0LAUK0 2015 01 Design Report: Difference between revisions
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'''1.2.1''' | '''1.2.1''' | ||
When a bus skips a few bus stops, it will arrive sooner than expected at the next stops, which means that people might have to wait longer than usual for next bus if that one does not skip any. This will lead to potential longer waiting times. However, this also means that there are also potential shorter waiting times between busses, if the first bus does not skip any stops, but the second one does. | When a bus skips a few bus stops, it will arrive sooner than expected at the next stops, which means that people might have to wait longer than usual for next bus if that one does not skip any. This will lead to potential longer waiting times. However, this also means that there are also potential shorter waiting times between busses, if the first bus does not skip any stops, but the second one does. | ||
'''1.2.2''' | '''1.2.2''' | ||
When there are stops that can be skipped, more efficient bus routes can be used to reduce the travel time. This will not be possible during rush hours, because the bus stops will be too crowded, which means that there will barely be any stops the bus can skip. | When there are stops that can be skipped, more efficient bus routes can be used to reduce the travel time. This will not be possible during rush hours, because the bus stops will be too crowded, which means that there will barely be any stops the bus can skip. | ||
In the following picture shows a fragment of the bus route between Eindhoven and Veldhoven. | In the following picture shows a fragment of the bus route between Eindhoven and Veldhoven. | ||
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Happiness will be “quantified” in the simulation, and the decrease in travel time should be weighing more heavily than the potential increase in waiting time, and perhaps the troubles caused by the use of the app to sign up for bus rides. | Happiness will be “quantified” in the simulation, and the decrease in travel time should be weighing more heavily than the potential increase in waiting time, and perhaps the troubles caused by the use of the app to sign up for bus rides. | ||
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Autonomous Bus Scheduling System Design Report
Introduction
Background
Public transportation has been around for a couple of decades now. It started with the stagecoach in the nineteenth century. Later on came the steam trains which were capable of carry large capacity of people at the same time. The trains were too big to travel in city themselfs, so the tram was invented. However not city are capable of creating a tramrail network. So with the increasing demands of mobility in the sixties, busses started to be used for public transportation in cities around the Netherlands and the rest of europe.
Bus stops were created around cities and a static scheduling system was implemented. This static scheduling system uses a fixed time table around the city. The busses follow fixed routes each time and do not take into account if there are any people waiting at a bus stop or not. Meaning that the busses do not take a shorter route when nobody is willing to stop of is waiting a certain bus stop. This means it is time for a dynamic system, this will be the main focus in this report. The new scheduling system for busses aims to create a more efficient passenger flow. It will be able to send extra busses to bus stops that are or are getting too crowded and also the system will choose a shorter route to it’s destination when no passengers are waiting at the coming bus stops. Users can check in at the bus stop or with their mobile phone apps. The scheduling system will then optimize the routes by taking this information into account. A small part of the report will discusses the possibility of using autonomous busses in the new dynamic scheduling system, analyzing the impact of user, society and enterprise.
Different approaches can be used to optimize this schedule. Those will be analyzed and take feedback data from a survey. This data will be inputted in a simulation in order to analyze the consequence of the different needs of the users. Furthermore in this report the infrastructure will be redesigned. The most important infrastructure alteration will be the placement of the bus depot. The simulation will also be used to validate the new dynamic scheduling system.
The validation will have with different requirement like waiting time and crowdiness but also with happiness. This is a design report for dynamic scheduling bus system, incorporating the needs of the User, Society and Enterprise.
Objectives
| Objective | Short description |
|---|---|
| 1.2.1 | A potential maximum waiting time of 20% longer than it currently is. |
| 1.2.2 | An average decrease in travel time of 20% (not including during rush hours) |
| 1.2.3 | An increase in happiness of the travelers |
1.2.1 When a bus skips a few bus stops, it will arrive sooner than expected at the next stops, which means that people might have to wait longer than usual for next bus if that one does not skip any. This will lead to potential longer waiting times. However, this also means that there are also potential shorter waiting times between busses, if the first bus does not skip any stops, but the second one does.
1.2.2
When there are stops that can be skipped, more efficient bus routes can be used to reduce the travel time. This will not be possible during rush hours, because the bus stops will be too crowded, which means that there will barely be any stops the bus can skip.
In the following picture shows a fragment of the bus route between Eindhoven and Veldhoven.
1.2.3
Happiness will be “quantified” in the simulation, and the decrease in travel time should be weighing more heavily than the potential increase in waiting time, and perhaps the troubles caused by the use of the app to sign up for bus rides.
Requirements
Proposed Plan of Action
Objectives
Past/Current attempts
Social impact/ethics
Infrastructure
Simulation
Conclusion
Discussion
References
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9.Han, A. F and Wilson, N. M. H (1982). The Allocation of Buses in Heavily Utilized Networks With Overlapping Routes, Transportation Research B, Vol. 16, No.3, pp 221 -232.
10.Baaj, M. H. (1990). The Transit Network Design Problem: An AI-Based Approach, Ph.D. thesis, Department of Civil Engineering, University of Texas, Austin, Texas.
11.Shih, M. and Mahmassani, H. S. (1994). A Design Methodology for Bus Transit Networks with Coordinated Operations, Research Report 60016-1,Center for Transportation Research, University of Texas at Austin, Austin, Texas.
12.Dashora, M. (1994). Development of an Expert System for Routing and Scheduling of Urban Bus Services, Ph.D. thesis, Department of Civil Engineering, lIT Bombay, INDIA.
13.“A survey of public opinion about autonomous and self-driving vehicles in the U.S., the U.K. and Australia”, Brandon Schoettle and Michael Sivak, July 2014
14.“Ethical Decision Making During Automated Vehicle Crashes” in Transportation Research Record: Journal of the Transportation Research Board, Noah J. Noah.
15. U.S. Census Bureau. Vehicles Involved in Crashes by Vehicle Type, Rollover Occurrence, and Crash Severity: 2009. Statistical Abstract of the United States. Publication Table 1107. U.S. Department of Commerce, 2012.
16. Office of Freight Management and Operations. Freight Facts and Figures 2011. Publication FHWA-HOP-12-002. FHWA, U.S. Department of Transportation, 2011.
17. NHTSA. Traffic Safety Facts 2009: A Compilation of Motor Vehicle Crash Data from the Fatality Analysis Reporting System and the General Estimates System. Publication DOT HS 811 402. U.S. Department of Transportation, 2009.