Finding a Solution for a Complex Street Routing Problem Using the Mixed Transportation Mode

Matis, Peter

doi:10.3846/transport.2010.05

Cited by 8 publications

(5 citation statements)

References 29 publications

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“…The latent preferences of drivers towards possible routes are typically difficult to capture accurately because they are significantly affected by past experience, a subjective interpretation of traffic information provided and personal attitudes dynamically changing traffic conditions. The most existing models are limited in their ability to capture the interacting effects of various situational factors and typically cannot adjust model parameters in a within-day context (Ruiz et al 2004;Daunoras et al 2008;Akgüngör 2008aAkgüngör , 2008bMatis 2008Matis , 2010Kinderytė-Poškienė and Sokolovskij 2008;Gowri and Sivanandan 2008;Niewczas et al 2008;Mesarec and Lep 2009;Çalışkanelli et al 2009;Junevičius and Bogdevičius 2009). The latter capability is critical for consistency-checking procedures for the real-time operational deployment of advanced information systems.…”

Section: Introductionmentioning

confidence: 98%

Route Planning Methodology of an Advanced Traveller Information System in Vilnius City

Jakimavièius

Burinskienė

2010

Transport

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As a subsystem of an Intelligent Transportation System (ITS), an Advanced Traveller Information System (ATIS) disseminates real-time traffic information to travellers. To help them with making better decisions on choosing their routes, a strong need to predict traffic congestion and to disseminate the predicted congestion information relating to travellers can be seen. This paper describes a methodology used by drivers for calculating an optimal driven route in Vilnius. The paper discusses how ATIS systems will likely evolve the experience of Information Service Providers (ISP) and optimal route planning calculations. A few methods of route planning have been taken into account. The paper presents the following types of route calculation: 1) the shortest route; 2) the quickest route; 3) the quickest forecasted route according to historical traffic information. Also, the paper deals with the architecture of the WEB based information system for drivers in Vilnius and analyzes data on traffic workflow. Furthermore, a comprehensive route planning procedure that forecasts data on driving time considering historical traffic is followed.

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Section: Introductionmentioning

confidence: 98%

Route Planning Methodology of an Advanced Traveller Information System in Vilnius City

Jakimavièius

Burinskienė

2010

Transport

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“…Sustainable development is one of the main areas investigated by a number of Lithuanian and foreign scientists including urbanists, architects, experts in the field of transport, environment, economic and other branches of sciences (Ruiz et al 2004;Oppen and Løkketangen 2006;Tanczos and Torok 2007;Ziari et al 2007;Brauers et al 2008;Daunoras et al 2008;Figliozzi 2008;Niewczas et al 2008;Vega and Penne 2008;Antov et al 2009;Burinskienė 2009;Burinskienė and Rudzkienė 2009;Çalışkanelli et al 2009;Janáček and Gábrišová 2009;Li et al 2009;McDonald et al 2009;Mesarec and Lep 2009;Szűcs 2009;Matis 2008Matis , 2010. In a broad sense, the object of sustainable development can be determined both a sustainable city or region or even a country.…”

Section: Introductionmentioning

confidence: 99%

The Evaluation of Investment Projects Within the Territory of Development

Griškevièiûtë‐Geèienë

2010

Transport

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Sustainable development is the most researchable sphere of many experts in urbanistics, architecture, transport, environment and economics in Lithuania. Every period of time has specific problems and solutions to solve them. The present days have increased the level of automobilization and growing traffic in cities has become the main task for sustainable development. State-wide improvement and development of transport infrastructure relate to the level of assigned investments that depend on State transport policy and existing opportunities. Comparing to several EU member states, the procedures of evaluating data on transport infrastructure projects evolved in parallel with the EU-financed projects. Therefore, it could be stated that this area is not falling behind.The analysis of evaluation methods in Lithuania and foreign countries showed that there were no standardized and united methods for evaluating projects on urban system infrastructure. During the last decade, investment projects in cooperation with the State were evaluated using complex analysis in Lithuania. Cost-benefit analysis was and is still being used for evaluating the EU-financed projects. Multicriteria analysis is often carried out in the EU and other countries to evaluate the financial feasibility of transport infrastructure and takes its first steps in Lithuania.

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“…More recent research has appeared following methodologies evaluating public transport systems where, even if bus stops are considered xed, their location plays an important role in determining the quality of service (Chen et al 2009;Shimamoto et al 2010;Hu et al 2010;Niewczas et al 2008;Jakimavičius, Burinskienė 2010;Daunoras et al 2008;Mesarec, Lep 2009;Matis 2010).…”

Section: Introductionmentioning

confidence: 99%

Bus Stop Location Under Different Levels of Network Congestion and Elastic Demand / Autobuso Stotelės Nuotolio Nustatymas Skirtingais Transporto Grūsties Atvejais Reguliuojant Poreikius / Определение Места Автобусной Остановки При Разных Уровнях Транспортного Затора С Целью Регулирования Потребностей

et al. 2011

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The article analyses optimal bus stop locations under different network congestion levels applying a bi-level optimisation model, covering an upper level minimizing an overall cost function (Social Cost) and a lower level that includes a modal split assignment model. This model is applied to Santander city (Spain) under a range of demand levels, starting from very low to high congestion, representing the evolution of variables in each case and analysing different solutions. The optimal distances between stops obtained for each demand and congestion level indicate that very low demands produce wider spaces. However, as demand increases, accessibility to public transport service should be increased and then spacing between bus stops drops to 360 metres. Santrauka Straipsnyje nagrinėjama, kaip nustatyti optimalią autobuso stotelės vietą (nuotolį), esant skirtingiems transporto grūsties lygiams. Taikomas dviejų lygmenų optimizavimo modelis, kuris aukštesniame lygmenyje iki minimumo sumažina bendrąsias (socialines) išlaidas, o žemesniajame – vertina transporto rūšių pasiskirstymo modelį. Šis modelis naudojamas Santandero mieste (Ispanija), kuriame transporto priemonių poreikiai grūsties atveju svyruoja nuo labai mažo iki didelio ir kiekvieną kartą reškia kintamųjų kaitą, analizuojant skirtingus sprendimus. Kiekvienu atveju tarp stotelių gauti optimalūs nuotoliai rodo, kad labai maži transportavimo poreikiai ir grūsties lygis sukuria daugiau erdvės. Tačiau, jiems didėjant, turėtų padidėti ir galimybės naudotis viešuoju transportu. Tokiu atveju nuotoliai tarp autobusų stotelių mažėja iki 360 metrų. Резюме Исследуется проблема определения конкретного расстояния (месторасположения) между автобусными остановками при разных уровнях транспортных заторов. Для этого используется оптимизационная модель, благодаря которой снижаются до минимума обобщенные (социальные) расходы, а также учитывается модель распределения типов транспорта. Данная модель нашла практическое применение в испанском городе Сантандер. В этом городе потребность в транспортных средствах во время заторов изменяется от очень маленького до очень большого значения и каждый раз по-своему влияет на значения переменных, что затрудняет анализ и принятие решения. Оптимальные расстояния между остановками, полученные в каждом случае, показывают, что малая потребность в транспортировании и малый уровень заторов создают большее пространство. А при их возрастании потребность в общественном транспорте также должна увеличиваться. В этом случае расстояния между автобусными остановками уменьшаются до 360 метров.

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Finding a Solution for a Complex Street Routing Problem Using the Mixed Transportation Mode

Cited by 8 publications

References 29 publications

Route Planning Methodology of an Advanced Traveller Information System in Vilnius City

Route Planning Methodology of an Advanced Traveller Information System in Vilnius City

The Evaluation of Investment Projects Within the Territory of Development

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