Road network and GPS tracking with data processing and quality assessment

GPS technology has been embedded into portable, low-cost electronic devices nowadays to track the movements of mobile objects. This implication has greatly impacted the transportation field by creating a novel and rich source of traffic data on the road network. Although the promise offered by GPS devices to overcome problems like underreporting, respondent fatigue, inaccuracies and other human errors in data collection is significant; the technology is still relatively new that it raises many issues for potential users. These issues tend to revolve around the following areas: reliability, data processing and the related application. This thesis aims to study the GPS tracking form the methodological, technical and practical aspects. It first evaluates the reliability of GPS based traffic data based on data from an experiment containing three different traffic modes (car, bike and bus) traveling along the road network. It then outline the general procedure for processing GPS tracking data and discuss related issues that are uncovered by using real-world GPS tracking data of 316 cars. Thirdly, it investigates the influence of road network density in finding optimal location for enhancing travel efficiency and decreasing travel cost. The results show that the geographical positioning is reliable. Velocity is slightly underestimated, whereas altitude measurements are unreliable.Post processing techniques with auxiliary information is found necessary and important when solving the inaccuracy of GPS data. The densities of the road network influence the finding of optimal locations. The influence will stabilize at a certain level and do not deteriorate when the node density is higher.

On processing GPS tracking data of car-movements in Borlänge, Sweden

The advancement of GPS technology enables GPS devices not only to be used as orientation and navigation tools, but also to track travelled routes. GPS tracking data provides essential information for a broad range of urban planning applications such as transportation routing and planning, traffic management and environmental control. This paper describes on processing the data that was collected by tracking the cars of 316 volunteers over a seven-week period. The detailed information is extracted. The processed data is further connected to the underlying road network by means of maps. Geographical maps are applied to check how the car-movements match the road network. The maps capture the complexity of the car-movements in the urban area. The results show that 90% of the trips on the plane match the road network within a tolerance.

On processing GPS tracking data of spatiotemporal car movements : a case study

The advancement of GPS technology has made it possible to use GPS devices as orientation and navigation tools, but also as tools to track spatiotemporal information. GPS tracking data can be broadly applied in location-based services, such as spatial distribution of the economy, transportation routing and planning, traffic management and environmental control. Therefore, knowledge of how to process the data from a standard GPS device is crucial for further use. Previous studies have considered various issues of the data processing at the time. This paper, however, aims to outline a general procedure for processing GPS tracking data. The procedure is illustrated step-by-step by the processing of real-world GPS data of car movements in Borlänge in the centre of Sweden.

Reliability of GPS based traffic data: an experimental evaluation

GPS tracking of mobile objects provides spatial and temporal data for a broad range of applications including traffic management and control, transportation routing and planning. Previous transport research has focused on GPS tracking data as an appealing alternative to travel diaries. Moreover, the GPS based data are gradually becoming a cornerstone for real-time traffic management. Tracking data of vehicles from GPS devices are however susceptible to measurement errors – a neglected issue in transport research. By conducting a randomized experiment, we assess the reliability of GPS based traffic data on geographical position, velocity, and altitude for three types of vehicles; bike, car, and bus. We find the geographical positioning reliable, but with an error greater than postulated by the manufacturer and a non-negligible risk for aberrant positioning. Velocity is slightly underestimated, whereas altitude measurements are unreliable.

Out-of-town shopping and its induced CO2-emissions

Planning policies in several European countries have aimed at hindering the expansion of out-of-town shopping centers. One argument for this is concern for the increase in transport and a resulting increase in environmental externalities such as CO2-emissions. This concern is weakly founded in science as few studies have attempted to measure CO2-emissions of shopping trips as a function of the location of the shopping centers. In this paper we conduct a counter-factual analysis comparing downtown, edge-of-town and out-of-town shopping. In this comparison we use GPS to track 250 consumers over a time-span of two months in a Swedish region. The GPS-data enters the Oguchi’s formula to obtain shopping trip-specific CO2-emissions. We find that consumers’ out-of-town shopping would generate an excess of 60 per cent CO2-emissions whereas downtown and edge-of-town shopping centers are comparable.

Trips and their CO2 emissions induced by a shopping center

Most previous studies have focused on entire trips in a geographic region, while a few of them addressed trips induced by a city landmark. Therefore paper explores trips and their CO2 emissions induced by a shopping center from a time-space perspective and their usage in relocation planning. This is conducted by the means of a case study in the city of Borlänge in mid-Sweden where trips to the city’s largest shopping mall in its center are examined. We use GPS tracking data of car trips that end and start at the shopping center. Thereafter, (1) we analyze the traffic emission patterns from a time-space perspective where temporal patterns reveal an hourly-based traffic emission dynamics and where spatial patterns uncover a heterogeneous distribution of traffic emissions in spatial areas and individual street segments. Further, (2) this study reports that most of the observed trips follow an optimal route in terms of CO2 emissions. In this respect, (3) we evaluate how well placed the current shopping center is through a comparison with two competing locations. We conclude that the two suggested locations, which are close to the current shopping center, do not show a significant improvement in term of CO2 emissions.

To what extent are CO2 emissions from intra-urban shopping trips by cars affected by drivers’ travel behaviour and store location?

Transportation is seen as one of the major sources of CO2 pollutants nowadays. The impact of increased transport in retailing should not be underestimated. Most previous studies have focused on transportation and underlying trips, in general, while very few studies have addressed the specific affects that, for instance, intra-city shopping trips generate. Furthermore, most of the existing methods used to estimate emission are based on macro-data designed to generate national or regional inventory projections. There is a lack of studies using micro-data based methods that are able to distinguish between driver behaviour and the locational effects induced by shopping trips, which is an important precondition for energy efficient urban planning. The aim of this study is to implement a micro-data method to estimate and compare CO2 emission induced by intra-urban car travelling to a retail destination of durable goods (DG), and non-durable goods (NDG). We estimate the emissions from aspects of travel behaviour and store location. The study is conducted by means of a case study in the city of Borlänge, where GPS tracking data on intra-urban car travel is collected from 250 households. We find that a behavioural change during a trip towards a CO2 optimal travelling by car has the potential to decrease emission to 36% (DG), and to 25% (NDG) of the emissions induced by car-travelling shopping trips today. There is also a potential of reducing CO2 emissions induced by intra-urban shopping trips due to poor location by 54%, and if the consumer selected the closest of 8 existing stores, the CO2 emissions would be reduced by 37% of the current emission induced by NDG shopping trips.

Residential planning, driver mobility and CO2 emission

The literature on residences and citizens’ transports has focused on either reforming traffic managing in response to residential relocation or post-evaluation of urban planning policies or the evolution of the urban spatial form. In a city there are hotspots that attract the citizens and most of the transportation in the city arises as the citizens’ movement between their residence and the hotspots. Little scholarly attention has been devoted to the possibility to minimize citizens’ transportation in the city by the urban planning of residential areas. In this paper we propose a method to evaluate the environmental impact (in terms of CO2-emissions) of urban plans of residential areas. The method is illustrated in a Swedish case of a midsize city which is presently preoccupied with urban planning of new residential areas in response to substantial population growth due to immigration. The residential plans aims to increase the compactness and residential density in the current center and sub centers leads to less CO2 emissions compare to urban expansion to the edge of the city. The plans of concentrated apartment buildings are more effective in meeting residential needs and mitigating CO2 emissions than dispersed single-family houses.