Urban network travel time estimation from stop-line loop detector data and signal controller data

This paper presents a model to estimate travel time using cumulative plots. Three different cases considered are i) case-Det, for only detector data; ii) case-DetSig, for detector data and signal controller data and iii) case-DetSigSFR: for detector data, signal controller data and saturation flow rate. The performance of the model for different detection intervals is evaluated. It is observed that detection interval is not critical if signal timings are available. Comparable accuracy can be obtained from larger detection interval with signal timings or from shorter detection interval without signal timings. The performance for case-DetSig and for case-DetSigSFR is consistent with accuracy generally more than 95% whereas, case-Det is highly sensitive to the signal phases in the detection interval and its performance is uncertain if detection interval is integral multiple of signal cycles.

Volcanic sulphate and Arctic dust plumes over the North Atlantic Ocean

High time resolution aerosol mass spectrometry measurements were conducted during a field campaign at Mace Head Research Station, Ireland, in June 2007. Observations on one particular day of the campaign clearly indicated advection of aerosol from volcanoes and desert plains in Iceland which could be traced with NOAA Hysplit air mass back trajectories and satellite images. In conjunction with this event, elevated levels of sulphate and light absorbing particles were encountered at Mace Head. While sulphate concentration was continuously increasing, nitrate levels remained low indicating no significant contribution from anthropogenic pollutants. Sulphate concentration increased about 3.8 g/m3 in comparison with the background conditions. Corresponding sulphur flux from volcanic emissions was estimated to about 0.3 TgS/yr, suggesting that a large amount of sulphur released from Icelandic volcanoes may be distributed over distances larger than 1000 km. Overall, our results corroborate that transport of volcanogenic sulphate and dust particles can significantly change the chemical composition, size distribution, and optical properties of aerosol over the North Atlantic Ocean and should be considered accordingly by regional climate models.

The influence of travel time and size of shopping center towards the frequencies of visiting customers in shopping centers in surabaya

Visiting a modern shopping center is becoming vital in our society nowadays. The fast growth of shopping center, transportation system, and modern vehicles has given more choices for consumers in shopping. Although there are many reasons for the consumers in visiting the shopping center, the influence of travel time and size of shopping center are important things to be considered towards the frequencies of visiting customers in shopping centers. A survey to the customers of three major shopping centers in Surabaya has been conducted to evaluate the Ellwood’s model and Huff’s model. A new exponent value N of 0.48 and n of 0.50 has been found from the Ellwood’s model, while a coefficient of 0.267 and an add value of 0.245 have been found from the Huff’s model.

Analytical modeling and sensitivity analysis for travel time estimation on signalized urban networks

This paper presents a model for estimation of average travel time and its variability on signalized urban networks using cumulative plots. The plots are generated based on the availability of data: a) case-D, for detector data only; b) case-DS, for detector data and signal timings; and c) case-DSS, for detector data, signal timings and saturation flow rate. The performance of the model for different degrees of saturation and different detector detection intervals is consistent for case-DSS and case-DS whereas, for case-D the performance is inconsistent. The sensitivity analysis of the model for case-D indicates that it is sensitive to detection interval and signal timings within the interval. When detection interval is integral multiple of signal cycle then it has low accuracy and low reliability. Whereas, for detection interval around 1.5 times signal cycle both accuracy and reliability are high.

Performance evaluation of an adaptive travel time prediction model

This paper presents a travel time prediction model and evaluates its performance and transferability. Advanced Travelers Information Systems (ATIS) are gaining more and more importance, increasing the need for accurate, timely and useful information to the travelers. Travel time information quantifies the traffic condition in an easy to understand way for the users. The proposed travel time prediction model is based on an efficient use of nearest neighbor search. The model is calibrated for optimal performance using Genetic Algorithms. Results indicate better performance by using the proposed model than the presently used naïve model.

Estimation of travel time on urban networks with midlink sources and sinks

This paper presents a methodology for estimation of average travel time on signalized urban networks by integrating cumulative plots and probe data. This integration aims to reduce the relative deviations in the cumulative plots due to midlink sources and sinks. During undersaturated traffic conditions, the concept of a virtual probe is introduced, and therefore, accurate travel time can be obtained when a real probe is unavailable. For oversaturated traffic conditions, only one probe per travel time estimation interval—360 s or 3% of vehicles traversing the link as a probe—has the potential to provide accurate travel time.

Effect of rain on travel demand and traffic accidents

This paper studies the effect of rain on travel demand measured on the Tokyo Metropolitan Expressway (MEX). Rainfall data monitored by the Japan Meteorological Agency's meso-scale network of weather stations are used. This study found that travel demand decreases during rainy days and, in particular, larger reductions occur over the weekend. The effect of rainfall on the number of accidents recorded on 10 routes on the MEX is also analysed. Statistical testing shows that the average frequency of accidents, during periods of rainfall, is significantly different from the average frequency at other times.

Use of electronic travel diaries and vehicle instrumentation packages in the year 2000 : Atlanta Regional Household Travel Survey

The Georgia Institute of Technology is currently performing research that will result in the development and deployment of three instrumentation packages that allow for automated capture of personal travel-related data for a given time period (up to 10 days). These three packages include: A handheld electronic travel diary (ETD) with Global Positioning System (GPS) capabilities to capture trip information for all modes of travel; A comprehensive electronic travel monitoring system (CETMS), which includes an ETD, a rugged laptop computer, a GPS receiver and antenna, and an onboard engine monitoring system, to capture all trip and vehicle information; and a passive GPS receiver, antenna, and data logger to capture vehicle trips only.

Investigation into travel of transit oriented development : school students’ travel survey of Kelvin Grove Urban Village

Travel surveys were conducted for collecting data related to school students’ travel at Kelvin Grove Urban Village (KGUV). Currently, KGUV has school students studying at grade 10 to 12. As a part of data collection process, travel surveys were undertaken for school students studying. This document contains the questionnaire form used to collect the demographic and travel data related to school students at KGUV. The surveys forms were hand delivered to the school and the responses were collected back via reply paid envelop provided with the questionnaire form.

New media services : ratings and recommendations websites in the travel and tourism industry

The travel and hospitality industry is one which relies especially crucially on word of mouth, both at the level of overall destinations (Australia, Queensland, Brisbane) and at the level of travellers’ individual choices of hotels, restaurants, sights during their trips. The provision of such word-of-mouth information has been revolutionised over the past decade by the rise of community-based Websites which allow their users to share information about their past and future trips and advise one another on what to do or what to avoid during their travels. Indeed, the impact of such user-generated reviews, ratings, and recommendations sites has been such that established commercial travel advisory publishers such as Lonely Planet have experienced a pronounced downturn in sales ¬– unless they have managed to develop their own ways of incorporating user feedback and contributions into their publications. This report examines the overall significance of ratings and recommendation sites to the travel industry, and explores the community, structural, and business models of a selection of relevant ratings and recommendations sites. We identify a range of approaches which are appropriate to the respective target markets and business aims of these organisations, and conclude that there remain significant opportunities for further operators especially if they aim to cater for communities which are not yet appropriately served by specific existing sites. Additionally, we also point to the increasing importance of connecting stand-alone ratings and recommendations sites with general social media spaces like Facebook, Twitter, and LinkedIn, and of providing mobile interfaces which enable users to provide updates and ratings directly from the locations they happen to be visiting. In this report, we profile the following sites: * TripAdvisor, the international market leader for travel ratings and recommendations sites, with a membership of some 11 million users; * IgoUgo, the other leading site in this field, which aims to distinguish itself from the market leader by emphasising the quality of its content; * Zagat, a long-established publisher of restaurant guides which has translated its crowdsourcing model from the offline to the online world; * Lonely Planet’s Thorn Tree site, which attempts to respond to the rise of these travel communities by similarly harnessing user-generated content; * Stayz, which attempts to enhance its accommodation search and booking services by incorporating ratings and reviews functionality; and * BigVillage, an Australian-based site attempting to cater for a particularly discerning niche of travellers; * Dopplr, which connects travel and social networking in a bid to pursue the lucrative market of frequent and business travellers; * Foursquare, which builds on its mobile application to generate a steady stream of ‘check-ins’ and recommendations for hospitality and other services around the world; * Suite 101, which uses a revenue-sharing model to encourage freelance writers to contribute travel writing (amongst other genres of writing); * Yelp, the global leader in general user-generated product review and recommendation services. In combination, these profiles provide an overview of current developments in the travel ratings and recommendations space (and beyond), and offer an outlook for further possibilities. While no doubt affected by the global financial downturn and the reduction in travel that it has caused, travel ratings and recommendations remain important – perhaps even more so if a reduction in disposable income has resulted in consumers becoming more critical and discerning. The aggregated word of mouth from many tens of thousands of travellers which these sites provide certainly has a substantial influence on their users. Using these sites to research travel options has now become an activity which has spread well beyond the digirati. The same is true also for many other consumer industries, especially where there is a significant variety of different products available – and so, this report may also be read as a case study whose findings are able to be translated, mutatis mutandis, to purchasing decisions from household goods through consumer electronics to automobiles.