Enhancing urban mobility: Integrating ride-sharing and public transit

Stiglic, Mitja; Agatz, Niels; Savelsbergh, Martin W. P.; Gradišar, Miro

doi:10.1016/j.cor.2017.08.016

Cited by 229 publications

(100 citation statements)

References 14 publications

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“…This feature applies to both passengers and goods but can have some variations. For example, in some ridesharing applications, a passenger can be picked up or dropped off at an intermediate location, usually called meeting point, which can lead to shorter detours (Stiglic et al (2016a)). Another example is found in multi-echelon transportation systems where goods are transported through a scheduled line to a public transport station and then delivered by vehicle to their final destination (Ghilas et al (2016b)).…”

Section: Routing Constraints (Rc)mentioning

confidence: 99%

A survey of models and algorithms for optimizing shared mobility

Mourad

Puchinger

Chu

2019

Transportation Research Part B: Methodological

238

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The rise of research into shared mobility systems reflects emerging challenges, such as rising traffic congestion, rising oil prices and rising environmental concern. The operations research community has turned towards more sharable and sustainable systems of transportation. Shared mobility systems can be collapsed into two main streams: those where people share rides and those where parcel transportation and people transportation are combined. This survey sets out to review recent research in this area, including different optimization approaches, and to provide guidelines and promising directions for future research. It makes a distinction between prearranged and real-time problem settings and their methods of solution, and also gives an overview of real-case applications relevant to the research area.

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Section: Routing Constraints (Rc)mentioning

confidence: 99%

A survey of models and algorithms for optimizing shared mobility

Mourad

Puchinger

Chu

2019

Transportation Research Part B: Methodological

238

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show abstract

“…Every traveller has her/his own travel behaviour regarding the travel purpose, final destination and time. Each traveller needs the flexibility to choose and adapt her/his individual package (Stiglic et al 2018). A good example of integrated mobility can be a Google Trip Planner that enables to identify the best route and smarter decisions of traveling (Mahmoud et al, 2015).…”

Section: Integrated Mobilitymentioning

confidence: 99%

Business Models Innovation for Sustainable Urban Mobility in Small and Medium-Sized European Cities

Bellini

Dulskaia

Savastano

et al. 2019

Management &Amp; Marketing. Challenges for the Knowledge Society

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Bad air conditions, limitless traffic, overloaded parking spaces are just some of the modern mobility problems that strike cities on a daily basis. The European Commission strives to address these issues by providing measures to improve the urban mobility situation in the small and medium-sized cities. The SUITS project (Supporting Urban Integrated Transport Systems: Transferable Tools for Authorities), which is financed under the umbrella of the HORIZON 2020 programme, aims at increasing the capacity of local authorities in Small and Medium (S-M) cities through the development and implementation of sustainable, integrated and accessible transport strategies and technologies. This paper aims to analyse and classify the innovative business models in the urban mobility sector that are aimed at increasing the capacity building of S-M cities' transportation authorities through the implementation of new mobility solutions. It describes the innovative mobility business identifying the most successful models of service and partnerships in the sector.

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“…Stiglic et al examined improving urban mobility by combining ride-sharing and public transportation that contribute fast, reliable, and affordable transfer to and from transportation stations in rural areas. Although the computational operations note that connecting ride-sharing and public transit can significantly enhance urban mobility, driver willingness to serve more than one rider is crucial for success (Stiglic et al, 2018). Simonetto et al introduced a novel, computationally efficient, a dynamic algorithm to simulate real-time city-scale ridesharing via linear assignment problems.…”

Section: Literature Reviewmentioning

confidence: 99%

An Agent-Based Modelling for Ride Sharing Optimization Using A* Algorithm and Clustering Approach

Gorgoon

Davoodi

Motieyan

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission VI, WG VI/4 ABSTRACT:Today, city management is one of the great challenges facing the world. The growth of population, industries, and services is in urgent need of transportation on a large scale. Meanwhile, transportation has great importance in urban management. Therefore, it is necessary to solve the traffic problem with scientific methods and reduce the traffic load of cities. An interesting way to reduce urban travels is using 2,3, or 4 people from one car that it is known as "Ride Sharing". In this research, the NetLogo software is used to simulate travel sharing scenarios. The three considered parameters are the number of passengers, the acceptable travel sharing radius, and the acceptable waiting time. The proposed algorithm uses a clustering method to find the best candidates to share a ride. Several scenarios were performed to evaluate numerical results. The number of passengers was 100, and 500, the radius of the trip was 1,000 and 2,000 meters, and the waiting time was 10 and 20 minutes. So, 8 experiments were carried out. The least amount of travel sharing was observed in the first scenario (100 passengers, 1000 m travel sharing radius and 10 minutes waiting time), in which 2% of single trips dropped out. The most sharing trips were in the final scenario (500 passengers, 2000 meters radius and 20 minutes waiting time), which saw a decrease of 36.4% of single trips. So, it can be said that sharing a trip can reduce traffic in cities and consequently reduce urban costs and either air pollution or noise pollution.

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Enhancing urban mobility: Integrating ride-sharing and public transit

Cited by 229 publications

References 14 publications

A survey of models and algorithms for optimizing shared mobility

A survey of models and algorithms for optimizing shared mobility

Business Models Innovation for Sustainable Urban Mobility in Small and Medium-Sized European Cities

An Agent-Based Modelling for Ride Sharing Optimization Using A* Algorithm and Clustering Approach

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