Train scheduling simulation that minimises operational conflicts due to service constraints

This paper presents an attempt made to facilitate re‐scheduling of trains to minimize operational delays and accommodate uniform headways for off peak sub urban services subject to resource constraints such as locomotive availability, poor track conditions and stations without siding facilities. The paper describes the computer simulation model designed to optimize train schedules on single‐track rail lines. Using this simulation program it is possible to plan and optimize timetables for railway networks with train runs within short time periods for both single track and double track conditions. The paper describes the capabilities of presenting the results of the simulation runs. These include the time‐distance graph, the network with train movements, dialog boxes with information about selected trains. The programme is capable of changing the starting point, departure time, train destinations and adding or deleting a stop etc. from the user interface. Four objects of array variables are used in the simulation process to keep train and station data. Two object arrays are used for the train movements in up and down directions. The stations' data are stored in the other two object arrays. One of these arrays of stations contains all the stations of the line while the other one contains only the stations with siding facilities. A case study that covers a 61 km long single‐track line with 14 stations is presented to highlight the model capabilities.     

Performance Evaluation of Hybrid-Drive Buses and Potential Fuel Savings in Brazilian Urban Transit

Transporting more than 55 million passengers per day, buses are the main transit mode in Brazil. Most of these vehicles use diesel oil and this situation causes dependence on oil, extensive greenhouse gas emissions and increasing air pollution in urban areas. In order to improve this situation the options for Brazilian cities include the use of alternative fuels and new propulsion technologies, such as hybrid vehicles. This article proposes a procedure for evaluating the performance of a recently developed Brazilian hybrid-drive technology. A simple procedure is presented to compare hybrid-drive buses with conventional diesel buses in urban operation focusing on fuel economy and the potential for reducing diesel oil consumption through the use of hybrid-drive buses. Field tests carried out by the authors indicate that fuel consumption improvement through the use of hybrid-drive buses would certainly exceed 20%, resulting in lower fuel costs and reduced carbon dioxide (CO₂) emissions.     

An Exploration of the Relationship between Timing and Duration of Maintenance Activities

The timing and duration of an activity episode are two important temporal aspects of activity-travel behavior. Understanding the causal relationship between these two variables would be useful in the development of activity-based travel demand modeling systems. This paper investigates the relationship between these two variables by considering two different causal structures – one structure in which time-of-day choice is determined first and influences duration and a second structure in which activity duration is determined first and affects time-of-day choice. These two structures are estimated within a discrete-continuous simultaneous equations framework employing a full-information maximum likelihood methodology that allows error covariance. The estimation is performed separately for commuter and non-commuter samples drawn from a 1996 household travel survey data set from the Tampa Bay area in Florida. The results of the model estimation effort show that the causal structure in which activity duration precedes or affects activity timing (time of day choice) performs better for the non-commuter sample. For the commuter sample, the findings were less conclusive with both causal structures offering equally good statistical measures of fit. In addition, for the commuter sample, all error correlations were found to be zero. These two findings suggest that time of day choice and activity episode duration are only loosely related for the commuter sample, possibly due to the relatively non-discretionary and inflexible work activity and travel.     

Correlation between automotive CO, HC, NO, and PM emission factors from on-road remote sensing: implications for inspection and maintenance programs

Carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NO) emission factors (EFs) are measured with a commercial vehicle emissions remote sensing system (VERSS) during a large-scale vehicle exhaust emissions study in Las Vegas. Particulate matter (PM) EFs are simultaneously measured for individual vehicles with a newly developed PM-VERSS based on ultraviolet backscatter light detection and ranging (Lidar). The effectiveness of CO and HC EFs as proxy for NO and PM EFs for spark-ignition vehicles is evaluated. Poor correlations were found between EFs for pollutants on an individual vehicle basis indicating that high EFs for one or more pollutants cannot be used as a predictor of high EFs for other pollutants. Stronger functional relationships became evident after averaging the EF data in bins based on rank-order of a single pollutant EF. Low overlap between the highest 10% emitters for CO, HC, NO, and PM was found. These results imply that for an effective reduction of the four pollutants, inspection and maintenance (I/M) programs, including clean screening, should measure all four pollutants individually. Fleet average CO and HC concentrations determined by gaseous VERSS were compared with fleet average CO and HC concentrations measured at low-idle and at high-idle during local I/M tests for spark-ignition vehicles. The fleet average CO concentrations measured by I/M tests at either idle were about half of those measured by remote sensing. The fleet average high-idle HC concentration measured by I/M tests was about half of that measured by VERSS while low-idle I/M and VERSS HC average concentrations were in better agreement. For a typical vehicle trip, most of the fuel is burned during non-idle conditions. I/M measurements collected during idling conditions may not be a good indicator of a vehicle’s potential to be a high emitter. VERSS measurements, when the vehicle is under a load, should more effectively identify high emitting vehicles that have a large contribution to the mobile emissions inventory.     

Hub location with flow economies of scale

A characteristic feature of hub and spoke networks is the bundling of flows on the interhub links. This agglomeration of flows leads to reduced travel costs across the interhub links. Current models of hub location do not adequately model the scale economies of flow that accrue due to the agglomeration of flows. This paper shows that current hub location models, by assuming flow-independent costs, not only miscalculate total network cost, but may also erroneously select optimal hub locations and allocations. The model presented in this paper more explicitly models the scale economies that are generated on the interhub links and in doing so provides a more reliable model representation of the reality of hub and spoke networks.     

An Optimal Self-Tuning Controller for an Active Suspension

An optimal self-tuning control algorithm is presented for vehicle suspension design. The controller, incorporating a weighting controller, state observer and parameter estimator, is designed according to linear optimal control (LQG) theory. Based on the updated estimates of vehicle parameters and states, and the adapted weighting parameters, the LQG controller provides the optimal set of gains over different operating conditions. The feasibility and effectiveness of the proposed self-tuning system was investigated and proved by simulation studies.     

Fuzzy-logic applied to yaw moment control for vehicle stability

In this paper, we propose a new yaw moment control based on fuzzy logic to improve vehicle handling and stability. The advantages of fuzzy methods are their simplicity and their good performance in controlling non-linear systems. The developed controller generates the suitable yaw moment which is obtained from the difference of the brake forces between the front wheels so that the vehicle follows the target values of the yaw rate and the sideslip angle. The simulation results show the effectiveness of the proposed control method when the vehicle is subjected to different cornering steering manoeuvres such as change line and J-turn under different driving conditions (dry road and snow-covered).     

Study on dynamic characteristics of vehicle gearbox under multi-boundary conditions

With the development of vehicle gearbox to high-power-density and high-speed, how to predict and optimize the dynamic characteristics of vehicle gearbox becomes increasingly prominent. Aiming at the vehicle gearbox, this paper comprehensively and deeply studies the dynamic characteristics under the multi-boundary conditions. The generation mechanism of the multi-source excitations triggering the gearbox vibration is analyzed firstly. The vibration transfer path of the gearbox is explored. Secondly, the engine excitation, the gear meshing excitation and the bearing support load are numerically calculated. According to the finite element method, a fluid-solid coupling finite element model of the gearbox body is established to predict the gearbox dynamic responses based on the Galerkin method and the Hamiltonian variational principle. Finally, the effects of the excitation condition, oil height and reinforcement forms on the vibration responses of the gearbox body are thoroughly studied by simulation. The analysis indicates that it not only helps to modify and improve the method of forecasting the gearbox dynamic response, and also provides the theoretical and technical guidance for the gearbox design and optimization.     

Target priority determination methods by interval-valued intuitionistic fuzzy sets with unknown attribute weights

The paper aims at the problem of multi-targets threat degree being hard to be evaluated accurately in complex air defense battlefield environments. Combined with multi-sensors information fusion and interval-valued intuitionistic fuzzy sets (IVIFS) theories, the target priority determination is studied. The score and accuracy functions of IVIFS are improved with thinking about the hesitating information in order to increase the rationality. Then, the influence factors of target priority and the nonlinear relationship between the influence factors and target priority are analyzed. Next, the algorithms for calculating the factor weights and sensor weights are given. Based on the theory of IVIFS and technique for order preference by similarity to an ideal solution (TOPSIS), two methods of target priority determination based on the IVIFS and TOPSIS are proposed. At last, an application example verifies the effectiveness and flexibility of the proposed algorithms.