An analysis of ridesharing trip time using advanced text mining techniques

The time cost of ridesharing rental represents a crucial factor influencing users'decisions to rent a car.Researchers have explored this aspect through text analysis and questionnaires.However,the current research faces limitations in terms of data quantity and analysis methods,preventing the extraction of key information.Therefore,there is a need to further optimize the level of public opinion analysis.This study aimed to investigate user perspectives concerning travel time in ridesharing,both pre and post-pandemic,within the Twitter application.Our analysis focused on a dataset from users residing in the USA and India,with considerations for demographic variables such as age and gender.To accomplish our research objectives,we employed Latent Dirichlet Allocation for topic modeling and BERT for sentiment analysis.Our findings revealed significant influences of the pandemic and the user's country of origin on sentiment.Notably,there was a discernible increase in positive sentiment among users from both countries following the pandemic,particularly among older individuals.These findings bear relevance to the ridesharing industry,offering insights that can aid in establishing benchmarks for improving travel time.Such improvements are instrumental in enabling ridesharing companies to effectively compete with other public transportation alternatives.

City-wide vehicle dispatching for multi-hop ridesharing package delivery

The city-wide ridesharing package delivery is becoming popular as it provides a convenience such as extra profits to the vehicle’s driver and high traffic efficiency to the city.The vehicle dispatching is a significant issue to improve the ridesharing efficiency in package delivery.The classic one-hop ridesharing package delivery requires the highly similar paths between the package and the vehicle given by the limited detour time,which depresses the ridesharing efficiency.To tackle this problem,a city-wide vehicle dispatching strategy for the multi-hop ridesharing package delivery was proposed,where a package is permitted to be delivered sequentially by different vehicles,until arriving the destination.The study formulates the vehicle dispatching as a maximum multi-dimensional bipartite matching problem with the goal of maximizing the total saving distance given by the limited detour time and ridesharing capacity.A multi-hop ridesharing vehicle dispatching algorithm was proposed to solve this problem by selecting the farthest reachable locker and multi-dimensional matching.Simulation results based on real vehicle dataset of Beijing demonstrate the effectiveness and efficiency of the proposed vehicle dispatching strategy.

A Dynamic Programming Algorithm for the Ridersharing Problem Restricted with Unique Destination and Zero Detour on Trees

We deal with the problem of sharing vehicles by individuals with similar itineraries which is to find the minimum number of drivers, each of which has a vehicle capacity and a detour to realize all trips. Recently, Gu et al. showed that the problem is NP-hard even for star graphs restricted with unique destination, and gave a polynomial-time algorithm to solve the problem for paths restricted with unique destination and zero detour. In this paper we will give a dynamic programming algorithm to solve the problem in polynomial time for trees restricted with unique destination and zero detour. In our best knowledge it is a first polynomial-time algorithm for trees.