Bike Share Toronto is Canada’s second largest public bike share system. It provides a unique case study as it is one of the few bike share programs located in a relatively cold North American setting, yet operates throughout the entire year. Using year-round historical trip data, this study analyzes the factors affecting Toronto’s bike share ridership. A comprehensive spatial analysis provides meaningful insights on the influences of socio-demographic attributes, land use and built environment, as well as different weather measures on bike share ridership. Empirical models also reveal significant effects of road network configuration (intersection density and spatial dispersion of stations) on bike sharing demands. The effect of bike infrastructure (bike lane, paths etc.) is also found to be crucial in increasing bike sharing demand. Temporal changes in bike share trip making behavior were also investigated using a multilevel framework. The study reveals a significant correlation between temperature, land use and bike share trip activity. The findings of the paper can be translated to guidelines with the aim of increasing bike share activity in urban centers. 相似文献
This paper focuses on the evaluation processes by which decisions regarding transportation alternatives can be assisted. A multidimensional approach usually called multiple criteria decision making is required to represent the complexity of transportation policy and systems. The multiple criteria decision making techniques can be divided into two groups. The first is based on a ranking scheme approach and the second on a mathematical programming approach. A multiple objective mathematical programming procedure known as Goal Programming is presented. The authors examined the use of that procedure in real transportation problems. The results suggest that multiple objective mathematical programming techniques in general do not appear to be appropriate in transportation policy analysis involving mutually exclusive alternatives. Their use can be limited to special cases in the private sector. 相似文献
This paper documents the efforts to operationalize the conceptual framework of MIcrosimulation Learning-based Approach to
TRansit Assignment (MILATRAS) and its component models of departure time and path choices. It presents a large-scale real-world
application, namely the multi-modal transit network of Toronto which is operated by the Toronto Transit Commission (TTC).
This large-scale network is represented by over 500 branches with more than 10,000 stops. About 332,000 passenger-agents are
modelled to represent the demand for the TTC in the AM peak period. A learning-based departure time and path choice model
was adopted using the concept of mental models for the modelling of the transit assignment problem. The choice model parameters
were calibrated such that the entropy of the simulated route loads was optimized with reference to the observed route loads,
and validated with individual choices. A Parallel Genetic Algorithm engine was used for the parameter calibration process.
The modelled route loads, based on the calibrated parameters, greatly approximate the distribution underlying the observed
loads. 75% of the exact sequence of transfer point choices were correctly predicted by the off-stop/on-stop choice mechanism.
The model predictability of the exact sequence of route transfers was about 60%. In this application, transit passengers were
assumed to plan their transit trip based on their experience with the transportation network; with no prior (or perfect) knowledge
of service performance. 相似文献
Concentrations of Cd, Pb, Cu and Zn were determined in water, sediments, gastropod (Bulla umpulla) and green algae (Ulva lactuca) collected from five stations in the western side of the northern part of the Gulf of Suez during the period February 1993–January 1994. Sediments recorded the highest concentrations of Cd (2.26–4.40 μg/g) and Pb (13.90–28.34 μg/g), While the highest concentrations of the essential metals Cu and Zn were found in B. umpulla (28.19–72.04 and 60.24–108.74 μg/g, respectively). Water and sediments showed similar spatial distribution patterns for the highest mean values of the different metals. Highest values of the studied metals were found at stations influenced by various pollution sources such as harbours, and sewage and industrial drains. In contrast, the lowest concentrations were observed faraway from any pollution source. Calculations of concentration factors (C.F.) for gastropod and algae showed highest C.F. of Cd (4312.5–8705.9) and Pb (2103.3–8317.9) in algae, and highest C.F. of Cu (5288.9–42376.5) and Zn (3686.7–9631.5) in gastropod. 相似文献
An optimal control design method is introduced and then applied to the optimum design of active and passive suspension systems. A basic three-dimensional 7-DOF car riding model subjected to four correlated random road inputs is considered. The design method is basically developed to allow arbitrary choice of sensors for various car state variables to be used for feedback control of each suspension unit. Previous studies show that full-state control laws and even some limited-state control laws often include feedback gains which are almost zero. Some other gains, although not zero, don't play an important role in improving the system performance measures. With the method proposed in this work, every suspension unit can have its own feedback measurements and the criterion function can be related to all state and control variables. Thus a large number of active and semi-active suspension systems with full- or limited-state control laws based on different measurement combination can be suggested, studied, and compared with each other. Instead of comparing these optimized active and semi-active suspension systems with a basic, passive suspension, the passive system itself is optimized with the same criterion. Simulations in the time domain and frequency analyses are performed, and comparisons are made among the systems in terms of r.m.s. car response measures and ISO riding comfort criterion. 相似文献
Stochastic optimal control and estimation theories are used to design an active suspension system for a cab ride in a tractor-semitrailer vehicle. A discrete-continuous vehicle model with eleven degrees of freedom is augmented by a stochastic road excitation model and a human perception of vibration shape filter. Both perfect measurement and estimated state cases are considered. The impact of the measurement noise on the design of the optimal controller is demonstrated. The performance of the optimally controlled system is compared with an optimal passive system. It is shown that significant improvements in ride comfort can be achieved through the use of actively controlled cab suspensions. 相似文献
ABSTRACTWe provide two empirical models for calculating the sailing time and berth time of maritime container liner networks to effectively model the ambiguity associated with sea and port contingency for ex-ante decisions of fleet deployment and route planning. The models are based on recorded AIS data of 110 mega vessels including all the operating container mega vessels with a capacity of 16,000 TEU or more during the summer of 2015. The models are able to estimate the sailing time (with R2 of 0.974) and the berth time (with R2 of 0.895) without knowledge of any operational-level explanatory variables. The models are validated against the published East Asia–North Europe services. Moreover, the study reveals that vessel operators adopt different berthing and sailing strategies even under the same conditions. 相似文献
The first commercial fleets of Robo-Taxis will be on the road soon. Today important efforts are made to anticipate future Robo-Taxi services. Fleet size is one of the key parameters considered in the planning phase of service design and configuration. Based on multi-agent approaches, the fleet size can be explored using dynamic demand response simulations. Time and cost are the most common variables considered in such simulation approaches. However, personal taste variation can affect the demand and consequently the required fleet size. In this paper, we explore the impact of user trust and willingness-to-use on the Robo-Taxi fleet size. This research is based upon simulating the transportation system of the Rouen-Normandie metropolitan area in France using MATSim, a multi-agent activity-based simulator. A local survey is made in order to explore the variation of user trust and their willingness-to-use future Robo-Taxis according to the sociodemographic attributes. Integrating survey data in the model shows the significant importance of traveler trust and willingness-to-use varying the Robo-Taxi use and the required fleet size.