results demonstrate that DABFS offers improved throughput and reduced packet loss rate and end-to-end delay, as compared with eminent routing protocols.
“…In [ 15 ], the regularity of vehicle moving behaviors has been used to improve the routing performance by predicting a vehicle’s future locations based on the past traces and a hidden Markov model. Darwish et al [ 16 ] have discussed the routing decision at the intersection, and proposed a protocol that makes routing decision based on road structure, vehicle position and received signal strength. There have been several studies considering some special types of vehicles to improve the routing.…”
Section: Related Workmentioning
confidence: 99%
“…There have been many studies discussing the routing problem in VANETs [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ]. However, the unicast routing problem and broadcast problem have been discussed separately.…”
We propose a context-aware edge-based packet forwarding scheme for vehicular networks. The proposed scheme employs a fuzzy logic-based edge node selection protocol to find the best edge nodes in a decentralized manner, which can achieve an efficient use of wireless resources by conducting packet forwarding through edges. A reinforcement learning algorithm is used to optimize the last two-hop communications in order to improve the adaptiveness of the communication routes. The proposed scheme selects different edge nodes for different types of communications with different context information such as connection-dependency (connection-dependent or connection-independent), communication type (unicast or broadcast), and packet payload size. We launch extensive simulations to evaluate the proposed scheme by comparing with existing broadcast protocols and unicast protocols for various network conditions and traffic patterns.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.