Optimization of bus stop placement for routes on uneven topography

Ceder, Avishai; Butcher, Matthew; Wang, Lingli

doi:10.1016/j.trb.2015.01.006

Cited by 44 publications

(28 citation statements)

References 20 publications

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“…(1) Bus stops: For a public bus route, one key factor that affects public transportation quality is the location of bus stops [3,11,26]. The majority of the previous studies typically treated bus stop spacing as a continuous variable by assuming that bus stops could be located anywhere along the transport routes.…”

Section: Transport Network Optimizationmentioning

confidence: 99%

“…To improve the service reliability of a bus service, Chien and Qin [28] formulated a mathematical model to optimize the bus stop location problem. Recently, Ceder et al [26] developed a mathematical modeling approach to bus stop placement by considering uneven topography. Their results suggested a number of ways, including walking speed, access path attractiveness, and acceleration delay, that will lead to optimal bus stop placement.…”

Section: Transport Network Optimizationmentioning

confidence: 99%

“…Taking bus route 031 as an example (Figure 10), the optimization measure for route 031 is to optimize the bus stop placement to avoid the congested RSB. Preliminary evaluation criteria according to previous studies [11,26,34]: (1) The number of multiplexed routes: According to the Zhongshan public transport network, the number of multiplexed routes between the Social Security Bureau stop and the Local Taxation Preliminary evaluation criteria according to previous studies [11,26,34]: (1) The number of multiplexed routes: According to the Zhongshan public transport network, the number of multiplexed routes between the Social Security Bureau stop and the Local Taxation Bureau stop is 6, which are routes 024, 030, 031, 038, 216, and BRT15. The reuse of multiple bus lines is an important inducement of road congestion.…”

Section: An Example Of Ptn Optimization Based On Congested Rsbsmentioning

confidence: 99%

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Public Traffic Congestion Estimation Using an Artificial Neural Network

Wang

Dong

2020

IJGI

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Alleviating public traffic congestion is an efficient and effective way to improve the travel time reliability and quality of public transport services. The existing public network optimization models usually ignored the essential impact of public traffic congestion on the performance of public transport service. To address this problem, this study proposes a data-based methodology to estimate the traffic congestion of road segments between bus stops (RSBs). The proposed methodology involves two steps: (1) Extracting three traffic indicators of the RSBs from smart card data and bus trajectory data; (2) The self-organizing map (SOM) is used to cluster and effectively recognize traffic patterns embedded in the RSBs. Furthermore, a congestion index for ranking the SOM clusters is developed to determine the congested RSBs. A case study using real-world datasets from a public transport system validates the proposed methodology. Based on the congested RSBs, an exploratory example of public transport network optimization is discussed and evaluated using a genetic algorithm. The clustering results showed that the SOM could suitably reflect the traffic characteristics and estimate traffic congestion of the RSBs. The results obtained in this study are expected to demonstrate the usefulness of the proposed methodology in sustainable public transport improvements. these network optimization models developed in the above-mentioned articles had been usually applied in uncongested road segments.Public traffic condition refers to the traffic volume of the road network and its dynamic spatial-temporal distribution, which can reflect the degree of congestion [8]. Recently, the traffic congestion impacts of bus operations on a road segment or a corridor have been investigated by researchers [9,10]. These congestion effects mainly include the effects of bus stop design, bus travel time, and bus priority options such as exclusive bus lanes or priority signals for buses [9]. Understanding these congestion impacts can help operators to identify the effectiveness of transport network optimization in relieving congested areas or congested routes. For example, under congested traffic conditions, it is difficult for buses to return to the driving lane, which leads to a longer travel time after picking-up/dropping off passengers at stops [11]. Furthermore, the bus travel time variation dominated by traffic congestion often results in unreliable service, which has negative impacts on both the operators and passengers [12]. Previous studies have pointed out that well-located stops have the potential to alleviate the impact of traffic congestion [3]. Therefore, it is critical to optimize PTN by considering the impact of traffic congestion in order to achieve a high level of public transport service and improve travel time reliability.In this study, we proposed a data-based methodology to estimate the traffic congestion of road segments between bus stops (RSBs) using a self-organizing feature map (SOM). The SOM was used to cluster and effective...

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Section: Transport Network Optimizationmentioning

confidence: 99%

Section: Transport Network Optimizationmentioning

confidence: 99%

Section: An Example Of Ptn Optimization Based On Congested Rsbsmentioning

confidence: 99%

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Public Traffic Congestion Estimation Using an Artificial Neural Network

Wang

Dong

2020

IJGI

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“…Wie intensiv eine Haltestelle genutzt wird ist abhängig von der Umgebung, in der sie platziert ist. Bei der Platzierung von Haltestellen müssen daher auch die topographischen Gegebenheiten berücksichtigt werden (Ceder et al 2015). Auch Chakour und Eluru (2016) stellen bei ihrer Analyse der Einflussfaktoren auf das Fahrgastaufkommen Faktoren, wie an die Haltestelle angrenzende Parks, Schnellstraßen oder Firmen in den Vordergrund (Chakour und Eluru 2016).…”

Section: Fachlicher Hintergrundunclassified

Die Zukunft der Bushaltestelle vor dem Hintergrund von Mobility-as-a-Service – Eine qualitative Betrachtung des öffentlichen Personennahverkehrs in Deutschland

Hahn,

Pakusch,

Stevens

2020

HMD

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Zusammenfassung Die Bundesrepublik Deutschland erlebt in jüngster Vergangenheit verstärkt Dieselfahrverbote in Großstädten. Gleichzeitig erfahren Großstädte als Lebensmittelpunkt eine steigende Beliebtheit. Für Verkehrsunternehmen gilt es, der Bevölkerung nachhaltige Mobilitätslösungen zu bieten, die ein Höchstmaß an Flexibilität ermöglichen. Moderne Mobility-as-a-Service-Konzepte und Innovationen in der Mobilität stellen den klassischen, planorientierten, öffentlichen Personennahverkehr und damit auch die Existenz von Bushaltestellen infrage. Mittels qualitativer Experten-Interviews lässt sich feststellen, dass sich die Bushaltestelle in den Innenstädten vor dem Hintergrund zunehmender digitaler Vernetzung von Mobilitätsanbietern und daraus resultierender modernen Mobility-as-a-service-Konzepte verändern wird. Die Ergebnisse deuten darauf hin, dass die Bushaltestelle in den Innenstädten auch in Zukunft bestehen bleibt und um "on demand"-Verkehre ergänzt wird. Ein radikaler Wandel, wie eine flächendeckende Einführung von autonom fahrenden Bussen, könnte langfristig eine Runderneuerung der Haltestelle zur Folge haben.

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“…Only by changing and renovating the infrastructure, is it possible to raise the value of public transport system and the willingness to use it. Many scientists [4,[6][7][8][9][10][12][13][14] have already studied the impact of various elements of infrastructure on the public transport system and the passenger satisfaction with it. The overview of these scientific studies was carried out to select the elements which hereafter are subjected to the multi-criteria analysis of the public transport system.…”

Section: Introductionmentioning

confidence: 99%

Multi-criteria Analysis of Indicators of the Public Transport Infrastructure

Ušpalytė−Vitkūnienė

Šarkienė

Žilionienė

2020

PROMET

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Public transport is a key element of sustainable transport in medium and large cities. Therefore, it is important that city residents want to use it. This paper aims to determine the criteria of the public transport infrastructure which have the most influence on passenger satisfaction with the public transport system. The criteria of public transport infrastructure of stops, vehicles, and route network were analysed. The primary attention was focused on rating these criteria from the most to the least important one. The analysis of scientific papers, specialized literature, Europe Union regulations, Lithuanian legislation, and recommendations were used to explore the necessary criteria that have a significant effect on the popularity of public transport, its functionality and gives a reference on how to raise the willingness of the citizens to use public transport. The experts (14 experts were involved) and social surveys (440 respondents were involved) were used to identify the evaluation criteria of public transport infrastructure and to investigate the state of these criteria. These criteria were grouped into three larger groups according to their nature (public transport infrastructure of stops, vehicles and route network) and were rated and prioritized by the multi-criteria analysis. The results reflect the priorities of criteria parameters of public transport infrastructure. The results show that when investing in public transport infrastructure, the main priority should be attributed to the infrastructure elements, such as public transport priority in the streets, then shelters, lighting, cleanness of bus stops and vehicles, which are physically appreciable. These parameters have the most significant impact on improving the level of service of public transport infrastructure in urban areas.

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Optimization of bus stop placement for routes on uneven topography

Cited by 44 publications

References 20 publications

Public Traffic Congestion Estimation Using an Artificial Neural Network

Public Traffic Congestion Estimation Using an Artificial Neural Network

Die Zukunft der Bushaltestelle vor dem Hintergrund von Mobility-as-a-Service – Eine qualitative Betrachtung des öffentlichen Personennahverkehrs in Deutschland

Multi-criteria Analysis of Indicators of the Public Transport Infrastructure

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