scholarly journals Solving Traffic Congestion through Street Renaissance: A Perspective from Dense Asian Cities

Urban Science ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 18 ◽  
Author(s):  
Liang Wen ◽  
Jeff Kenworthy ◽  
Xiumei Guo ◽  
Dora Marinova
Keyword(s):  
Land Use Planning ◽  
Traffic Congestion ◽  
Travel Demand ◽  
Supply And Demand ◽  
Demand Management ◽  
Holistic Approach ◽  
Residential Areas ◽  
Travel Demand Management ◽  
Traffic Demand ◽  
Work Related

Traffic congestion is one of the most vexing city problems and involves numerous factors which cannot be addressed without a holistic approach. Congestion cannot be narrowly tackled at the cost of a city’s quality of life. Focusing on transport and land use planning, this paper examines transport policies and practices on both the supply and demand sides and finds that indirect travel demand management might be the most desirable solution to this chronic traffic ailment. The concept of absorption of traffic demand through the renaissance of streets as a way for traffic relief is introduced from two perspectives, with some examples from dense Asian urban contexts to demonstrate this. Firstly, jobs–housing balance suggests the return of production activities to residential areas and sufficient provision of diverse space/housing options to deal with work-related traffic. The second approach is to promote the street as a multi-activity destination rather than a thoroughfare to access dispersed daily needs, and to advocate more street life to diminish non-commuting traffic. Based on this, suggestions for better transport planning policies are put forward.

scholarly journals SOLVING TRAFFIC CONGESTION FROM THE DEMAND SIDE

2015 ◽  
Vol 27 (6) ◽  
pp. 529-538 ◽  
Author(s):  
Ying-En Ge ◽  
Olegas Prentkovskis ◽  
Chunyan Tang ◽  
Wafaa Saleh ◽  
Michael G. H. Bell ◽  
...  
Keyword(s):  
Travel Behavior ◽  
Traffic Congestion ◽  
Travel Demand ◽  
State Of The Art ◽  
Demand Management ◽  
Relevant Literature ◽  
Short Review ◽  
Active Management ◽  
Demand Side ◽  
Travel Demand Management

It is nowadays widely accepted that solving traffic congestion from the demand side is more important and more feasible than offering more capacity or facilities for transportation. Following a brief overview of evolution of the concept of Travel Demand Management (TDM), there is a discussion on the TDM foundations that include demand-side strategies, traveler choice and application settings and the new dimensions that ATDM (Active forms of Transportation and Demand Management) bring to TDM, i.e. active management and integrative management. Subsequently, the authors provide a short review of the state-of-the-art TDM focusing on relevant literature published since 2000. Next, we highlight five TDM topics that are currently hot: traffic congestion pricing, public transit and bicycles, travel behavior, travel plans and methodology. The paper closes with some concluding remarks.

Path Reconstruction of Intelligent Traffic Based on Positive Feedback System

2014 ◽  
Vol 513-517 ◽  
pp. 3160-3164
Author(s):  
Xue Li Zhang
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Intelligent Systems ◽  
Supply And Demand ◽  
Demand Management ◽  
Reference Value ◽  
Feedback System ◽  
Urban Traffic ◽  
Urban Transport ◽  
Traffic Demand

Traffic congestion are prevalent in worldwide cities. The imbalance between demand and supply of urban traffic is the root cause of this problem. So taking effective measures to regulate traffic demand, and guiding the traffic problems of the supply and demand balance is the best way to solve traffic congestion. This paper improves the TDM measure, and combines with intelligent information platform for the design of a new urban transport demand management adaptability of dynamic traffic data analysis platform. The platform supported by the technology of wireless sensor communications, intelligent terminals, the Internet and cloud computing is facing with the dynamic needs of traffic flow and traffic congestion state to carry out the operations of spatiotemporal data mining, clustering, and track detection, and to apply it into the traffic hot spots, abnormal driving track, traffic congestion trends and traffic flow detection and analysis, which has a good reference value for the improvement of management and service level of traffic intelligent systems.

scholarly journals What Factors Affect Commuters’ Utility of Choosing Mobility as a Service? An Empirical Evidence from Seoul

2021 ◽  
Vol 13 (16) ◽  
pp. 9324
Author(s):  
Sujae Kim ◽  
Sangho Choo ◽  
Sungtaek Choi ◽  
Hyangsook Lee
Keyword(s):  
Traffic Congestion ◽  
Latent Class ◽  
Travel Demand ◽  
Public Transit ◽  
Latent Class Model ◽  
Influencing Factor ◽  
Demand Management ◽  
Related Factors ◽  
Travel Demand Management ◽  
Trip Frequency

Mobility as a Service (MaaS), which integrates public and shared transportation into a single service, is drawing attention as a travel demand management strategy aimed at reducing automobile dependency and encouraging public transit. In particular, there have been few studies that recognize traffic congestion during peak hours and identify related factors for practical application. The purpose of this study is to explore what factors affect Seoul commuters’ mode choice including MaaS. A web-based survey that 161 commuters participated in was conducted to collect information about personal, household, and travel attributes, together with their mode preference for MaaS. A latent class model was developed to classify unobserved latent groups based on trip frequency by means and to identify factors influencing mode-specific utilities (in particular, MaaS service) for each class. The result shows that latent classes are divided into two groups (public transit-oriented commuters and balanced mode commuters). Most variables have significant impacts on choice for MaaS. The coefficient of MaaS choice of Class 1 and Class 2 were different. These findings suggest there is a difference between the classes according to trip frequency by means as an influencing factor in MaaS choice.

scholarly journals Multimode Traffic Travel Behavior Characteristics Analysis and Congestion Governance Research

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Wen Li ◽  
Wei Feng ◽  
Hua-zhi Yuan
Keyword(s):  
Sustainable Development ◽  
Public Transportation ◽  
Travel Behavior ◽  
Traffic Congestion ◽  
Travel Demand ◽  
Demand Management ◽  
Congestion Management ◽  
Traffic Demand ◽  
Modern Cities ◽  
Behavior Characteristics

The rapid aggregation of modern urban population and the rapid growth of car travel lead to traffic congestion, environmental pollution, and other problems. In view of the limited land resources in our country, it is impractical to meet residents’ travel demand by blindly increasing traffic supply. Therefore, addressing the urban road congestion problem for sustainable development of modern cities, the paper makes research on residents’ travel behavior characteristics and travel preference under the condition of multimodal transportation to formulate reasonable traffic demand management strategy for the guide on public traffic demand, bus priority strategy, and congestion management. The operation characteristic of each transportation mode is analyzed by comparing its related traffic and economic characteristics. Multimode traffic choice behavior is discussed by establishing multiple logistic regression models to analyze the main influencing factors to travelers’ social and economic attributes, travel characteristics, and preference based on travel survey data of urban residents. The paper proposes the development of an urban public transportation system and travelling mode shift from cars to public transportation as reasonable travel structure for congestion management and sustainable development of modern cities.

Modeling the Effectiveness of Infrastructure and Travel Demand Management Measures to Improve Traffic Congestion during Typhoons

2018 ◽  
Vol 2672 (1) ◽  
pp. 43-53 ◽  
Author(s):  
Wisinee Wisetjindawat ◽  
Sybil Derrible ◽  
Amirhassan Kermanshah
Keyword(s):  
Failure Probability ◽  
Traffic Congestion ◽  
Travel Demand ◽  
Climate Model ◽  
Demand Management ◽  
Travel Time Reliability ◽  
Travel Demand Management ◽  
Management Measures ◽  
Departure Time ◽  
Tokai Region

Many commuters find themselves stranded during natural disasters like typhoons. In the Tokai region in Japan, many road sections become heavily congested during typhoons, with some commuters reporting homebound trips taking more than four times longer than usual because of road flooding at several locations. Although large typhoons are considered extreme events (in terms of magnitude), they occur frequently (i.e., several times per year), substantiating the need for better preparedness. Nonetheless, it is impossible to predict exactly which roads are going to be flooded during a typhoon. As a result, in this study, a stochastic modeling approach was used that assigns a failure probability to each road segment based on climate model outputs for the region. Using this stochastic model, the travel time reliability between any given origin–destination pair can be determined. By applying this model to the road network of the Tokai region, two major measures were identified that could be implemented to reduce severe congestion during a typhoon. First, targeted infrastructure management measures can be implemented to strengthen heavily used roads, thus reducing the failure probability of major roads. Second, travel demand management measures can be implemented, such as asking commuters to leave their workplace or school one or two hours after their normal departure time. Overall, it was found that strengthening heavily used roads has a bigger impact in relieving congestion than delaying departure time, but that combining both strategies achieves the best results.

scholarly journals Understanding the Effects of Improving Transportation on Pilgrim Travel Behavior: Evidence from the Lhasa, Tibet, China

2018 ◽  
Vol 10 (10) ◽  
pp. 3528 ◽  
Author(s):  
Gang Cheng ◽  
Shuzhi Zhao ◽  
Di Huang
Keyword(s):  
Choice Behavior ◽  
Travel Demand ◽  
Mode Choice ◽  
Demand Management ◽  
Sustainable Transportation ◽  
Travel Demand Management ◽  
Traffic Demand ◽  
The Public ◽  
Underdeveloped Areas ◽  
Transportation Improvements

Effective travel demand management measures provide the opportunity to fully utilize limited transportation resources, especially in underdeveloped areas. It is increasingly recognized that the improvement in existing transportation infrastructure and the optimization of traffic demand management method would result in a complicated urban transportation system with multiple travel modes. This paper aims to investigate the relationship between transportation improvements (e.g., pedestrian flow, free bus for the elderly, and parking space planning) and the mode choice behavior of pilgrimages in the Lhasa of Tibet, China. This study employed a distinctive survey conducted among pilgrims in Lhasa, including both individual questionnaires and interviews from 2010 to 2016. The analysis was undertaken using a multinomial logit model to identify the extent to which transportation improvements could affect the pilgrim’s travel mode choice behavior. The results show that transportation improvements, as an operational method in underdeveloped areas, play an important role in motivating the pilgrimage to travel that can increase the attractiveness of private car use, and make pedestrian traffic more prominent. However, improvements in the public transport need to be conducted to attract more travelers. These results confirm that increasing the attractiveness of low-carbon transportation (e.g., buses, walking, and cycling) to the public can reduce the usage on private vehicles and maintain the development of sustainable transportation in underdeveloped areas with limited transportation resources.

scholarly journals Urban Planning: a Game Theory Application for the Travel Demand Management

2017 ◽  
Author(s):  
Mark Koryagin
Keyword(s):  
Land Use ◽  
Public Transport ◽  
Traffic Congestion ◽  
Travel Demand ◽  
Choice Model ◽  
Demand Management ◽  
Search Time ◽  
Travel Demand Management ◽  
Public Transport System ◽  
Theory Application

Urban infrastructure in the developing nations is generating a great number of environmental problems. Therefore, the problem of land distribution among road networks, parking spaces and landscaped parks is to be researched. The passenger behavior depends on traffic congestion, parking search time, public transport frequency, parking fee, etc. The travel mode choice model is described by logit function.A city territory is subdivided into three districts, residential, central and industrial, each of them trying to develop and implement the optimal policy of land use. The district criterion includes residential travel times, congestion and impacts of the parks on the environment. Any district should solve the effective land use problem while the public transport system tries to find the optimal frequency.The travel time depends on road capacity and is described by Greenshields model. The influence of parking capacity upon the parking search time is described by the BPR formula.Participants’ solutions influence one another; therefore, the coalition-free game is constructed. The existence of Nash equilibrium is proved for districts, passengers and public transport. The numerical example shows the impacts of value of time (VOT), population density and parking fee rates on districts land use.

scholarly journals Windowed Transportation Planning Model

1997 ◽  
Vol 1607 (1) ◽  
pp. 45-54 ◽  
Author(s):  
David M. Levinson ◽  
Yuanlin Huang
Keyword(s):  
Traffic Congestion ◽  
Transportation Planning ◽  
Travel Demand ◽  
Transportation Network ◽  
Demand Management ◽  
Local Area ◽  
Planning Model ◽  
Travel Demand Management ◽  
Traffic Calming ◽  
The Impact

A transportation planning model that integrates regional and local-area forecasting approaches is developed and applied. Although regional models have the scope to model the interaction of demand and congestion, they lack spatial detail. Local-area analysis typically does not consider the feedback between new project loadings and existing levels of traffic. A windowed model, which retains regional trip distribution information and the consistency between travel demand and congestion, permits the use of a complete transportation network and block-level traffic zones while retaining computational feasibility. By combining the two methods a number of important policy issues can be addressed, including the implications of traffic calming, changes in flow due to alternative traffic operation schemes, the influence of microscale zoning changes on nearby intersections, and the impact of travel demand management on traffic congestion.

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