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Assignment 1 January 14, 2021 Transportation Engineering II, Spring 2021 Assignment 1 Due date: Tuesday, February 2, 2021 Page | 1 1. Read the 2019 Urban Mobility Report and answer the following questions by generating figures and charts: (10 pts) a. b. c. d. e. Trend of U.S. Jobs from 1982 to 2017 Trend of Delay per Commuter from 1982 to 2017 Trend of Total Delay from 1982 to 2017 Trend of Fuel Wasted from 1982 to 2017 Trend of Total Cost from 1982 to 2017 2. On page 13-14, several ideas of alleviating traffic congestions are listed. From you point of view by observing the traffic pattern and traffic problems in Tampa, which one do you think will be the most effective for alleviating traffic congestion in Tampa. Note that before you make the choice, you need to read through the ideas and make sure you understand the content. (10 pts) a. b. c. d. e. f. Get as much as possible from what we have Provide choices Add capacity in critical corridors Diversify the development patterns Technology advances Realistic expectations 3. Problem 1 on Page 155 of the textbook. (20 pts) Special Note: Since all your work must be submitted electronically via CANVAS, I encourage you to produce your work electronically on computer. If you prefer handwriting, then you may need to scan your work and submit the electronic version. How to present your results: (1) if you do hand calculation on the Dijkstra's algorithm, I encourage you to program in Software (i.e. Matlab) since it is convenient and can help to test if you understand the problem clearly and can turn it into a mathematical model. Please attach the codes, the final results and other supportive graphs/screenshots in your solutions. (2) However, if you prefer hand writing, scanning and uploading your work, then my suggestion is that, in your results, provide an example of shortest path including at least 3 nodes (including the origin and destination nodes) and follow the example we have in the course slides, and show me how you do the calculation step by step (start at the origin, initialize all nodes (P, C), select a candidate node, update labels to neighbor nodes, and update permanent node set). Word description is needed for each step, and graphic illustration is highly Course Name: Transportation Engineering II (TTE 4005) Assignment 1 January 14, 2021 recommended to support your calculation. I will evaluate your step-by-step example demonstration and the final results for grading. In this problem, since you need to find the shortest path from node a to all other nodes, it may take tremendous effort to hand-write all shortest paths step by step. So an example demonstration of a 3node shortest path is needed, as explained above. 4. Problem 3 on Page 155 of the textbook. (20 pts) Hint: Note that this problem refers to Figure 3.70 (there is some confusion in the problem description), since all the nodes in Table 3.14 are letters, not numbers. “Link flow” means the total flow on each link between two adjacent nodes, such as a-b, b-c, b-f, h-j, etc. 5. Problem 7 on Page 158 of the textbook. (20 pts) 6. Drivers pay the highway toll in cash, or by credit card. On the average, toll booth attendant needs 12 s to collect the money from the driver. Average vehicles arrival rate equals 240(veh/h). Treat toll booth as M/M/1 queueing system and calculate: (20 pts) • the average number of vehicles in the queue; • the average waiting time a client spends in the queue; and • the average waiting time a client spends in the queueing system. • What will be the benefits of introducing the electronic pay system that will need 3 s per driver to pay the toll? Course Name: Transportation Engineering II (TTE 4005) Page | 2 URBAN MOBILITY REPORT 2019 POWERED BY 2019 URBAN MOBILITY REPORT Published by The Texas A&M Transportation Institute with cooperation from INRIX David Schrank Senior Research Scientist Bill Eisele Senior Research Engineer Tim Lomax Research Fellow Texas A&M Transportation Institute The Texas A&M University System mobility.tamu.edu Sponsored by Texas Department of Transportation August 2019 DISCLAIMER The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. Sponsorship The authors would like to thank the Texas Department of Transportation for sponsorship of the 2019 Urban Mobility Report. The ‘2019 Urban Mobility Report’ highlights the reality of how motorists in the largest urban areas across the U.S. are experiencing the negative effects of congestion levels in their daily lives. In 2017, the average commuter wasted nearly 7 full working days in extra traffic delay, which translated to over $1,000 in personal costs. These are real impacts to people and businesses in our cities, and the problem does not appear to be letting up, especially for fast‐ growing areas. This is why Texas launched its Texas Clear Lanes initiative to address the top chokepoints in the state’s largest metro areas. Over the past 10 years, the total cost of delay in our nation’s top urban areas has grown by nearly 48%. The value of investing in our nation’s transportation infrastructure in a strategic and effective manner cannot be overstated as these added costs impact our national productivity, quality of life, economic efficiency and global competitiveness. – Marc Williams, Texas Department of Transportation Acknowledgements Shawn Turner, David Ellis and Phil Lasley — Concept and Methodology Development Phil Lasley, L.D. White — Website Tableau Visualization Michelle Young — Report Preparation Lauren Geng, Don Kang, Jack Kong, Yi Meng, Rex Peng, and Simon Fang — GIS Assistance Matthew Richards — Data Analysis Tobey Lindsey — Web Page Creation and Maintenance Richard Cole, Bernie Fette, Michelle Canton and Rick Davenport — Media Relations John Henry — Cover Artwork Dolores Hott and Nancy Pippin — Printing and Distribution Jim Williams, Rick Schuman and Ted Trepanier of INRIX — Data Technical Support 2019 Urban Mobility Report ii Table of Contents Page 2019 Urban Mobility Report ......................................................................................................................... 1 Better Congestion Data and Improved Analysis ........................................................................................... 3 One Page of Congestion Problems ............................................................................................................... 5 More Detail About Congestion Problems ..................................................................................................... 6 The Trouble With Planning Your Trip .......................................................................................................... 11 The Future of Congestion ........................................................................................................................... 12 Congestion Relief – An Overview of the Strategies .................................................................................... 13 Using the Best Congestion Data & Analysis Methodologies ...................................................................... 15 Where Should the Congestion Solutions Be Implemented?....................................................................... 16 Delivering the Goods: And Your Role in the Congestion Impacts on Trucking .......................................... 17 Concluding Thoughts .................................................................................................................................. 19 References .................................................................................................................................................. 21 Appendix A 2019 UMR Methodology (https://mobility.tamu.edu/umr/report/#methodology) Appendix B 2019 UMR Vehicle Occupancy (https://mobility.tamu.edu/umr/report/#appx‐b) Appendix C 2019 UMR Value of Time (https://mobility.tamu.edu/umr/report/#appx‐c) List of Exhibits Page Exhibit 1. Major Findings of the 2019 Urban Mobility Report (494 U.S. Urban Areas) ............................... 1 Exhibit 2. National Congestion Measures, 1982 to 2017 ............................................................................. 2 Exhibit 3. Percent of Delay Based on Measured Speeds ............................................................................. 3 Exhibit 4. Congestion Growth Trend – Hours of Delay per Auto Commuter ............................................... 6 Exhibit 5. Percent of Delay for Each Day ...................................................................................................... 7 Exhibit 6. Percent of Delay for Hours of Day................................................................................................ 7 Exhibit 7. Percent of Delay ‐ Road Type and Time of Day ............................................................................ 8 Exhibit 8. Peak Period Congestion in 2017 .................................................................................................. 8 Exhibit 9. 2017 Congestion Cost for Urban Passenger and Freight Vehicles ............................................... 9 Exhibit 10. How Much Extra Time Must You Allow to Be ‘On‐Time’? ........................................................ 11 Exhibit 11. Percent of Delay Based on Measured ....................................................................................... 15 List of Tables Table 1. Table 2. Table 3. Table 4. Page What Congestion Means to You, 2017 ......................................................................................... 22 What Congestion Means to Your Town, 2017 ............................................................................. 26 How Reliable is Freeway Travel in Your Town, 2017.................................................................... 30 Key Congestion Measures for 393 Urban Areas, 2017................................................................. 34 2019 Urban Mobility Report iii 2019 Urban Mobility Report 2019 Urban Mobility Report Congestion is back to its growth pattern. The 8‐ to 10‐year growing economy has brought traffic congestion to the highest measured levels in most U.S. cities. The myriad possible solutions –more highways, streets and public transportation; better traffic operations; more travel options; new land development styles; advanced technology – have not been deployed in sufficient numbers to restrain the mobility degradation. For more information and congestion data on your city, see: https://mobility.tamu.edu/umr/. The trends from 1982 to 2017 (see Exhibit 1) show that congestion is a persistently growing problem. • The problem is larger than ever. In 2017, congestion caused urban Americans to travel an extra 8.8 billion hours and purchase an extra 3.3 billion gallons of fuel for a congestion cost of $179 billion. • Trucks account for $20 billion (11 percent) of the cost, a bigger share than their 7 percent of traffic. • The average auto commuter spends 54 hours in congestion and wastes 21 gallons of fuel due to congestion at a cost of $1,080 in wasted time and fuel. • The variation in congestion is often more difficult for commuters and freight shippers to accommodate than the regular, predictable back‐ups. To reliably arrive on time for important freeway trips, travelers had to allow 34 minutes to make a trip that takes 20 minutes in light traffic. • Employment was up by 1.9 million jobs from 2016 to 2017, slower growth than the 2.3+ million job growth in 4 of the previous 5 years, but substantial enough to cause congestion growth (1). Exhibit 2 shows the historical national congestion trend. • More detailed speed data on more roads and more hours of the day from INRIX (2) a leading private sector provider of travel time information for travelers and shippers, have caused congestion estimates in most urban areas to be higher than in previous Urban Mobility Reports. Each region should use the combination of strategies that match its goals and vision. There is no panacea. And the decade‐long recovery from economic recession has proven that the problem will not solve itself. Exhibit 1. Major Findings of the 2019 Urban Mobility Report (494 U.S. Urban Areas) (Note: See page 3 for description of changes since the 2015 report) Measures of… … Individual Congestion Yearly delay per auto commuter (hours) Travel Time Index Planning Time Index (Freeway only) “Wasted" fuel per auto commuter (gallons) Congestion cost per auto commuter (2017 $) … The Nation’s Congestion Problem Travel delay (billion hours) “Wasted” fuel (billion gallons) Truck congestion cost (billions of 2017 dollars) Congestion cost (billions of 2017 dollars) 1982 2000 2012 2017 5‐Yr Change 20 1.10 ‐‐ 5 $610 38 1.19 ‐‐ 16 $920 47 1.22 ‐‐ 20 $970 54 1.23 1.67 21 $1,080 15% 1 Point ‐‐ 5% 11% 1.8 0.8 $1.8 $15 5.3 2.5 $7.0 $75 7.7 3.2 $14.5 $150 8.8 3.3 $19.5 $179 14% 3% 35% 19% Yearly delay per auto commuter – The extra time spent during the year traveling at congested speeds rather than free‐ flow speeds by private vehicle drivers and passengers who typically travel in the peak periods. Travel Time Index (TTI) – The ratio of travel time in the peak period to travel time at free‐flow conditions. A Travel Time Index of 1.30 indicates a 20‐minute free‐flow trip takes 26 minutes in the peak period. Planning Time Index (PTI) – The ratio of travel time on the worst day of the month to travel time in free‐flow conditions. Wasted fuel – Extra fuel consumed during congested travel. Congestion cost – The yearly value of delay time and wasted fuel by all vehicles. Truck congestion cost ‐ The yearly value of extra operating time and wasted fuel for commercial trucks. 2019 Urban Mobility Report 1 Exhibit 2. National Congestion Measures, 1982 to 2017 Year 5‐Year Change U.S. Jobs (Millions) Delay Per Commuter (Hours) Total Delay (Billion Hours) Fuel Wasted (Billion Gallons) Total Cost (Billions of 2017 Dollars) 8% 15% 14% 3% 19% 54 8.8 3.3 $179 2017 153.3 53 8.6 3.3 $171 2016 151.4 51 8.4 3.3 $165 2015 148.8 50 8.2 3.2 $163 2014 146.3 48 8.0 3.2 $157 2013 143.9 47 7.7 3.2 $150 2012 142.5 45 7.5 3.2 $143 2011 139.9 44 7.2 3.1 $132 2010 139.1 43 6.9 3.1 $124 2009 139.9 42 6.8 3.2 $127 2008 145.4 43 6.8 3.2 $121 2007 146.1 42 6.7 3.1 $115 2006 144.4 42 6.6 3.0 $107 2005 141.7 41 6.3 2.9 $100 2004 139.2 41 6.1 2.8 $92 2003 137.7 40 5.9 2.7 $86 2002 136.5 39 5.6 2.6 $81 2001 136.9 38 5.3 2.5 $75 2000 136.9 37 5.1 2.3 $69 1999 133.5 36 4.8 2.2 $64 1998 131.5 36 4.6 2.1 $60 1997 129.6 34 4.3 2.0 $56 1996 126.7 33 4.1 1.9 $51 1995 124.9 32 3.8 1.8 $47 1994 123.1 31 3.6 1.7 $43 1993 120.3 30 3.4 1.6 $39 1992 118.5 29 3.2 1.5 $36 1991 117.7 28 3.0 1.4 $33 1990 118.8 27 2.9 1.3 $29 1989 117.3 26 2.7 1.2 $26 1988 115.0 25 2.5 1.1 $24 1987 112.4 24 2.4 1.1 $22 1986 109.6 23 2.2 1.0 $20 1985 107.2 22 2.1 0.9 $18 1984 105.0 21 1.9 0.9 $17 1983 100.8 20 1.8 0.8 $15 1982 99.5 Note: See Exhibit 1 for explanation of measures. For more congestion information see Tables 1 to 4. For congestion information on your city, see https://mobility.tamu.edu/umr/. 2019 Urban Mobility Report 2 Better Congestion Data and Improved Analysis The 2019 Urban Mobility Report is the 5th partnership between TTI and INRIX (2). The data behind the 2019 Report are hundreds of speed data points for every 15 minutes of the average day of the week for almost every mile of major road in urban America. For the congestion analyst, this means about a billion speeds on about 1.5 million miles of U.S. streets and highways – an awesome amount of information. For the policy analyst and transportation planner, this means congestion problems can be described in detail, and solutions can be targeted with much greater specificity and accuracy. Key aspects of the 2019 Urban Mobility Report are summarized below.  At least four years of congestion estimates are presented for each of the 494 U.S. urban areas. Improvements in the INRIX traffic speed data, and the data provided by the states to the Federal Highway Administration (3), means improved congestion measures in every urban area. Tables 1, 2, and 3 provide congestion estimates for the 101 urban areas that have been studied in many past reports; Table 4 displays 2017 congestion measures for the other 393 urban areas.  Previous reports had estimated many speeds, especially on minor roads and in non‐peak periods. The greatly expanded INRIX traffic speed dataset now means that more than 90 percent of the travel delay in the 2019 report is based on a measured traffic speed (Exhibit 3). The previous approach of using a conservative delay estimate means that the amount of urban travel delay increased substantially on some roads. The delay estimation methodology is described in Appendix A on the mobility study website (4).  An updated vehicle occupancy value is used to reflect travel changes (5). (Appendix B)  The value of congested travel time is measured by the median hourly wage for all job classifications in the Occupational Employment Statistics series by the Bureau of Labor Statistics (6). (Appendix C)  Commercial truck operating cost estimates are drawn from the American Transportation Research Institute’s annual survey of their membership (6). (Appendix C) More information on the performance measures and data can be found at: https://mobility.tamu.edu/umr/report/#methodology. For more information about INRIX, go to www.inrix.com. Exhibit 3. Percent of Delay Based on Measured Speeds 2019 Urban Mobility Report 3 One Page of Congestion Problems Rush‐hour traffic jams are expected in big cities. When a large percentage of workers are on an 8 a.m. to 5 p.m. or 9 a.m. to 5 p.m. schedule, there will be travel delays on freeways, streets, and even public transportation. This results in a “rush hour” in the morning and afternoon. The problem obviously affects commuters, but it also affects many other trip types: manufacturers that rely on a reliable transportation system and companies who have delivery schedules and service calls. Some key measures are listed below. See data for your city at https://mobility.tamu.edu/umr/congestion‐data/. Congestion costs are increasing. The “invoice” for only two of the congestion effects – the cost of extra time and fuel – in the 494 U.S. urban areas was (all values in constant 2017 dollars):  In 2017 – $179 billion  In 2016 – $171 billion  In 2000 – $75 billion  In 1982 – $15 billion Congestion wastes a massive amount of time and fuel and creates more uncertainty for travelers and freight. In 2017:  8.8 billion hours of extra travel time (in that time, 124 million couples could binge‐watch all eight seasons of Game of Thrones).  3.3 billion gallons of wasted fuel (equal to a line of 18‐wheel fuel trucks from Los Angeles to Boston).  And if all that isn’t bad enough, travelers and freight shippers making important trips had to add nearly 70 percent more travel time compared with light traffic conditions to account for the effects of unexpected crashes, bad weather, special events and other irregular congestion causes. Congestion is also a type of tax  $179 billion of delay and fuel cost (equal to the cost of about 175 million summer vacations)  The negative effect of uncertain or longer delivery times, missed meetings, business relocations and other congestion‐related effects are not included.  11 percent ($20 billion) of the delay cost was the effect of congestion on truck operations (equivalent to the average grocery bills of 2.5 million families); this does not include any value for the goods being transported in the trucks.  The ...
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