Uncertainty in urban mobility: Predicting waiting times for shared bicycles and parking lots

Author(s):  
Bei Chen ◽  
Fabio Pinelli ◽  
Mathieu Sinn ◽  
Adi Botea ◽  
Francesco Calabrese
2020 ◽  
Author(s):  
Caroline Mazetto Mendes ◽  
Willian Marrion Cavenagli

Parking lots are no longer practical solutions but become anothertopic of urban mobility problem due to the difficulty in finding availableparking spaces. This work proposes a parking space detectionsystem to assist drivers. The system detects unoccupied vacanciesby image processing techniques and convolutional neural networks.Vacancies are detected through horizontal markings and by recognizingspaces with or without vehicles. Finally, a mobile applicationmakes available to the user the occupancy status of vacancies. Initialresults showed that the system detects vacancies with visiblemarkings during the daytime. To improve detection in adversesituations, the vacancy detection algorithm is being improved.


2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Huang Yantao ◽  
Kara M. Kockelman ◽  
Long T. Truong

Before shared automated vehicles (SAVs) can be widely adopted, they are anticipated to be implemented commercially in confined regions or fixed routes where the benefits of automation can be realized. SAVs have the potential to operate in a traditional transit corridor, replacing conventional transit vehicles, and have frequent interactions with riders and other vehicles sharing the same right of way. This paper microsimulates SAVs’ operation on a 6.5-mile corridor to understand how vehicle size and attributes of such SAV-based transit affect traffic, transit riders, and system costs. The SUMO (Simulation of Urban MObility) platform is employed to model microscopic interactions among SAVs, transit passengers, and other traffic. Results show that the use of smaller, but more frequent, SAVs leads to reduced passenger waiting times but increased vehicle travel times. More frequent services of smaller SAVs do not, in general, significantly affect general traffic due to shorter dwell times. Overall, using smaller SAVs instead of the large 40-seat SAVs can reduce system costs by up to 4% while also reducing passenger waiting times, under various demand levels and passenger loading factors. However, the use of 5-seat SAVs does not always have the lowest system costs.


2020 ◽  
Vol 65 (1) ◽  
pp. 27-44 ◽  
Author(s):  
Houshmand Masoumi ◽  
Erik Fruth

AbstractThe number of urban mobility studies and projects in the three large metropoles of the Middle East and North Africa (MENA) region, Tehran, Istanbul, and Cairo, is growing while other large cities do not enjoy a large share. It would be efficient for those other large cities to adapt the experiences, projects, and studies of Tehran, Istanbul, and Cairo to their own contexts. This paper can help facilitate that adaptation. It investigates the transferability and generalisability of the findings of a recent publication by the lead author on mobility choices in Tehran, Istanbul, and Cairo to some other large cities of more than one million inhabitants in the MENA region. The discussion provided here can provide decision-makers in the MENA region with guidance on how to utilise the findings from a recent study on Tehran/Istanbul/Cairo in their own contexts. T-tests were conducted to test the comparability of the three base cities with a sample 57 others with populations of over one million people. The results show that it would be possible to adapt the urban mobility studies of the three base megacities to 3 to 27 cities based on different criteria. Key suggestions identified by this study include providing local accessibility, neighbourhood facilities, and cycling facilities as well as removing social and legal constraints to cycling, advertising cycling, informing people about the harm arising from the overuse of cars, and increasing street connectivity by adding intersections. According to the findings, these evidence-based recommendations can enhance sustainable mobility for the inhabitants of up to 27 large cities.


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