Near-Optimal Fixed-Route Scheduling for Crowdsourced Transit System

Author(s):  
Hanlin Li ◽  
Xiaowei Wu ◽  
Leong Hou U ◽  
Kun Pang Kou
2016 ◽  
Vol 6 (3) ◽  
pp. 123-134 ◽  
Author(s):  
Yohen Cuéllar ◽  
Rodrigo Buitrago Tello ◽  
Luis Carlos Belalcazar Ceronn

2013 ◽  
Vol 12 (3) ◽  
Author(s):  
Djoko Prijo Utomo

In consequence of the increasing of regional economic activities in Pulau Batam, a reliable transportation system is required. Decreasing road network performance as a result of increasing traffic volume needs a strategic planning to anticipate the worsening condition in the future. One of the solutions is by providing mass transit system which is expected to attract private car users. Therefore, determination of potential corridor of mass transit system need to be identified so that the system provide better accessibility. Trip pattern in Pulau Batam must be known by developing trip distribution model. The trip distribution model is calibrated using origin-destination (O-D) data that is based on home interview survey. The validated model will be used to forecast and simulate travel demand onto transport network. Result of model calibration process shows mean trip length difference between model and survey is equal 0.141 %. From simulation of trip assignment is obtained that potential corridor for mass transit system using LRT is Batu Ampar – Batu Aji via Muka Kuning. Passenger forecast in the year 2030 is 193,990 passenger/day (2 directions).


Author(s):  
Tony Kerr ◽  
Martin Lowson ◽  
Austin Smith

2021 ◽  
Vol 10 (5) ◽  
pp. 321
Author(s):  
Alessandro Emilio Capodici ◽  
Gabriele D’Orso ◽  
Marco Migliore

Background: In a world where every municipality is pursuing the goals of more sustainable mobility, bicycles play a fundamental role in getting rid of private cars and travelling by an eco-friendly mode of transport. Additionally, private and shared bikes can be used as a feeder transit system, solving the problem of the first- and last-mile trips. Thanks to GIS (Geographic Information System) software, it is possible to evaluate the effectiveness of such a sustainable means of transport in future users’ modal choice. Methods: Running an accessibility analysis of cycling and rail transport services, the potential mobility demand attracted by these services and the possible multimodality between bicycle and rail transport systems can be assessed. Moreover, thanks to a modal choice model calibrated for high school students, it could be verified if students will be really motivated to adopt this solution for their home-to-school trips. Results: The GIS-based analysis showed that almost half of the active population in the study area might potentially abandon the use of their private car in favour of a bike and its combination with public transport systems; furthermore, the percentage of the students of one high school of Palermo, the Einstein High School, sharply increases from 1.5% up to 10.1%, thanks also to the combination with the rail transport service. Conclusions: The GIS-based methodology shows that multimodal transport can be an effective way to pursue a more sustainable mobility in cities and efficiently connect suburbs with low-frequent public transport services to the main public transport nodes.


2020 ◽  
Vol 13 (1) ◽  
pp. 158
Author(s):  
Sishen Wang ◽  
Hao Wang ◽  
Pengyu Xie ◽  
Xiaodan Chen

Low-carbon transport system is desired for sustainable cities. The study aims to compare carbon footprint of two transportation modes in campus transit, bus and bike-share systems, using life-cycle assessment (LCA). A case study was conducted for the four-campus (College Ave, Cook/Douglass, Busch, Livingston) transit system at Rutgers University (New Brunswick, NJ). The life-cycle of two systems were disaggregated into four stages, namely, raw material acquisition and manufacture, transportation, operation and maintenance, and end-of-life. Three uncertain factors—fossil fuel type, number of bikes provided, and bus ridership—were set as variables for sensitivity analysis. Normalization method was used in two impact categories to analyze and compare environmental impacts. The results show that the majority of CO2 emission and energy consumption comes from the raw material stage (extraction and upstream production) of the bike-share system and the operation stage of the campus bus system. The CO2 emission and energy consumption of the current campus bus system are 46 and 13 times of that of the proposed bike-share system, respectively. Three uncertain factors can influence the results: (1) biodiesel can significantly reduce CO2 emission and energy consumption of the current campus bus system; (2) the increased number of bikes increases CO2 emission of the bike-share system; (3) the increase of bus ridership may result in similar impact between two systems. Finally, an alternative hybrid transit system is proposed that uses campus buses to connect four campuses and creates a bike-share system to satisfy travel demands within each campus. The hybrid system reaches the most environmentally friendly state when 70% passenger-miles provided by campus bus and 30% by bike-share system. Further research is needed to consider the uncertainty of biking behavior and travel choice in LCA. Applicable recommendations include increasing ridership of campus buses and building a bike-share in campus to support the current campus bus system. Other strategies such as increasing parking fees and improving biking environment can also be implemented to reduce automobile usage and encourage biking behavior.


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