Vehicular Fog Computing Enabled Real-time Collision Warning via Trajectory Calibration

Vehicular fog computing (VFC) has been envisioned as a promising paradigm for enabling a variety of emerging intelligent transportation systems (ITS). However, due to inevitable as well as non-negligible issues in wireless communication, including transmission latency and packet loss, it is still challenging in implementing safety-critical applications, such as real-time collision warning in vehicular networks. In this paper, we present a vehicular fog computing architecture, aiming at supporting effective and real-time collision warning by offloading computation and communication overheads to distributed fog nodes. With the system architecture, we further propose a trajectory calibration based collision warning (TCCW) algorithm along with tailored communication protocols. Specifically, an application-layer vehicular-to-infrastructure (V2I) communication delay is fitted by the Stable distribution with real-world field testing data. Then, a packet loss detection mechanism is designed. Finally, TCCW calibrates real-time vehicle trajectories based on received vehicle status including GPS coordinates, velocity, acceleration, heading direction, as well as the estimation of communication delay and the detection of packet loss. For performance evaluation, we build the simulation model and implement conventional solutions including cloud-based warning and fog-based warning without calibration for comparison. Real-vehicle trajectories are extracted as the input, and the simulation results demonstrate that the effectiveness of TCCW in terms of the highest precision and recall in a wide range of scenarios

Navigation/traffic control satellite mission study. Volume 3 - System concepts

Satellite network for air traffic control, solar flare warning, and collision avoidanc

Real-Time Estimation of the Distribution of Brake Response Times for an Individual Driver Using Vehicular Ad Hoc Network

Adapting the functioning of the collision warning systems to the specific drivers' characteristics is of great benefit to drivers. For example, by customizing collision warning algorithms we can minimize false alarms, thereby reducing injuries and deaths in highway traffic accidents. In order to take the behaviors of individual drivers into account, the system needs to have a Real-Time estimation of the distribution of brake response times for an individual driver. In this paper, we propose a method for doing this estimation which is not computationally intensive and can take advantage of the information contained in all data points

Forward Vehicle Collision Warning Based on Quick Camera Calibration

Forward Vehicle Collision Warning (FCW) is one of the most important functions for autonomous vehicles. In this procedure, vehicle detection and distance measurement are core components, requiring accurate localization and estimation. In this paper, we propose a simple but efficient forward vehicle collision warning framework by aggregating monocular distance measurement and precise vehicle detection. In order to obtain forward vehicle distance, a quick camera calibration method which only needs three physical points to calibrate related camera parameters is utilized. As for the forward vehicle detection, a multi-scale detection algorithm that regards the result of calibration as distance priori is proposed to improve the precision. Intensive experiments are conducted in our established real scene dataset and the results have demonstrated the effectiveness of the proposed framework

Safety distance awareness system for Malaysian Driver

It is known that the risk of an accident increases exponentially with the speed of the vehicle and most collisions happen when the driver fails to brake at the required time and distance. The objective of this research is to create a Safety Distance Awareness System which aims at warning the driver of the potential frontal collision and to alter Malaysian driver attitudes. This system is to manipulate Malaysian driver attitude that likes to tailgating and to prevent rear-end collision in Malaysia. This is done by using a Sound Navigation and Ranging (SONAR) range finder to determine the distance of the vehicle or obstacle in front of the host vehicle. With the help of microcontroller, the distance of the host vehicle could be determined and a warning will be issued in the form of both visual and hearing so driver could take the correct preventive measure. There will be few stages of warning, the system will intensify the distress warning until the collision occurs. These SDAs do not take any automatic prevention or control to the vehicle to avoid collision. In overall the research hopes to achieve a more convenient driving experience and a safer driving environment by implementing the SDAS to keep drivers aware of the potential hazards ahead of their vehicle. Hopefully the Malaysian government will involve in this research, since the implementation of Safety Distance Awareness System can provide a new alternative in the safety system hence it can reduce accidents in Malaysia

Potential benefits of an adaptive forward collision warning system

Forward collision warning (FCW) systems can reduce rear-end vehicle collisions. However, if the presentation of warnings is perceived as mistimed, trust in the system is diminished and drivers become less likely to respond appropriately. In this driving simulator investigation, 45 drivers experienced two FCW systems: a non-adaptive and an adaptive FCW that adjusted the timing of its alarms according to each individual driver’s reaction time. Whilst all drivers benefited in terms of improved safety from both FCW systems, non-aggressive drivers (low sensation seeking, long followers) did not display a preference to the adaptive FCW over its non-adaptive equivalent. Furthermore, there was little evidence to suggest that the non-aggressive drivers’ performance differed with either system. Benefits of the adaptive system were demonstrated for aggressive drivers (high sensation seeking, short followers). Even though both systems reduced their likelihood of a crash to a similar extent, the aggressive drivers rated each FCW more poorly than their non-aggressive contemporaries. However, this group, with their greater risk of involvement in rear-end collisions, reported a preference for the adaptive system as they found it less irritating and stress-inducing. Achieving greater acceptance and hence likely use of a real system is fundamental to good quality FCW design

Computer simulation model of terminal air traffic and PWI systems, phase 1

Collision avoidance computer simulation model of terminal air traffic and proximity warning indicator system

Display research, collision warning systems Final report

Display research for aircraft collision warning system

Integrating Multiple Alarms & Driver Situation Awareness

This study addresses this gap in CAS and intelligent alarm research by examining whether or not a single master alarm warning versus multiple warnings for the different collision warning systems conveys adequate information to the drivers. Intelligent driver warning systems signaling impending frontal and rear collisions, as well as unintentional lane departures were used in this experiment, and all the warnings were presented to drivers through the auditory channel only. We investigated two critical research questions in this study: 1. Do multiple intelligent alarms as opposed to a single master alarm affect drivers’ recognition, performance, and action when they experience a likely imminent collision and unintentional lane departure? 2. Is driver performance and overall situation awareness under the two different alarm alerting schemes affected by reliabilities of the warning systems?Prepared For Ford Motor Compan

Requirement analysis for building practical accident warning systems based on vehicular ad-hoc networks

An Accident Warning System (AWS) is a safety application that provides collision avoidance notifications for next generation vehicles whilst Vehicular Ad-hoc Networks (VANETs) provide the communication functionality to exchange these notifi- cations. Despite much previous research, there is little agreement on the requirements for accident warning systems. In order to build a practical warning system, it is important to ascertain the system requirements, information to be exchanged, and protocols needed for communication between vehicles. This paper presents a practical model of an accident warning system by stipulating the requirements in a realistic manner and thoroughly reviewing previous proposals with a view to identify gaps in this area