Estimation of a route choice model for urban public transport using smart card data

This paper describes a logit model of route choice for urban public transport and explains how the archived data from a smart card-based fare payment system can be used for the choice set generation and model estimation. It demonstrates the feasibility and simplicity of applying a trip-chaining method to infer passenger journeys from smart card transactions data. Not only origins and destinations of passenger journeys can be inferred but also the interchanges between the segments of a linked journey can be recognised. The attributes of the corresponding routes, such as in-vehicle travel time, transfer walking time and to get from alighting stop to trip destination, the need to change, and the time headway of the first transportation line, can be determined by the combination of smart card data with other data sources, such as a street map and timetable. The smart card data represent a large volume of revealed preference data that allows travellers' behaviour to be modelled with higher accuracy than by using traditional survey data. A multinomial route choice model is proposed and estimated by the maximum likelihood method, using urban public transport in ?ilina, the Slovak Republic, as a case study     

Characterization of Longitudinal Road Unevenness in the Light of the International PIARC - EVEN Experiment 1998

The basic model of road pavement unevenness (homogeneous random function with Gaussian distribution function and simple power spectral density function) is generalized to cover real states of roads under traffic conditions, such as: independent characterization of long and short wavelengths unevenness, and consideration of non-homogeneity including appearance of individual large imperfections. The method of estimating relevant parameters is based on the interaction coupling between the traveling vehicle and the road. To justify the need for these generalizations, summarizing results are given of the International PIARC - EVEN experiment conducted in 1998 in three world regions (Arizona, USA, Hokkaido, Japan, and Netherlands / Germany). Total 47 road sections of different technological execution and different unevenness levels were tested using DYNVIA device.     

Compliance and data quality in GPS-based studies

Recent years have witnessed a growing volume of papers describing the use of GPS technology and other tracking technologies for obtaining data on time–space activities. These methods have several advantages over traditional methods of time–space data collection in terms of accuracy, resolution and length of the possible data collection period. However, to date, no work has been done on the compliance rates among participants and the resulting validity of the collected data. This paper presents a method that combines the use of a GPS receiver with Radio Frequency Identification (RFID) technology that was implemented in research on time–space activities of elderly persons with cognitive impairment. The method presented in this paper enables monitoring the level of compliance of the participants during their participation in the study and presents a unique opportunity to examine the extent to which participants in a GPS based study are able to comply with study requirements. Healthy older adults and those with cognitive decline were found to be generally compliant with a complex study protocol. These results serve as another step into the acceptance of GPS based studies as a valid methodology for mobility data collection.     

The influence of three-way catalysts on harmful emission production

This article deals with the influence of three-way catalysts on the production of basic emissions, such as carbon monoxide, unburned hydrocarbons and nitrogen oxides from spark-ignition engines. A virtual simulation of the new European driving cycle is used. Characteristics of components in emissions in the front and back of the catalyst are measured on the test bed to form the basis of the simulation. The results relate to emissions for 1 km travelled.     

Optimisation of driver actions in RWD race car including tyre thermodynamics

ABSTRACT

The paper presents an innovative method for a lap time minimisation by using genetic algorithms for a multi objective optimisation of a race driver–vehicle model. The decision variables consist of 16 parameters responsible for actions of a professional driver (e.g. time traces for brake, accelerator and steering wheel) on a race track part with RH corner. Purpose-built, high fidelity, multibody vehicle model (called ‘miMa’) is described by 30 generalised coordinates and 440 parameters, crucial in motorsport. Focus is put on modelling of the tyre tread thermodynamics and its influence on race vehicle dynamics. Numerical example considers a Rear Wheel Drive BMW E36 prepared for track day events. In order to improve the section lap time (by 5%) and corner exit velocity (by 4%) a few different driving strategies are found depending on thermal conditions of semi-slick tyres. The process of the race driver adaptation to initially cold or hot tyres is explained.