Transportation - The associations between objective and subjective dimensions of the built environment and walking behaviour have been examined extensively in existing studies. However, the... 相似文献
Transportation - Predicting how changes to the urban environment layout will affect the spatial distribution of pedestrian flows is important for environmental, social and economic sustainability.... 相似文献
Previous choice studies have proposed a way to condition the utility of each alternative in a choice set on experience with the alternatives accumulated over previous periods, defined either as a mode used or not in a most recent trip, or the mode chosen in their most recent trip and the number of similar one-way trips made during the last week. The paper found that the overall statistical performance of the mixed logit model improved significantly, suggesting that this conditioning idea has merit. Experience was treated as an exogenous influence linked to the scale of the random component, and to that extent it captures some amount of the heterogeneity in unobserved effects, purging them of potential endogeneity. The current paper continues to investigate the matter of endogeneity versus exogeneity. The proposed approach implements the control function method through the experience conditioning feature in a choice model. We develop two choice models, both using stated preference data. The paper extends the received contribution in that we allow for the endogenous variable to have an impact on the attributes through a two stage method, called the Multiple Indicator Solution, originally implemented in a different context and for a single (quality) attribute, in which stage two is the popular control function method. In the first stage, the entire utility expression associated with all observed attributes is conditioned on the prior experience with an alternative. Hence, we are capturing possible correlates associated with each and every attribute and not just one selected attribute. We find evidence of potential endogeneity. The purging exercise however, results in both statistical similarities and differences in time and cost choice elasticities and mean estimates of the value of travel time savings. We are able to identify a very practical method to correct for possible endogeneity under experience conditioning that will encourage researchers and practitioners to use such an approach in more advanced non-linear discrete choice models as a matter of routine.
Some agent-based models have been developed to estimate the spread progression of coronavirus disease 2019 (COVID-19) and to evaluate strategies aimed to control the outbreak of the infectious disease. Nonetheless, COVID-19 parameter estimation methods are limited to observational epidemiologic studies which are essentially aggregated models. We propose a mathematical structure to determine parameters of agent-based models accounting for the mutual effects of parameters. We then use the agent-based model to assess the extent to which different control strategies can intervene the transmission of COVID-19. Easing social distancing restrictions, opening businesses, speed of enforcing control strategies, quarantining family members of isolated cases on the disease progression and encouraging the use of facemask are the strategies assessed in this study. We estimate the social distancing compliance level in Sydney greater metropolitan area and then elaborate the consequences of moderating the compliance level in the disease suppression. We also show that social distancing and facemask usage are complementary and discuss their interactive effects in detail.
Successful modelling and simulation of driver behaviour is important for the current industrial thrust of computer-based vehicle development. The main contribution of this paper is the development of an adaptive lateral preview human driver model. This driver model template has a few parameters that can be adjusted to simulate steering actions of human drivers with different driving styles. In other words, this model template can be used in the design process of vehicles and active safety systems to assess their performance under average drivers as well as atypical drivers. We assume that the drivers, regardless of their style, have driven the vehicle long enough to establish an accurate internal model of the vehicle. The proposed driver model is developed using the adaptive predictive control (APC) framework. Three key features are included in the APC framework: use of preview information, internal model identification and weight adjustment to simulate different driving styles. The driver uses predicted vehicle information in a future window to determine the optimal steering action. A tunable parameter is defined to assign relative importance of lateral displacement and yaw error in the cost function to be optimized. The model is tuned to fit three representative drivers obtained from driving simulator data taken from 22 human drivers. 相似文献
Advanced modelling of rail vehicle dynamics requires realistic solutions of contact problems for wheels and rails that are able to describe contact singularities, encountered for wheels and rails. The basic singularities demonstrate themselves as double and multiple contact patches. The solutions of the contact problems have to be known practically in each step of the numerical integration of the differential equations of the model. The existing fast, approximate methods of solution to achieve this goal have been outlined. One way to do this is to replace a multi-point contact by a set of ellipses. The other methods are based on so-called virtual penetration. They allow calculating the non-elliptical, multiple contact patches and creep forces online, during integration of the model. This allows nearly real-time simulations. The methods are valid and applicable for so-called quasi-Hertzian cases, when the contact conditions do not deviate much from the assumptions of the Hertz theory. It is believed that it is worthwhile to use them in other cases too. 相似文献
This paper presents vibration control of a tracked vehicle installed with electro-rheological suspension units (ERSU). As a first step, an in-arm type ERSU is designed, and its spring and damping characteristics are evaluated with respect to the intensity of electric fields. Subsequently, a 16 degree-of-freedom model for a tracked vehicle equipped with the proposed ERSU is established followed by the formulation of a neuro-fuzzy controller. This controller takes account for both ride quality and steering stability by adopting a weighting parameter between two performance requirements. The parameter is appropriately determined by employing a fuzzy algorithm associated with two fuzzy variables: the vertical speed of the body and the rotational angular speed of the wheel. Control performances to isolate unwanted vibration from bump and random road excitations are evaluated through computer simulations. In addition, maximum speed of the vehicle with 6 Watt power absorption is investigated with respect to the road roughness. 相似文献