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This paper presents a robust motion planning methodology for autonomous tracked vehicles navigating in a rough and unknown environment. Two fields of study are dealt with in this paper: motion planning and slip estimation. For the motion planner, the CC-RRT* algorithm is combined with LQG-MP. The motion planner uses a chance-constrained approach and considers the role of compensator in the planning...
In classical Vehicle Routing Problem, algorithms are developed based on travel distance or travel time estimated from an assumed constant travel speed. However, in city logistics, due to a growing amount of traffic and a limited capacity of the road network, travel speed between two locations no longer remains a constant but location and time dependent. In this paper, we propose a framework to visualize...
A probabilistic framework for online motion planning of vehicles in dynamic environments is proposed. We develop a sampling-based motion planner that incorporates prediction of obstacle motion. A key feature is the introduction of task specifications as artificial measurements. This allows us to cast the exploration phase in the planner as a nonlinear, possibly multimodal, estimation problem, which...
The advent of electric vehicles (EVs) will bring forth large increases to the pre-existing demand in the power grid. Adverse impacts to the system will arise if the charging of these EVs is uncontrolled. In order to mitigate this challenge, as a first step the estimation of the additional power due to EV charging is crucial. The estimation is dependent upon the temporal (i.e. time) and spatial (i...
Bus Rapid Transit (BRT) is a high quality bus based transit system which has been identified by the Ministry of Transport, Sri Lanka as an effective transport solution for urbanized areas. Demand estimation for the BRT is a key element in operational planning as it becomes a primary criterion for selection of vehicles, scheduling of services, determination of fleet size and the design stations etc...
Estimating Origin-Destination matrix, named O-D matrix or ODM, is an important issue in transportation planning. Due to need to survey movements on the network, estimating ODM is usually considered as a high-cost measure in transportation planning. In this research work, a two-stage procedure, including solving routing problem and minimizing the difference between observed and estimated traffic volumes...
A methodology to estimate the energy consumption of an electric vehicle is presented. An approach to create a driving cycle based on data extracted from road planning software is developped; it is used to forecast the total cycle energy consumption. Results are compared to the ones obtained from the corresponding actual driving cycle. The influence of road elevation is taken into. Results match with...
Traffic information is important for drivers and the traffic monitoring center (TMC) to avoid traffic congestions. VANET based systems use probe vehicles (PVs) to sense and upload the traffic information. However, due to the uneven distribution of the PVs, only a small part of the real-time traffic data can be gathered. Also, it is not efficient to estimate the traffic conditions at TMC and then publish...
In this paper, we present a congestion-aware route planning system. First we learn the congestion model based on real data from a fleet of taxis and loop detectors. Using the learned street-level congestion model, we develop a congestion-aware traffic planning system that operates in one of two modes: (1) to achieve the social optimum with respect to travel time over all the drivers in the system...
Motorists' trip Origin-Destination (O-D) demand in a vehicular network is one of the critical components for transportation applications. Specially, for transportation planning, trip O-D demand information depicts the travel pattern of travelers in a given time period, whereas in traffic engineering practice, similar information is beneficial to effectively determine the optimal traffic control strategies...
Construction operations have a tremendous impact upon both the environment and public health due to the generation of significant amounts of airborne emissions, including greenhouse gases and other traditional criteria air pollutants. Quantifying emissions in the pre-planning phase of construction operations is the first step in identifying mitigation opportunities. The authors therefore have quantified...
We present a novel way to learn sampling distributions for sampling-based motion planners by making use of expert data. We learn an estimate (in a non-parametric setting) of sample densities around semantic regions of interest, and incorporate these learned distributions into a sampling-based planner to produce natural plans. Our motivation is that certain aspects of the workspace have a local influence...
This paper presents the control system of an autonomous vehicle capable of perceiving and describing the environment using different inputs, such as GPS waypoints, roadways borders and lines, leader vehicles, and obstacles to be avoided. The controller has been implemented and tested for the VisLab Intercontinental Autonomous Challenge, a long intercontinental trip that aims to demonstrate capabilities...
This paper addresses the problem of optimizing the navigation of an intelligent mobile in a real world environment, described by a map. The map is composed of features representing natural landmarks in the environment. The vehicle is equipped with a sensor which allows it to obtain range and bearing measurements from observed landmarks during the execution. These measurements are correlated with the...
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