This paper will review the match between single driver and single rider in online taxi services through a resource sharing (sharing platform) for the operators with the objectives to maximize the profit for drivers (operators) and minimize waiting time for passengers so that the matching rate is higher. A low matching rate between rider and driver can cause the consumer to drop the services. The matching between single driver and single rider in online taxi services through a sharing platform scheme is formulated in maximum weighted bipartite matching problem. To solve the proposed model, we use Kuhn Munkres Algorithm, while to solve the shortest path for the driver to pick up the passenger and the shortest path of passenger's origin destination, modified Dijkstra with adaptive algorithm based on Wei Peng et.al (2012) is used. Based on illustrative example with several cases, we found a resource sharing scenario can optimize the matching between driver and rider and moreover can solve the surge pricing problem which is deemed as less transparant to customer
Inter-urban roads in Indonesia are characterized mainly by distinct road geometry and heterogeneous traffic features. The accident database from the Republic of Indonesia National Traffic Police recorded a substantial number of fatal accidents and fatalities along inter-urban roads. This study aimed to analyze the effects of traffic heterogeneity and road geometry features on fatal accidents along inter-urban roads in South Sulawesi, Indonesia. Segment-based accident analysis was adopted to minimize bias due to the large standard deviations of road lengths. Vehicle-specific speeds, speed standard deviations, and volumes of six vehicle categories, road surface condition, and road geometry were the classified predicting factors. A machine learning technique was adopted to produce predictions of the classification problem. A total of 1,068 road segment observations from 2013-2016 were used to build and validate the model. Model generalization was carried out using the out-of-sample 2019 data. With 26 potential predictors, three machine learning techniques based on the ensembles of regression trees were used to avoid removing potential predictors altogether. The results indicate that road-related features show the greatest importance in predicting the number of fatal accidents. Among the speed features, the average speed of angkots and speed standard deviation of motorcycles showed the greatest importance. The average daily traffic (ADT) of pickups had the greatest importance among other vehicle-specific ADTs.
Jakarta Outer Ring Road (JORR) is a toll road system that circles the outskirts of Jakarta, where the purpose of this road is to reduce congestion on the streets in Jakarta city centre. However, the high composition of trucks in JORR resulted in congestion of the road, which is hypothesized as attributed by the gradient of this road. This study aims to evaluate the impact of road gradient on truck and the overall traffic performance. Using data obtained from 24-hour traffic recording on selected JORR section, a VISSIM model was constructed to simulate traffic performance on some combinations of traffic and gradient conditions. In terms of macroscopic view point of traffic stream, the simulations showed that road gradient alone insignificantly affected truck speed, as well as the overall traffic speed. Instead, truck composition had more effect on the traffic speed rather than the gradient. In a particular composition of trucks different gradients did not significantly affect traffic speed differently. This implies that any policy to restrict truck access to toll road should depend mainly on the composition of truck itself, not the gradient of the road.
This study concerns to the determination of location of freight distribution warehouses. It is part of a series of research projects on a distribution system we developed to deal with cases in a public service obligation state-owned company (PSO-SOC). This current research is characterized by the consideration of background traffic of the entire time period of planning rather than one certain time target on location model. It is aimed that the location decision to be more applicable and accommodative to the dynamic of the traffic condition. Once the decision is implemented, it will give the best outcome for the entire time period, not only for the initial time, end time or certain time of time period. A heuristic approach is proposed to simplify complexity of the model and network representation technique is applied to solve the model. A hyphotetical example is discussed to illustrate the mechanism of finding the optimal solution in term of both its objective function and applicability
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.