Multi-Sensor Lane Finding in Urban Road Networks
نویسندگان
چکیده
This paper describes a system for detecting and estimating the properties of multiple travel lanes in an urban road network from calibrated video imagery and laser range data acquired by a moving vehicle. The system operates in several stages on multiple processors, fusing detected road markings, obstacles, and curbs into a stable non-parametric estimate of nearby travel lanes. The system incorporates elements of a provided piecewise-linear road network as a weak prior. Our method is notable in several respects: it estimates multiple travel lanes; it fuses asynchronous, heterogeneous sensor streams; it handles high-curvature roads; and it makes no assumption about the position or orientation of the vehicle with respect to the road. We analyze the system’s performance in the context of the 2007 DARPA Urban Challenge. With five cameras and thirteen lidars, it was incorporated into a closed-loop controller to successfully guide an autonomous vehicle through a 90 km urban course at speeds up to 40 km/h amidst moving traffic.
منابع مشابه
Estimation Model of Two-Lane Rural Roads Safety Index According to Characteristics of the Road and Drivers’ Behavior
Vehicle crashes are amongst the major causes of mortality and results in losses of lives and properties. A large number of the vehicle crashes occur on rural roads. Accidents become more noteworthy in two-lane roads due to going and coming traffic. Therefore, prediction of crashes and their causes are considerably important to reduce the number and severity of the accidents. The safety index is...
متن کاملA multi-hop PSO based localization algorithm for wireless sensor networks
A sensor network consists of a large number of sensor nodes that are distributed in a large geographic environment to collect data. Localization is one of the key issues in wireless sensor network researches because it is important to determine the location of an event. On the other side, finding the location of a wireless sensor node by the Global Positioning System (GPS) is not appropriate du...
متن کاملAutomatic Lane Detection in Image Sequences for Vision-based Navigation Purposes
Intelligent Vehicles, as a main part of Intelligent Transportation Systems (ITS), will have great impact on transportation in near future. They would be able to understand their immediate environment and also communicate with other traffic participants such as other vehicles, infrastructures and traffic management centres. Intelligent vehicles could navigate autonomously in highway and urban sc...
متن کاملEvaluation and comparison performance of deep neural networks FCN and RDRCNN in order to identify and extract urban road using images of Sentinel-2 with medium spatial resolution
Road extraction using remote sensing images has been one of the most interesting topics for researchers in recent years. Recently, the development of deep neural networks (DNNs) in the field of semantic segmentation has become one of the important methods of Road extraction. In the Meanwhile The majority of research in the field of road extraction using DNN in urban and non-urban areas has been...
متن کاملHybrid Evolutionary Metaheuristics for Concurrent Multi-Objective Design of Urban Road and Public Transit Networks
This paper addresses a bi-modal multi-objective discrete urban road network design problem. The problem includes the simultaneous design of urban road and bus networks in urban areas in which the authorities play a major role in designing bus network topology. The road network design consists of decision making for lane additions to the existing streets, new street constructions, determining th...
متن کامل