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Potential travel cost saving in urban public-transport networks using smartphone guidance
- Source :
- PLoS ONE, Vol 13, Iss 5, p e0197181 (2018), PLoS ONE
- Publication Year :
- 2018
- Publisher :
- Public Library of Science (PLoS), 2018.
-
Abstract
- Public transport (PT) is a key element in most major cities around the world. With the development of smartphones, available journey planning information is becoming an integral part of the PT system. Each traveler has specific preferences when undertaking a trip, and these preferences can also be reflected on the smartphone. This paper considers transit assignment in urban public-transport networks in which the passengers receive smartphone-based information containing elements that might influence the travel decisions in relation to line loads, as well as passenger benefits, and the paper discusses the transition from the current widespread choosing approach to a personalized decision-making approach based on smartphone information. The approach associated with smartphone guidance that considers passengers’ preference on travel time, waiting time and transfer is proposed in the process of obtaining his/her preferred route from the potential travel routes generated by the Deep First Search (DFS) method. Two other approaches, based on the scenarios reflecting reality, include passengers with access to no real time information, and passengers that only have access to the arrival time at the platform are used as comparisons. For illustration, the same network proposed by Spiess and Florian is utilized on the experiments in an agent-based model. Two experiments are conducted respectively according to whether each passenger’s choosing method is consistent. As expected, the results in the first experiment showed that the travel for consistent passengers with smartphone guidance was clearly shorter and that it can reduce travel time exceeding 15% and weighted cost exceeding 20%, and the average saved time approximated 3.88 minutes per passenger. The second experiment presented that travel cost, as well as cost savings, gradually decreased by employing smartphone guidance, and the maximum cost savings accounted for 14.2% of the total weighted cost.
- Subjects :
- Computer science
0211 other engineering and technologies
Social Sciences
lcsh:Medicine
Transportation
02 engineering and technology
Systems Science
Cognition
Agent-Based Modeling
Sociology
Transfer (computing)
Psychology
lcsh:Science
Geographic Areas
021103 operations research
Multidisciplinary
Geography
Simulation and Modeling
05 social sciences
Process (computing)
Mobile Applications
Transport economics
Public transport
Physical Sciences
Costs and Cost Analysis
Engineering and Technology
Smartphone
Research Article
Urban Areas
Computer and Information Sciences
Relation (database)
Decision Making
Equipment
Research and Analysis Methods
Transport engineering
0502 economics and business
Humans
Communication Equipment
050210 logistics & transportation
business.industry
lcsh:R
Cognitive Psychology
Biology and Life Sciences
Communications
Earth Sciences
Key (cryptography)
Cognitive Science
lcsh:Q
Cell Phones
business
Mathematics
Neuroscience
Dwell Time
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 13
- Issue :
- 5
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....d8ed1dc91ca8fc2fd5ef3a110c89c66a