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  • 1.
    Alam, Assad
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik.
    Sahlholm, Per
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik.
    A Method for Determining an Economical Speed for Heavy Vehicles2008Ingår i: Proceedings of the 15th World Congress on Intelligent Transport Systems, World Congress on Intelligent Transport Systems (ITS), 2008Konferensbidrag (Refereegranskat)
  • 2. Ivarsson, Maria
    et al.
    Sahlholm, Per
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Blackenfelt, Michael
    Johansson, Karl Henrik
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Nielsen, Lars
    Jansson, Henrik
    Vehicle control using preview information2006Konferensbidrag (Refereegranskat)
    Abstract [en]

    The background and the aim of the project,“Vechicle control by using preview information - ’Look Ahead’ ” , are discussed. The project is raisedto explore the possibilities of reduction of fuel consumption and improvements in comfort and safety for heavy vehicles. In particular research will focus on improvements that can be made, in actual and future control systems, with knowledge of the road ahead. This paper describes the project and reports on initial findings as well as related research.

  • 3.
    Jansson, Henrik
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik.
    Kozica, Eermin
    Scania CV.
    Sahlholm, Per
    Scania CV.
    Johansson, Karl Henrik
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Improved road grade estimation using sensor fusion2006Konferensbidrag (Refereegranskat)
    Abstract [en]

    A method for estimation of the road grade basedon standard mounted sensors in a heavy duty vehicle ispresented. The method combines information from a barometerand a GPS with velocity and torque measurements of conventionaltype. The sensor information is adaptively integratedusing extended Kalman filtering. This provides a systematicmethod for dealing with varying uncertainty in the sensors.The method can handle periods of missing or unreliable datafrom one or several sensors, e.g., occasions when the satellitecoverage is low or when the brakes are applied.

  • 4.
    Sahlholm, Per
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik.
    Distributed Road Grade Estimation for Heavy Duty Vehicles2011Doktorsavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    An increasing need for goods and passenger transportation drives continued worldwide growth in traffic. As traffic increases environmental concerns, traffic safety, and cost efficiency become ever more important. Advancements in microelectronics open the possibility to address these issues through new advanced driver assistance systems. Applications such as predictive cruise control, automated gearbox control, predictive front lighting control, and hybrid vehicle state-of-charge control decrease the energy consumption of vehicles and increase the safety. These control systems can benefit significantly from preview road grade information. This information is currently obtained using specialized survey vehicles, and is not widely available. This thesis proposes new methods to obtain road grade information using on-board sensors. The task of creating road grade maps is addressed by the proposal of a framework where vehicles using a road network collect the necessary data for estimating the road grade. The estimation can then be carried out locally in the vehicle, or in the presence of a communication link to the infrastructure, centrally. In either case the accuracy of the map increases over time, and costly road surveys can be avoided.

    This thesis presents a new distributed method for creating accurate road grade maps for vehicle control applications. Standard heavy duty vehicles in normal operation are used to collect measurements. Estimates from multiple passes along a road segment are merged to form a road grade map, which improves each time a vehicle retraces a route. The design and implementation of the road grade estimator are described, and the performance is experimentally evaluated using real vehicles.

    Three different grade estimation methods, based on different assumption on the road grade signal, are proposed and compared. They all use data from sensors that are standard equipment in heavy duty vehicles. Measurements of the vehicle speed and the engine torque are combined with observations of the road altitude from a GPS receiver, using vehicle and road models. The operation of the estimators is adjusted during gearshifts, braking, and poor satellite coverage, to account for variations in sensor and model reliability. The estimated error covariances of the road grade estimates are used together with their absolute positions to update a stored road grade map.

    Highway driving trials show that the proposed estimators produce accurate road grade data. The estimation performance improves as the number of road segment traces increases. A vehicle equipped with the proposed system will rapidly develop a road grade map for its area of operation. Simulations show that collaborative generation of the third dimension for a pre-existing large area two-dimensional map is feasible. The experimental results indicate that road grade estimates from the proposed methods are accurate enough to be used in predictive vehicle control systems to enhance safety, efficiency, and driver comfort in heavy duty vehicles. The grade estimators may also be used for on-line validation of road grade information from other sources. This is important in on-board applications, since the envisioned control applications can degrade vehicle performance if inaccurate data are used.

  • 5.
    Sahlholm, Per
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik.
    Iterative Road Grade Estimation for Heavy Duty Vehicle Control2008Licentiatavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    This thesis presents a new method for iterative road grade estimation based on sensors that are commonplace in modern heavy duty vehicles. Estimates from multiple passes of the same road segment are merged together to form a road grade map, that is improved each time the vehicle revisits an already traveled route. The estimation algorithm is discussed in detail together with its implementation and experimental evaluation on real vehicles. 

    An increasing need for goods and passenger transportation drives continuing worldwide growth in road transportation while environmental concerns, traffic safety issues, and cost efficiency are becoming more important. Advancements in microelectronics open the possibility to address these issues through new advanced driver assistance systems. Applications such as predictive cruise control, automated gearbox control, predictive front lighting control and hybrid vehicle state-of-charge control benefit from preview road grade information. Using global navigation satellite systems an exact vehicle position can be obtained. This enables stored maps to be used as a source of preview road grade information. The task of creating such maps is addressed herein by the proposal of a method where the vehicle itself estimates the road grade each time it travels along a road and stores the information for later use. 

    The presented road grade estimation method uses data from sensors that are standard equipment in heavy duty vehicles equipped with map-based advanced driver assistance systems. Measurements of the vehicle speed and the engine torque are combined with observations of the road altitude from a GPS receiver in a Kalman filter, to form a road grade estimate based on a system model. The noise covariance parameters of the filter are adjusted during gear shifts, braking and poor satellite coverage. The estimated error covariance of the road grade estimate is then used together with its absolute position to update a stored road grade map, which is based on all previous times the vehicle has passed the same location. 

    Highway driving trials detailed in the thesis demonstrate that the proposed method is capable of accurately estimating the road grade based on few road traversals. The performance of the estimator under conditions such as braking, gear shifting, and loss of satellite coverage is presented. The experimental results indicate that road grade estimates from the proposed method are accurate enough to be used in predictive vehicle control systems to enhance safety, efficiency, and driver comfort of heavy duty vehicles.

  • 6. Sahlholm, Per
    et al.
    Gattami, Ather
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Piecewise Linear Road Grade Estimation2011Ingår i: SAE 2011 World Congress and Exhibition, SAE international , 2011Konferensbidrag (Refereegranskat)
    Abstract [en]

    Emerging heavy duty vehicle control systems increasingly rely on advance knowledge of the road topography, described by the longitudinal road grade. Highway road grade profiles are restricted by road design specifications to be piecewise affine. This characteristic is used herein to derive a method for road grade estimation based on standard on-vehicle sensors and optimal piecewise linear estimation through dynamic programming. The proposed method is demonstrated with on-road experiments. It is able to represent the road grade profile for two studied 15 km road sections, by 20 linear segments for each, with a root mean square error between 0.42 % and 0.55 % grade.

  • 7.
    Sahlholm, Per
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Jansson, H.
    Kozica, Ermin
    Johansson, Karl Henrik
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    A sensor and data fusion algorithm for road grade estimation2007Konferensbidrag (Refereegranskat)
    Abstract [en]

    Emerging driver assistance systems, such as look-ahead cruise controllers for heavy duty vehicles, require high precision digital maps. This contribution presents a road grade estimation algorithm for fusion of GPS and vehicle real-time sensor data, with measurements from previous runs over the same road segment. The resulting road grade estimate is thus enhanced using measurements from additional traversals of known roads. Distributed data fusion is utilized to ensure that the storage requirement of known roads does not increase when additional measurements are processed. The implemented algorithm, which is based on extended Kalman filtering and smoothing, is described in detail. Experiments on a Scania test vehicle show the advantages and some of the challenges with the proposed approach.

  • 8.
    Sahlholm, Per
    et al.
    Scania CV AB, Södertälje.
    Jansson, Henrik
    Scania CV AB, Södertälje.
    Johansson, Karl Henrik
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Road grade estimation results using sensor and data fusion2007Ingår i: 14th World Congress on Intelligent Transport Systems, ITS 2007, 2007, s. 5206-5217Konferensbidrag (Refereegranskat)
    Abstract [en]

    Advanced driver assistance systems for heavy duty vehicles, such as lookahead cruise and gearshift controllers, rely on high quality map data. Current digital maps do not offer the required level of road grade information. This contribution presents an algorithm for on-board road grade estimation based on fusion of GPS and vehicle sensor data with measurements from previous runs over the same road segment. An incremental update scheme is utilized to ensure that data storage requirements are independent of the number of measurement runs. Results of the implemented system based on six traversals of a known road with three different vehicles are presented.

  • 9.
    Sahlholm, Per
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Jansson, Henrik
    Östman, Magnus
    Johansson, Karl Henrik
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Automated speed selection for heavy duty vehicles2007Konferensbidrag (Refereegranskat)
    Abstract [en]

    Many different advanced driver assistance systems are currently being developed to improve road safety and vehicle performance in many areas. The aim of this project has been to create a cruise control system which takes the legal speed limit and road geometry en route into account when determining the appropriate vehicle speed. The system uses a digital map to gain information about curvature and speed limits, and a vehicle model to calculate appropriate control actions. When lowering the speed is required the system coasts with no fueling, thus saving fuel and brake wear.

  • 10.
    Sahlholm, Per
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Johansson, Karl H.
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Road grade estimation for look-ahead vehicle control using multiple measurement runs2010Ingår i: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 18, nr 11, s. 1328-1341Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Look-ahead cruise controllers and other advanced driver assistance systems for heavy duty vehicles require high precision digital topographic road maps. This paper presents a road grade estimation algorithm for creation of such maps based on Kalman filter fusion of vehicle sensor data and GPS positioning information. The algorithm uses data from multiple passes over the same road to improve previously stored road grade estimates. Measurement data from three test vehicles and six experiments have been used to evaluate the quality of the obtained road grade estimate compared to a known reference. The obtained final grade estimate compares favorably to one acquired from a specialized road grade measurement vehicle with a DGPS receiver and inertial measurement unit, with an average root mean square error of 0.17% grade.

  • 11.
    Sahlholm, Per
    et al.
    Scania AB.
    Johansson, Karl Henrik
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Road Grade Estimation for Look-ahead Vehicle Control2008Ingår i: Proceedings of the 17th IFAC World Congress, 2008 / [ed] Chung, Myung Jin; Misra, Pradeep, 2008Konferensbidrag (Refereegranskat)
    Abstract [en]

    Look-ahead cruise controllers and other advanced driver assistance systems for heavy duty vehicles require high precision digital maps. This contribution presents a road grade estimation algorithm for creation of such maps based on Kalman filter fusion of vehicle sensor data and GPS positioning information. The algorithm uses data from multiple traversals of the same road to improve previously stored road grade estimates. Measurement data from three test vehicles and six road traversals have been used to evaluate the quality of the obtained road grade estimate compared to a known reference. The obtained final grade estimate compares favourably to one acquired from a specialized road grade measurement vehicle with a DGPS receiver and inertial measurement unit.

  • 12.
    Sahlholm, Per
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Segmented road grade estimation for fuel efficient heavy duty vehicles2010Konferensbidrag (Refereegranskat)
    Abstract [en]

    Long haulage road transport consumes considerable amounts of energy in today's world. Predictive control strategies based on digital maps can significantly lower the portion being wasted in traditional cruise control operated highway driving. Such control strategies rely on high quality stored road grade information. This paper describes a newly developed method to estimate the road grade using sensors commonly found on standard heavy duty vehicles. The method utilizes a piecewise linear road model derived from highway design methodologies. The estimation method has been implemented and evaluated experimentally, and is shown to give better results compared to an existing method.

1 - 12 av 12
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