Analytical model for calibrating delay at congested bus stops

Abstract

A model is proposed to calculate the overall operating and delay times spent at bus stops due to passenger boarding and alighting and the time lost to queuing caused by bus stop saturation. A formula for line demand at each stop and the interaction between the buses themselves is proposed and applied to different bus stops depending on the number of available berths. The application of this model has quantified significant operational delays suffered by users and operator due to consecutive bus arrival at stops, even with flows below bus stop capacity.     

Optimizing bus-size and headway in transit networks

Optimization models for calculating the best size for passenger carrying vehicles in urban areas were popular during the 1980s. These studies were abandoned in the ‘90s concluding that it was more efficient to use smaller buses at higher frequencies. This article returns to this controversial question, starting from the point of view that any calculation of bus size can only be made after considering the demand for each of the routes on the system. Therefore, an optimization model for sizing the buses and setting frequencies on each route in the system is proposed in accordance with the premises detailed below. The proposed model is a bi-level optimization model with constraints on bus capacity. The model allows buses of different sizes to be assigned to public transport routes optimizing the headways on each route in accordance with observed levels of demand. At the upper level the model considers the optimization of the system’s social and operating costs, these are understood to be the sum of the user’s and operator’s costs. At the lower level there is an assignment model for public transport with constraints on vehicle capacity which balances the flows for bus sizes and headways at each iteration. By graphically representing the results of the model applied to a real case, a series of useful conclusions are reached for the management and planning of a fleet of public transport vehicles.     

Willingness to pay for improving service quality in a multimodal area

Travellers use the installations at multimodal areas to transfer from one mode of transport to another. In many cases these installations are called interchanges. This article characterises the users of transport interchanges to determine the fundamental attributes which they most value when they pass through the area. A Stated Choice survey is designed and administered and Mixed Logit models are estimated to calculate willingness to pay levels for three main attributes: transfer time, the quality of the available information and the services provided in the area. Travellers place most value on the quality of the information they receive and the available services rather than on transfer time, which contradicts the widely held opinion of experts in the field. This opens up new possibilities in the design of modern interchanges which should concentrate more on being welcoming areas with many information points rather than being based around minimising transfer times.     

Planning school transport: design of routes with flexible school opening times

Abstract

This paper puts forward a methodology for designing a system for school transport which, apart from designing routes, specifies school opening times. Traditionally school opening times have always been identical in the same area meaning many buses have to be used at the same time. This paper suggests the staggering of school opening times in order to minimise the number of buses and thereby reduce the enormous costs involved in running them. The methodology is based on: a first phase which addresses the classic routing problem by using mixed integer lineal programming and a second phase which uses bi-level programming to find the vector for school opening times, which, when staying within the constraints of the problem, minimises the direct costs of the system. The upper level represents the evaluation of the system costs and the lower level finds the best combination of optimum routes for the same bus.     

Relationship between service quality and demand for inter-urban buses

This article proposes a model for analysing the modal choice of travellers making inter-urban journeys. Discrete choice models with systematic and random tastes variation were applied to find the most relevant variables for encouraging the use of public transport by bus rather than private car. This research follows on from the results of previous user satisfaction studies on inter-urban bus services in the province of Burgos (Spain). Willingness to pay is also estimated for time savings or other improvements in the bus service.The results indicate that, in general, improvements in the journey time or the number of daily journeys are valued less by inter-urban bus users than they are by car or railway users. The type of bus and its characteristics are evaluated as a function of the distance travelled and result in very small values for this variable. Contrary to what is often reported in satisfaction surveys, the journey cost is found to be relevant when choosing which mode of transport to use, but the most important variable is journey time. Little value is placed on the features of the bus, except on long distance journeys.Finally, a methodology differentiating four hierarchical groups is presented for comparing the results of the relevant variables in demand and satisfaction models. Some only improve perception rather than encourage new users, while others increase take-up but do not improve the image of the service.     

Modelling user satisfaction in public transport systems considering missing information

Collecting data to obtain insights into customer satisfaction with public transport services is very time-consuming and costly. Many factors such as service frequency, reliability and comfort during the trip have been found important drivers of customer satisfaction. Consequently, customer satisfaction surveys are quite lengthy, resulting in many interviews not being completed within the aboard time of the passengers/respondents. This paper questions as to whether it is possible to reduce the amount of information collected without a compromise on insights. To address this research question, we conduct a comparative analysis of different Ordered Probit models: one with a full list of attributes versus one with partial set of attributes. For the latter, missing information was imputed using three different methods that are based on modes, single imputations using predictive models and multiple imputation. Estimation results show that the partial model using the multiple imputation method behaves in a similar way to the model that is based on the full survey. This finding opens an opportunity to reduce interview time which is critical for most customer satisfaction surveys.

     

Is accessibility relevant in trip generation? Modelling the interaction between trip generation and accessibility taking into account spatial effects

The influence of accessibility to opportunities in trip generation continues to be debated in the specialised literature given its relevance to simulate phenomena such as induced demand. This article estimates multiple linear regression models (MLR), spatial autoregressive models (SAR), spatial autoregressive models in the error term (SEM) and spatially filtered Poisson regression models (SPO) to discover whether or not accessibility is a significant factor in trip generation using data from the urban area of Santander (Spain). The results obtained provide evidence which shows that, on an intraurban scale, more accessibility to opportunities decreases trip production in private vehicle for work purpose, whereas it increases trip production in other transport modes for non—mandatory purposes. For the correct interpretation of the estimated parameters it was important to consider the direct and indirect effects of the independent variables in the SAR production models. Finally, the validation of the models showed that the SAR and SEM models had a mean squared error slightly lower than the MLR models in predicting overall trip production. This was because the spatial models reduced the correlation of the residuals present in the MLR models. Furthermore, the SPO models performed better in validation mode than all the continuous models.     

Assessment of wind quality for oceanographic modelling in semi-enclosed basins

The quality of surface winds derived from four meteorological models is assessed in the semi-enclosed Adriatic Sea over a 2-month period: a global hydrostatic model ECMWF T511 (40 km resolution), a hydrostatic limited area model LAMBO (20 km), and two non-hydrostatic limited area models: LAMI (7 km) and COAMPS™ (4 km). These wind models are used to drive a 2 km resolution wave model (SWAN) of the Adriatic, and wind and wave results are compared with observations at the ISMAR oceanographic tower off Venice. Waves are also compared at buoy locations near Ancona and Ortona. Consistently with earlier studies, the ECMWF fields underestimate the wind magnitude and do not reproduce the known spatial structure of strong wind events. The results show that the higher-resolution, limited area models LAMI and COAMPS exhibit better amplitude response than the coarser ECMWF: there is a 3- to 4-fold reduction of the wind underestimation at the platform (from 36% to 8–11%). The wave response is also improved with LAMI and COAMPS: there is a 2-fold reduction in the underestimation of wave heights at the platform. These non-hydrostatic models also produce wind fields with more realistic small-scale, spatial structure during strong wind events. The temporal correlation between observed and modelled wind, however, is highest with the global ECMWF model due to the fact that large-scale features can be predicted deterministically, whereas small-scale features can only be predicted stochastically. Models with less small-scale structure have better correlation because they have less “noise.” This explanation is supported by increased correlation between modelled and observed waves, the waves representing a smoothing of the wind over fetch and duration. Although there is room for improvement, the high-resolution, non-hydrostatic models (LAMI and COAMPS) offer significant advantages for driving oceanographic simulations in semi-enclosed basins such as the Adriatic Sea.     

Modelling demand in restricted parking zones

Multiple linear regression (MLR) and geographically weighted regression (GWR) models are used for estimating parking demand in areas with paid short stay parking systems. These models have been applied to the city of Santander (Cantabria, Spain) to check their goodness of fit and their predictive ability. The results show the main advantages and disadvantages of using GWR models. The technique proved to be useful in this case study because it offered a better fit and made better predictions in a scenario showing a certain degree of spatial heterogeneity unexplained by any of the variables introduced into the global model. However, the GWR model also presented situations of local correlation although this was considered moderate given the results provided by the variance inflation factors and the local condition indexes.