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Megacity Mobility: Integrated Urban Transportation Development and Management [Kietas viršelis]

(Illinois Institute of Technology, Chicago, USA), (Reason Foundation, USA), (Florida State University, USA)
  • Formatas: Hardback, 230 pages, aukštis x plotis: 254x178 mm, weight: 630 g, 22 Tables, black and white; 34 Line drawings, black and white; 36 Halftones, black and white; 70 Illustrations, black and white
  • Išleidimo metai: 15-Dec-2021
  • Leidėjas: CRC Press
  • ISBN-10: 0367363585
  • ISBN-13: 9780367363581
Kitos knygos pagal šią temą:
Megacity Mobility: Integrated Urban Transportation Development and ManagementDidesnis paveikslėlis
  • Formatas: Hardback, 230 pages, aukštis x plotis: 254x178 mm, weight: 630 g, 22 Tables, black and white; 34 Line drawings, black and white; 36 Halftones, black and white; 70 Illustrations, black and white
  • Išleidimo metai: 15-Dec-2021
  • Leidėjas: CRC Press
  • ISBN-10: 0367363585
  • ISBN-13: 9780367363581
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9780367363581.html
Raktažodžiai:
World population growth and economic prosperity have given rise to ever-increasing demands on cities, transportation planning, and goods movement. This growth, coupled with a slower pace of transportation capacity expansion and deteriorated facility restoration, has led to rapid changes in the transportation planning and policy environment. These stresses are particularly acute for megacities where degradation of mobility and facility performance have reached alarming rates. Addressing these transportation challenges requires innovative solutions.

Megacity Mobility grapples with these challenges by addressing transportation policy, planning, and facilities in a multimodal context. It discusses innovative short- and long-term solutions for meeting current and future mobility needs for the worlds most dynamic cities by addressing the influence of urban land use on mobility, 3D spiderweb transportation planning, travel demand management, multimodal transportation with flexible capacity, efficient capacity utilization driven by new technologies, innovative transportation funding and financing, and performance-based budget allocation using asset management principles. It discusses emerging issues, highlights potential challenges affecting proposed solutions, and provides policymakers, planners, and transportation professionals a road map to achieving sustainable mobility in the 21st century.

Zongzhi Li is a professor and the director of the Sustainable Transportation and Infrastructure Research (STAIR) Center at Illinois Institute of Technology (IIT).

Adrian T. Moore is vice president of policy at Reason Foundation in Washington, D.C., with focuses on privatization, transportation and urban growth, and more.

Samuel R. Staley is the director of the DeVoe L. Moore Center in the College of Social Sciences and Public Policy at Florida State University.
Foreword xv
Acknowledgments xvii
List of abbreviations
xix
Authors xxiii
1 Introduction
1(16)
2.1 Urban mobility in a post-COVID pandemic world
1(6)
1.1.1 Definition of mobility
2(1)
1.1.2 People versus freight
2(1)
1.1.3 Economics of mobility
3(2)
1.1.4 Hidden costs of mobility degradation
5(2)
1.2 Challenges of megacity mobility
7(5)
1.2.1 Ever-increasing travel demand
8(2)
1.2.2 Shifting travel patterns
10(1)
1.2.3 The case of China's megacities
10(2)
1.3 Framing the next wave of transportation solutions
12(3)
References
15(2)
2 New perspectives of urban transportation decision-making
17(20)
2.1 Framing the megacity mobility challenge
17(4)
2.2 The need for complex and sophisticated transportation systems
21(1)
2.3 Setting a new standard for megacity mobility
21(1)
2.4 Is the hub-and-spoke transportation network design obsolete?
22(5)
2.5 Building resilience using 3D transportation planning
27(5)
2.6 Fundamental elements of megacity mobility
32(2)
References
34(3)
3 Travel demand management
37(16)
3.1 Influence of land use on mobility
38(1)
3.2 Physical travel management
39(1)
3.3 Destination location and arrival time management
40(1)
3.4 Travel mode management
41(1)
3.5 Demand leveling management
42(1)
3.6 Departure time and travel route management
42(1)
3.7 Travel lane management
43(1)
3.8 Cases in action
43(6)
3.8.1 Bay Area travel demand leveling program, California
43(1)
3.8.2 Sustainable urban mobility in Stockholm, Sweden
43(2)
3.8.3 Smarter travel choices from better travel information in Reading, Berkshire, UK
45(1)
3.8.4 Urban transportation development and management in Singapore
46(3)
References
49(4)
4 Building out 3D highway transportation with flexible capacity
53(36)
4.1 General
53(2)
4.1.1 3D spiderweb transportation networks
54(1)
4.1.2 Multimodal integration
54(1)
4.2 Conventional options of highway capacity expansion
55(2)
4.2.1 Adding new travel lanes or building new roads
55(1)
4.2.2 Roadway widening
55(1)
4.2.3 Grade separation improvements
56(1)
4.2.4 Case in action: U.S. Interstate 2.0
56(1)
4.3 Elevated freeways
57(1)
4.3.1 Elevated crosstown expressways
57(1)
4.3.2 Case in action: Tampa Bay crosstown expressway
57(1)
4.4 Transportation tunnels
58(10)
4.4.1 Importance of tunnels
58(2)
4.4.2 Feasibility of tunneling
60(1)
4.4.2.1 Physical feasibility
60(1)
4.4.2.2 Environmental impacts
60(1)
4.4.2.3 Financial feasibility
61(3)
4.4.3 Cases in action
64(1)
4.4.3.1 Paris A86 West tunnels
64(1)
4.4.3.2 Sydney M5 East Freeway tunnels
64(1)
4.4.3.3 Istanbul Bosporus multimodal crossings
64(1)
4.4.3.4 Shanghai Yangtze River Tunnel-Bridge crossing
65(3)
4.4.3.5 Chongqing Jiefangbei underground circle
68(1)
4.5 Redesigning at-grade intersections
68(6)
4.5.1 Unconventional at-grade intersection designs
68(1)
4.5.1.1 Doublewide intersections
68(1)
4.5.1.2 Continuous flow intersections
69(1)
4.5.1.3 Median U-turn intersections
69(1)
4.5.1.4 Super street intersections
69(1)
4.5.2 Unconventional overpass, queue jumper, and interchange designs
70(1)
4.5.2.1 Center-turn overpasses
70(1)
4.5.2.2 Queue jumpers
70(1)
4.5.2.3 Tight diamond interchanges
70(1)
4.5.2.4 Single point interchanges
70(1)
4.5.2.5 Echelon interchanges
70(2)
4.5.2.6 Median U-turn diamond interchanges
72(1)
4.5.3 Cases in action
72(1)
4.5.3.1 Young Circle in Hollywood, Florida
72(1)
4.5.3.2 Lujiazui pedestrian circle/vehicular roundabout in Shanghai, China
72(2)
4.6 Complete streets
74(1)
4.6.1 Basic elements
74(1)
4.6.2 Case in action: complete streets in Saint Paul, Minnesota
75(1)
4.7 Optimal control of signalized intersections
75(2)
4.7.1 General
75(2)
4.7.2 SCOOT adaptive traffic signal control system
77(1)
4.8 New truck route capacity
77(2)
4.8.1 Truckways
78(1)
4.8.2 Case in action: tolled truckways in Georgia
78(1)
4.9 Connected and automated/autonomous vehicles
79(4)
4.9.1 Connected vehicles
79(1)
4.9.2 Automated/autonomous vehicles
80(2)
4.9.3 Cases in action
82(1)
4.9.3.1 Self-driving cars by Waymo in California
82(1)
4.9.3.2 Autopilot/full self-driving by Tesla in California
82(1)
4.10 Conclusion
83(1)
References
83(6)
5 Building out transit and multimodal transportation
89(30)
5.1 Transit capacity provision
90(9)
5.1.1 Transit performance benchmarks
90(1)
5.1.2 Transit network planning and design
90(2)
5.1.3 Transit vehicles
92(1)
5.1.3.1 Bus transit
92(1)
5.1.3.2 Bus rapid transit
92(1)
5.1.3.3 Fixed guideway transit
93(1)
5.1.4 Transit signal priority
93(1)
5.1.4.1 Bus signal priority
93(2)
5.1.4.2 Bus signal priority in SCOOT
95(1)
5.1.5 Cases in action
96(1)
5.1.5.1 Downtown Seattle Transit Tunnel
96(1)
5.1.5.2 Los Angeles Metro Busway system
96(1)
5.1.5.3 Lagos BRT-Lite in Lagos, Nigeria
97(2)
5.1.5.4 Transit priority system in Los Angeles
99(1)
5.2 Ridesharing modes
99(3)
5.2.1 General
99(2)
5.2.2 Case in action: BART integrated carpool to transit access program
101(1)
5.2.3 Case in action: Seattle on demand microtransit
102(1)
5.3 Active transportation and micromobility modes
102(5)
5.3.1 Pedestrian walking facilities
105(1)
5.3.2 Bike facilities
106(1)
5.3.3 Scooter facilities
106(1)
5.4 Multimodal integrated passenger travel
107(2)
5.4.1 General
107(1)
5.4.2 Case in action: multimodal passenger travel in Hong Kong, China
108(1)
5.5 Multimodal freight transportation
109(1)
5.5.1 Freight rails
109(1)
5.5.2 Cargo drones
109(1)
5.5.3 Cases in action
109(1)
5.5.3.1 The CREATE program in Chicago
109(1)
5.5.3.2 Rhaegal heavy-lifting drones
110(1)
5.5.3.3 Amazon's Prime Air
110(1)
5.6 Urban curb spaces as multimodal passenger/freight shared use mobility terminals
110(3)
5.7 Conclusion
113(1)
References
114(5)
6 Mobility management for efficient capacity utilization
119(22)
6.1 General
119(1)
6.1.1 Multiple, distinct goals in transportation system management
119(1)
6.1.2 The need for performance-based management
120(1)
6.2 Mobility-centered, performance-based transportation system management
120(1)
6.2.1 General
121(1)
6.2.2 Mobility performance measures
121(1)
6.3 Measures and strategies for mobility management
121(3)
6.3.1 Managing multimodal travel demand
123(1)
6.3.2 Multimodal integrated, expanded, and flexible transportation capacity
124(1)
6.3.3 Efficient capacity utilization
124(1)
6.4 From reactive to proactive mobility management
124(1)
6.5 Mobility management system
125(8)
6.5.1 Mobility management bundles and user services
126(1)
6.5.1.1 Travel demand and traffic management
126(2)
6.5.1.2 Travel and traffic information dissemination
128(1)
6.5.1.3 Advanced vehicle technologies
128(1)
6.5.1.4 Transit mobility management
128(1)
6.5.1.5 Commercial vehicle mobility management
129(1)
6.5.1.6 Incident and emergency management for more resilient mobility
129(1)
6.5.1.7 Electronic payment
130(1)
6.5.2 Mobility management system architecture
130(1)
6.5.2.1 Logical architecture
130(1)
6.5.2.2 Physical architecture
131(1)
6.5.2.3 Communications
131(1)
6.5.3 Mobility management technologies
132(1)
6.6 Cases in action
133(5)
6.6.1 I-94 corridor ITS deployments in Minnesota
133(1)
6.6.2 I-90 Smart road in Schaumburg, Illinois
133(2)
6.6.3 Spotlight ITS developments in Mainland China
135(1)
6.6.4 Intelligent traffic management system in Hong Kong, China
136(2)
References
138(3)
7 Innovative transportation funding and financing
141(38)
7.1 Historical revenue sources
141(5)
7.1.1 Fuel taxes
141(1)
7.1.2 Tolls or fares
142(1)
7.1.3 Weight-distance fees
143(1)
7.1.4 Value capture charges
144(1)
7.1.5 General revenue
145(1)
7.1.6 Parking fees
146(1)
7.1.7 Externality fees
146(1)
7.2 Transportation funding is fraught with tradeoffs
146(2)
7.2.1 General
146(1)
7.2.2 User fees
147(1)
7.3 Principles of sound transportation funding
148(1)
7.4 Price-based revenue generation
149(7)
7.4.1 Pricing to pay for highway infrastructure
150(3)
7.4.2 Pricing for specific facilities
153(1)
7.4.3 Pricing for externalities
153(2)
7.4.3.1 User charges for other externalities
155(1)
7.4.4 Pricing controversies and challenges
155(1)
7.5 Transportation financing
156(12)
7.5.1 Public financing of mobility
157(1)
7.5.1.1 Debt
157(1)
7.5.1.2 Infrastructure banks
157(1)
7.5.1.3 Asset recycling
157(2)
7.5.2 Public-private partnerships
159(2)
7.5.2.1 Strengths of PPPs
161(3)
7.5.2.2 Risks and challenges of PPPs
164(2)
7.5.2.3 PPPs as a tool
166(2)
7.6 Cases in action
168(4)
7.6.1 PPP for urban highways in Santiago, Chile
168(1)
7.6.2 Land value capture to fund urban metro in Hong Kong, China
169(2)
7.6.3 Congestion charges in London
171(1)
References
172(7)
8 Performance-based, mobility-centered transportation budget allocation
179(32)
8.1 General
179(1)
8.2 Mobility-centered, performance-based budget allocation process
179(1)
8.3 Mobility management data needs and database management
180(7)
8.3.1 General requirements
180(1)
8.3.2 Field collected data
181(1)
8.3.3 Predictive traffic data
182(1)
8.3.4 Data sampling methods
182(1)
8.3.5 Data collection techniques
183(2)
8.3.6 Data collection frequency
185(1)
8.3.7 Data quality assurance
185(1)
8.3.8 Data integration and database management
186(1)
8.4 Mobility performance analysis and predictions
187(2)
8.4.1 O-D path travel time estimation
187(1)
8.4.2 Travel time index and travel time buffer index
188(1)
8.5 Mobility improvement needs assessment
189(4)
8.5.1 Mobility improvement needs assessment by travel mode
189(3)
8.5.2 Mobility improvement options
192(1)
8.6 Mobility improvement evaluation
193(3)
8.6.1 Mobility improvement benefits in monetary values
195(1)
8.6.2 Mobility improvement benefits in utility values
196(1)
8.7 Budget allocation for mobility-centered performance improvements
196(3)
8.7.1 Issues
196(1)
8.7.2 Budget allocation methods
197(1)
8.7.3 Tradeoff analysis methods
198(1)
8.7.4 Implementation of prioritized alternatives and feedback of effectiveness
199(1)
8.8 Cases in action
199(3)
8.8.1 Budget allocation practices in U.S. state transportation agencies
199(1)
8.8.2 Illinois tollways' investment decision-making in interdependent capital projects
200(2)
8.9 Issues and challenges
202(2)
8.9.1 Institutional issues
203(1)
8.9.1.1 Strategic challenges
203(1)
8.9.1.2 Data management challenges
203(1)
8.9.1.3 Analytical challenges
204(1)
8.9.2 Strategies for implementing mobility-centered, performance-based budget allocation
204(1)
References
204(7)
9 The path to sustainable megacity mobility
211(16)
9.1 Keys to building a mobility-sustained megacity in the 21st century
213(3)
9.1.1 3D spiderweb multimodal transportation network planning
213(1)
9.1.2 Engineering innovations for multimodal network capacity
214(1)
9.1.3 New technologies for demand management and efficient capacity utilization
215(1)
9.1.4 Innovative financing and asset management-based budget allocation
216(1)
9.2 Emerging issues and challenges
216(8)
9.2.1 Challenges to pricing-based funding
217(1)
9.2.1.1 Consideration of traffic dynamics
217(1)
9.2.1.2 Advanced vehicle technologies
218(1)
9.2.1.3 Integration of physical facility, vehicle, and user/nonuser components
218(1)
9.2.2 Institutional issues
219(1)
9.2.2.1 Performance-based agency reorganization
219(1)
9.2.2.2 Intra- and inter-agency coordination
220(2)
9.2.2.3 Agency workforce development
222(1)
9.2.2.4 Communication with stakeholders
223(1)
9.2.2.5 Acceptance of users and nonusers
224(1)
9.3 Toward the transformation of transportation development and management
224(1)
References
225(2)
Index 227
Dr. ZONGZHI LI received his BE from Changan University, China. He obtained his MSCE and PhD in transportation and infrastructure systems engineering, as well as MSIE in operations research from Purdue University, USA. He holds full professor rank with tenure and serves as director of the Sustainable Transportation and Infrastructure Research (STAIR) Center at Illinois Institute of Technology (IIT), USA. His research interests include multimodal transportation demand and system performance modeling, asset management, and network economics.

Dr. ADRIAN T. MOORE holds a Masters and PhD in economics from the University of California, Irvine; a Master's in history from California State University, USA. He is vice president of policy at Reason Foundation, Washington, D.C., USA. Prior to joining Reason, Dr. Moore served 10 years in the U.S. Army on active duty and reserves. He leads Reason's policy implementation efforts and conducts research on privatization, government and regulatory reform, air quality, transportation and urban growth, prisons, and utilities.

Dr. SAMUEL R. STALEY earned a BA in economics and public policy from Colby College, Maine; an MS in applied economics from Wright State University, Ohio; and a PhD in public administration from The Ohio State University, USA. Dr. Staley was Robert W. Galvin Fellow at Reason Foundation, Washington, D.C., and currently serves as director of the DeVoe L. Moore Center at Florida State University, USA, with research focuses on urban planning, social entrepreneurship, and urban economics.