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  • 1.
    Fu, Jiali
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    A Microscopic Simulation Model for Earthmoving Operations2012In: Proceedings of the International Conference on Sustainable Design and Construction, 2012, p. 218-223Conference paper (Refereed)
    Abstract [en]

    Earthmoving operations are a major part of many construction projects. Because of the complexity and fast-changing environment of such operations, the planning and estimating are crucial on both planning and operational levels. This paper presents the framework ofa microscopic discrete-event simulation system for modeling earthmoving operations and conducting productivity estimations on an operational level.A prototype has been developed to demonstrate the applicability of the proposed framework, and this simulation system is presented via a case study based on an actual earthmoving project. The case study shows that the proposed simulation model is capable of evaluating alternative operating strategies and resource utilization at a very detailed level.

  • 2.
    Fu, Jiali
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Evaluating and Improving the Transport Efficiency of Logistics Operations2017Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The thesis focuses on evaluating and improving the transport efficiency of two types of logistics operations in the supply chain.

    One research area is the production of raw material in construction operations, specifically earthmoving operations. Methods and tools are developed to provide decision support in improving the transport efficiency of earthmoving at the vehicle and the systems levels. Using known road topography and a GPS unit, an optimal control problem is formulated and solved (Paper III) to determine the optimal gear shift sequence and timing in order to improve the transport efficiency at the vehicle level. For decision support at the systems level, a Fleet Performance Simulation (FPS) model is designed (Paper IV) to evaluate the transport efficiency for a given mix of construction vehicles in earthmoving. The FPS system is integrated with an optimization algorithm to solve the optimal fleet composition problem for earthmoving operations (Paper V & VI). Construction operations are dynamic and the environment is changing constantly, which bring difficulties in decision-making. Using GPS data from construction vehicles, a map inference framework (Papers I & II) is developed to automatically extract relevant input to decision support at the vehicle and the systems levels, which include the locations of various workstations, driving time distributions and road networks.

    The second research area is the transport efficiency of urban distribution system, which is in the final phase of the supply chain. An off-peak delivery pilot project in Stockholm is used as the background, designed to evaluate the potential for commercial vehicles to make use of off-peak hours for goods delivery. The thesis (Paper VII) evaluates the transport efficiency impacts of the off-peak pilot. An evaluation framework is defined where transport efficiency is studied in a number of dimensions. GPS data, fleet management data, and logistic information are used to assess the impacts.

  • 3.
    Fu, Jiali
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Logistics of Earthmoving Operations: Simulation and Optimization2013Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Earthworks are a fundamental part of heavy construction engineering and involve the moving and processing of the soil surface of earth. Normally, earthmoving operations are carried out during the early stages of heavy construction projects. To a large extent, the success of the fundamental earthmoving determines the sequence of the remaining parts of a project. Furthermore, the operations require expensive heavy equipment as well as manpower. Thus, improving the efficiency of earthmoving operations is a primary target from the point of view of the project management.

    This thesis develops simulation and optimization methods for logistics of earthmoving operations. Modeling earthmoving operations correctly is essential to ensure the credibility of simulation, and the well-known CYCLONE modeling methodology is employed to represent the earthmoving logistics. Discrete event simulation techniques are used to capture the interaction between resources and the randomness of the earthmoving activities. A prototype has been developed (Paper I) to demonstrate that the capability of the simulation system of evaluating alternative operating strategies and resource utilizations for earthmoving operations at a detailed level, as well as conducting productivity estimation and Total Cost of Ownership (TCO) calculations. The simulation system is then integrated with optimization to solve the optimal fleet selection problem for earthmoving operations (Paper II and III). Two optimization objectives are formulated and solved using the proposed simulation-based optimization framework and a genetic optimization algorithm: TCO minimization and maximization of productivity. The case studies show that the proposed mechanism can effectively allocate an optimal equipment combination for earthmoving operations and hence serve as an efficient tool for construction management. The main aim of the integrated simulation-based optimization platform is to act as a sales tool to help customers optimize their fleet and eventually their sites.

    In addition to the simulation-based optimization framework for earthmoving logistics, the thesis examines the possibility of reducing fuel consumption for articulated haulers which are the most fuel consuming machines in earthmoving (Paper IV). Fuel consumption has become one of the main focuses for automobile manufacturers and several studies have been carried out over the last years to evaluate the possibility of using topographical information and positioning systems to aid look-ahead control systems for road vehicles. Based on the assumption of available road slope information and positioning system, an optimal control problem is formulated to determine the optimal gear shift sequence and time of shifting. Model Predictive Control algorithms together with Dynamic Programming techniques are employed to solve the optimal gear shifting problem. Computer simulations show that both fuel consumption and travel time can be reduced simultaneously. In addition, the optimal gear shift sequence resembles the behavior of an experienced driver.

  • 4.
    Fu, Jiali
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Simulation-Based Optimization of Earthmoving Operations Using Genetic Algorithm2012In: Proceedings of the 17th International Conference of Hong Kong Society for Transportation Studies, 2012, p. 57-64Conference paper (Refereed)
  • 5.
    Fu, Jiali
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Bortolin, Gianantonio
    Gear shift optimization for off-road construction vehicles2014In: European Journal of Transport and Infrastructure Research, ISSN 1567-7133, Vol. 14, no 3, p. 214-228Article in journal (Refereed)
    Abstract [en]

    This paper explores the possibility of using recorded road slope data in order to reduce fuel consumption for off-road construction vehicles such as articulated haulers. Road gradients have strong influence on the fuel consumption of a vehicle. This effect is even more significant on construction vehicles due to their large mass and heavy load. In this study, a control algorithm based on model predictive control and dynamic programming is formulated and solved to find an optimal gear shift sequence and time of shifting. The fuel consumption model of an articulated hauler is formulated with a dynamic model and used together with the travel time in the objective function to balance the trade-off between these two aspects. The proposed control algorithm is simulated on a typical road stretch on the construction work site with frequent steep up- and downhill. Simulation shows that both fuel consumption and travel time can be reduced simultaneously. In addition, the optimal gear shift sequence resembles the behaviour of an experienced driver.

  • 6.
    Fu, Jiali
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Bortolin, Gianantonio
    Gear Shift Optimization for Off-road Construction Vehicles2012In: PROCEEDINGS OF EWGT2012 - 15TH MEETING OF THE EURO WORKING GROUP ON TRANSPORTATION, Elsevier, 2012, p. 989-998Conference paper (Refereed)
    Abstract [en]

    This paper explores the possibility of using recorded road slope data in order to reduce fuel consumption for off-road construction vehicles such as articulated haulers. An optimal control algorithm based on model predictive control and dynamic programming is formulated to find an optimal gear shift sequence. Computer simulation shows that both fuel consumption and travel time can be reduced simultaneously. In addition, the optimal gear shift sequence resembles the behavior of an experienced driver.

  • 7.
    Fu, Jiali
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Off-peak goods deliveries in Stockholm inner city - evaluation of transport efficiency2016Conference paper (Other (popular science, discussion, etc.))
  • 8.
    Fu, Jiali
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Optimal Fleet Selection for Earthmoving Operations2013Conference paper (Refereed)
    Abstract [en]

    Earthmoving operations often involve a large number of specially designed equipment with significant purchasing/leasing prices, high operating and maintenance costs. Hence, choosing the right fleet is a major concern from the construction planners’ point of view. This paper presents a methodology that combines discrete-event simulation and optimization to solve the optimal fleet selection problem for earthmoving operations. Two optimization objectives are formulated and solved using the proposed framework and a genetic algorithm: minimization of Total Cost of Ownership (TCO) and maximization of productivity. Further, a two-stage rating scheme is introduced to arrange the fleet configurations so that the optimization algorithm converges to a fleet with better second-stage performance while the first-stage performance remains at the same level. The case study shows that the proposed mechanism can effectively allocate an optimal equipment combination for earthmoving operations and hence serve as an efficient tool for construction management.

  • 9.
    Fu, Jiali
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Transport Science.
    Transport efficiency of off-peak urban goods deliveries: A Stockholm pilot study2018In: Case Studies on Transport Policy, ISSN 2213-624X, E-ISSN 2213-6258, Vol. 6, no 1, p. 156-166Article in journal (Refereed)
    Abstract [en]

    It is increasingly recognized that even cities with severe congestion during peak hours have available road capacity during nights, evenings and early mornings. Policies that shift urban goods deliveries from peak hours to off-peak hours have the potential to increase the efficiency of freight distribution, as well as to reduce negative external impacts. Between 2014 and 2016, the City of Stockholm ran a pilot project allowing inner city goods deliveries with heavy trucks at night. This paper evaluates the transport efficiency impacts of the Stockholm off-peak pilot. An evaluation framework is defined where transport efficiency is studied in a number of dimensions, including driving efficiency, delivery reliability, energy efficiency and service efficiency. For each dimension, performance indicators are introduced and evaluated. Vehicle GPS probe data, fleet management data, and logistic information are used to assess the impacts. The results suggest that shifting deliveries from daytime peak hours to night-time achieved better transport efficiency in driving efficiency, delivery reliability and energy efficiency. Meanwhile, there were no clear efficiency gains from moving deliveries from mid-day hours. For cities with varying congestion during daytime like Stockholm, the results suggest that night-time deliveries mainly increase the scheduling flexibility of carriers and recipients through the introduction of additional off-peak hours. The conclusions provide input to planners, decision-makers and local authorities to design and implement effective policy initiatives.

  • 10.
    Fu, Jiali
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Transport efficiency of off-peak urban goods deliveries: A Stockholm pilot study2017Conference paper (Refereed)
  • 11.
    Fu, Jiali
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Haris, Koutsopoulos
    Driving time and path generation for heavy construction sites from GPS traces2016In: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, IEEE, 2016, p. 1141-1146Conference paper (Refereed)
    Abstract [en]

    The paper presents a methodology for using GPS probe data to automatically extract the driving time between workstations and build a detailed representation of the paths between workstations in a construction environment. The inferred driving time distribution is aimed as input to construction simulation models to assess fleet performance, while the path information can be utilized to examine the performance of individual vehicles. A case study, using GPS data collected from a construction site, is used to demonstrate the capability of the proposed approach. The GPS data are processed without any prior knowledge about the underlying work environment. The results show that the proposed approach is capable of accurately inferring the driving time distribution and the paths between workstations.

  • 12.
    Fu, Jiali
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Koutsopoulos, Haris
    Identification of workstations in earthwork operations from vehicle GPS data2016Conference paper (Refereed)
    Abstract [en]

    Increasing availability and the use of Global Positioning System (GPS) devices open great opportunities for various transportation applications. The authors propose a generative probabilistic model for extraction of locations of workstations in earthwork operations using raw GPS traces from construction vehicles. The probabilistic model incorporates the GPS measurements with relevant information extracted from the GPS data to compute locations of different workstations as probability distribution over the environment. The location of workstations will be used as a part of a map inference method for generating and continuously updating the layout and road network topology of the construction environment. A detailed case study was conducted with construction equipment at a complex site. The authors first demonstrate the probabilistic model to extract the locations of loading stations using vehicle speed and interactions among vehicles, and then to discover dumping stations with help of vehicle moving patterns. The results from the experiment show that the proposed method is able to discover important places and workstations for earthwork environment efficiently and in sufficient details.

  • 13.
    Fu, Jiali
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering. Department of Civil and Environmental Engineering, Northeastern University, 360 Huntington Avenue, Boston, USA.
    Identification of workstations in earthwork operations from vehicle GPS data2017In: Automation in Construction, ISSN 0926-5805, E-ISSN 1872-7891, Vol. 83, p. 237-246Article in journal (Refereed)
    Abstract [en]

    The paper proposes a methodology for the identification of workstations in earthwork operations based on GPS traces from construction vehicles. The model incorporates relevant information extracted from the GPS data to infer locations of different workstations as probability distributions over the environment. Monitoring of workstation locations may support map inference for generating and continuously updating the layout and road network topology of the construction environment. A case study is conducted at a complex earthwork site in Sweden. The workstation identification methodology is used to infer the locations of loading stations based on vehicle speeds and interactions between vehicles, and the locations of dumping stations based on vehicle turning patterns. The results show that the proposed method is able to identify workstations in the earthwork environment efficiently and in sufficient detail.

  • 14.
    Pernestål Brenden, Anna
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    Koutoulas, Anastasios
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
    Fu, Jiali
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Rumpler, Romain
    KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering.
    Sanchez-Diaz, Ivan
    Chalmers University of Technology.
    Behrends, Sönke
    Chalmers University of Technology.
    Glav, Ragnar
    Scania CV AB.
    Cederstav, Fredrik
    Volvo AB.
    Brolinsson, Märta
    Stockholms Stad.
    Off-peak City Logistics – A Case Study in Stockholm2017Report (Other academic)
    Abstract [en]

    Two heavy trucks have been operated in Stockholm city center during night time for e period of one and a half years. New technology has been tested: one the trucks was an electric hybrid with zone management and one was a PIEK certified biogas truck. The two trucks have been operated in different delivery schemes: on dedicated and one consolidated. The off-peak trial has been assessed in from four different perspectives: noise, transport efficiency, users and policy, and socioeconomic aspects. In addition, a literature survey has been performed.  

    Noise produced while travelling with the two trucks tested is not disturbing. The main challenge is noise produced during unloading, and in particular in areas where the background noise is low.

    Transportation efficiency is improved from several perspectives compared with daytime deliveries: transport speed increased, fuel consumption decreased and service times decreased. However, one conclusion from the project is that it is challenging to compare daytime deliveries with off-peak deliveries for an individual truck, since the routing will be different depending on the time of the day even if the delivery points are the same. The reason is that the routing during daytime will be optimized to take congestion into account. Therefore, if general conclusions are to be drawn, data from more different trucks in different delivery schemes need to be collected and analyzed.

    Stakeholder interviews showed that the most important benefits are increased efficiency, shorter travel and deliver times, higher productivity both for carriers and receivers, less environmental impacts and fuel cost savings, as well as better working conditions when trucks are moved from rush hours to off-peak hours. The most important social costs are increased noise levels and noise disturbances, additional staff, equipment and wage costs as well as higher risks in handling goods deliveries at night times, especially in the case of unassisted deliveries. In general, the benefits exceed the costs.

    From the socio-economic analysis it is clear that the dominating type of external cost for daytime deliveries is contribution to congestion. This cost is reduced is nearly eliminated during off-peak deliveries. In addition, off-peak deliveries reduces CO2 emissions, but even more the emissions of air pollutants and can therefore contribute significantly to improving local air quality. The cost of noise is more than twice as big as for daytime deliveries.

    From the city’s perspective the most important remaining challenges are related to 1) Noise measurements and surveillance, 2) general requirements and surveillance, for example concerning vehicles, fuels, and emission levels that are to be allowed, 3) The responsibility for potential additional costs related to infrastructural changes needed. 

    The overall conclusion from the project is that the benefits from off-peak deliveries exceed the costs. The results from the project suggest that the concept of off-peak deliveries is beneficiary in the Stockholm region, and the off-peak delivery program is suggested to continue and be scaled up to involve more vehicles and other types of goods. During the upscaling it is relevant to continue to study effects on transport efficiency, noise levels, and potential business barriers that may arise.

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