Collision avoidance system

About: Collision avoidance system is a research topic. Over the lifetime, 1788 publications have been published within this topic receiving 23667 citations.

Train collision avoidance system by using RFID

Abstract: Railways are the convenient, reasonable and popular node of transport in almost all major cities of not only in India but also all over the World. Railways are the most widely used and comfortable nodes of transportation system. Now a day's in India most of the train accidents are occurs due to the human errors. It is very difficult to avoid to such train accidents because of the speed of train is very high and it requires some time to control it. In this paper the effective solution is present to avoid the train accidents by using Radio Frequency Identification (RFID). The primary goal of proposed system is to identify possible train collision ahead of time and to send the report to the main control room or driver before collision happens. Currently there is no solution to avoid train collision. Indian Railways have implemented solution based on ACD (Anti-Collision Device) system. Each locomotive is equipped with an automated surveillance system. The train tracks in railway network are divided into different frames and each segment has 10 km distance and given with distinct track numbers which are read by surveillance system inside the locomotive. Therefore the track id is needed to be given at 10 km distance on the train track. This track number will be shared with the base station by using Radio Frequency Communication system. The paper proposes specific way of numbering the train tracks in frames. If two trains are travelling on the same track then system sends SMS through GSM network to the authorized person to take appropriate action. In areas where GSM network is poor then also the system avoid collision by using RF Module. Wherever at crossing LDR sensor and microcontroller unit take appropriate action if obstacle can be observed.

Development of analysis methods using recent data

Abstract: This report documents the second phase of a two-phase project under Strategic Highway Research Program 2 (SHRP 2) Safety Project S01A. The primary objective of this work was to establish an analytic foundation for using conflicts and near crashes as surrogate measures. The project introduced a counterfactual analytic approach suggesting that a traffic event qualifies as a crash cause under two conditions: (a) both the event and the crash occurred and (b) had the event in question not occurred, then the crash also would not have occurred. Data from site-based field studies and vehicle studies were used to extend these ideas from a trajectory model to more complicated scenarios. The report introduces an approach to microscopic (i.e., individual event) modeling of crash-related events, where driver actions, initial speeds, and vehicle locations are treated as inputs to a physical model describing vehicle motion. This choice of modeling strategy reflects a need for such models if realistic crash processes are to be included in microscopic traffic simulation models. The simple trajectory model can be used to estimate features of crash and near-crash events—such as driver reaction times, following headways, and deceleration rates—from trajectory data produced from a site-based field study. Given sufficiently large samples of crash and near-crash events, this method can be used to compile distributions for these inputs for use in traffic simulation models. Finally, the report illustrates how a trajectory model, together with estimates of input variables, can quantify the degree to which a non-crash event could have been a crash event. The report describes how these ideas were extended to more complicated scenarios by using data from both vehicle- and site-based field studies, including data obtained from the 100-car vehicle-based field study, data from site-based video on Interstate 94 from the Minnesota Traffic Observatory, and site-based radar data from the Cooperative Intersection Collision Avoidance System (CICAS) intersection in North Carolina.

Probabilistic decision making for collision avoidance systems: Postponing decisions

Abstract: For collision avoidance systems to be accepted by human drivers, it is important to keep the rate of unnecessary interventions very low. This is challenging since the decision to intervene or not is based on incomplete and uncertain information. The contribution of this paper is a decision making strategy for collision avoidance systems which allows the system to occasionally postpone a decision in order to collect more information. The problem is formulated in the framework of statistical decision theory, and the core of the algorithm is to run a preposterior analysis to estimate the benefit of deciding with the additional information. A final decision is made by comparing this benefit with the cost of delaying the intervention. The proposed approach is evaluated in simulation at a two-way stop road intersection for stop sign violation scenarios. The results show that the ability to postpone decisions leads to a significant reduction of false alarms and does not impair the ability of the collision avoidance system to prevent accidents.

Device And Method For Judging Likelihood Of Collision Between Vehicle And Target, Vehicle Collision Avoidance System, And Method For Avoiding Collision Between Vehicle And Target

Abstract: A device for judging a likelihood of a collision between a vehicle and a target is provided. The device comprises: a target detection sensor and an ECU. The ECU comprises: a CPU; an orientation determining unit configured to enable the CPU to determine the orientation of a target relative to a reference vehicle in which the device for judging a likelihood of a collision is mounted, using information which is detected by the target detection sensor; a change-amount detecting unit configured to enable the CPU to detect an amount of temporal change in the orientation of the target; and a determining unit configured to enable the CPU to determine a likelihood of a collision between the reference vehicle and the target under a condition that the amount of temporal change in the orientation of the target is a predetermined threshold or less.