Joint Model of Sustainable Mode Choice for Commute, Shift Potential and Alternative Mode Chosen

2021 ◽  
pp. 036119812110179
Author(s):  
Ganesh Ambi Ramakrishnan ◽  
Karthik K. Srinivasan ◽  
Aupal Mondal ◽  
Chandra R. Bhat
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Mode Choice ◽  
State Dependence ◽  
Probit Model ◽  
Three Dimensions ◽  
Vehicle Ownership ◽  
Mode Iii ◽  
Alternative Mode ◽  
Work Commute

Rising traffic congestion and severe air pollution in urban areas have led policymakers to find appropriate strategies to encourage the use of sustainable modes. In this context, this paper investigates three choice dimensions related to the work commute travel: (i) Whether and to what extent are sustainable modes considered? (ii) What factors influence the propensity to shift from the primary work commute mode? (iii) Which mode is most likely to be chosen conditional on the decision to shift? These dimensions are analyzed using data of workers from Chennai, India. As the three choices of an individual may be correlated and mutually endogenous because of common and persistent psychological attributes and modal service characteristics, they are modeled using a multi-dimensional probit model. The results show significant evidence of endogeneity, state-dependence, and unobserved correlation across these dimensions leading to significant improvement in fit measures. The results show that perceptions of walkability and environmental impacts of travel modes affect only the consideration of sustainable modes, while vehicle ownership and accessibility to transit affect all three dimensions. Four different behavioral motivations for the decision to shift from the usual mode: dissatisfaction with service attributes, activity constraints, multimodal travel pattern, and inertia, were identified. The mode to which shift occurs is influenced by household vehicle fleet (number and type), exclusive availability to the given decision-maker, and work distance. The insights from this study can be used to identify suitable factors and frame policies to promote sustainable mode choice at various levels.

scholarly journals Assessment of road traffic performance of the Tsunami evacuation road in Padang Municipality area based on the traffic volume simulation approach

2020 ◽  
Vol 156 ◽  
pp. 04008
Author(s):  
Yossyafra Yossyafra ◽  
Nurhuda Fitri ◽  
Rahmat Punama Sidhi ◽  
Yosritzal Yosritzal ◽  
Deni Irda Mazni
Keyword(s):  
Land Use ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Road Traffic ◽  
Traffic Volume ◽  
Disaster Mitigation ◽  
Degree Of Saturation ◽  
Vehicle Ownership ◽  
The Road ◽  
Tsunami Disaster

There are many cities on the west coast of the Sumatra, which are at high risk of the Tsunami disaster. Regional Regulations on Regional Spatial Planning for each City/ Regency have compiled disaster mitigation by constructing several evacuation roads. This study wants to illustrate: what are the volume of traffic generation and road performance, if there is a Tsunami disaster. The simulation is developed by predicting traffic volume based on parameters, population density, vehicle ownership, land use, and activities in the area around the road. The assessment was carried out on two tsunami evacuation roads in the city of Padang, West Sumatra Province. The results show that the highest traffic volume occurred in the period from 06.30 a.m until 3:00 p.m., during school activities. One of the roads will not be able to accommodate the volume of traffic during a disaster, due to significant traffic congestion. This study shows that: (1) the period of activity and land use are two main parameters, which must be considered in designing tsunami evacuation roads, (2) The degree of saturation ratio and the ratio between the capacity of sections of Tsunami evacuation routes can be proposed as a parameter for assessing the performance of Tsunami evacuation roads in urban areas.

The Characteristic of Parking in Pasar Badung Area

2016 ◽  
Vol 2 (7) ◽  
pp. 69
Author(s):  
I Ketut Sutapa
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Average Length ◽  
Processing System ◽  
Vehicle Ownership ◽  
The Road ◽  
Capacity Market ◽  
Parking Lot ◽  
The One

In urban areas, the parking area was a problem that was quite complicated, especially in areas that become activities like industry centres, economy, tourism and others. In term of this, it was due to the fairly large urbanization which causes increasing population in urban areas. In addition, the level of private vehicle ownership was high enough so that it would directly add to the traffic flow. The problem that arose then was the traffic congestion caused by traffic flow exceeds the road capacity, the traffic processing system that is not good, nor because the road does not operate as it should. The one implication was the road not functioning properly was the parking of vehicles using the road (on-street parking). Therefore, this study was conducted to determine the park characteristics, in order to know the parking spaces capacity, as well as providing alternative solutions when capacity did not meet the parking space. This study was only conducted on the parking lot of the capacity market delinquent parking spaces as well as the park characteristics that included the accumulated parking, parking volume, parking average length, parking turnover rate, index parking of which was the object of this research was cars passenger and two-wheelers. In regarding this research could be used as input and consideration in determining or take wisdom in dealing with the parking problem in Pasar Badung (traditional market).

scholarly journals An Analysis of Habitual Mode Use in the Years of Rising Oil Prices

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Chansung Kim ◽  
Woo-Yung Kim ◽  
Jiyoung Park
Keyword(s):  
Public Transportation ◽  
Transportation Network ◽  
Oil Prices ◽  
State Dependence ◽  
Probit Model ◽  
Policy Implications ◽  
Vehicle Ownership ◽  
Passenger Cars ◽  
Transportation Modes ◽  
New City

The existence of state dependence derived from panel data has played a very important role in studying employment and labor policies. This study is about state dependence of the transportation sector using retrospective panel survey data. The Ministry of Land, Infrastructure and Transport of Korea has conducted the survey to monitor changes in vehicle ownership and usage nationwide and to prepare measures when oil prices tend to rise sharply. From this data, we identify the existence of state dependence on passenger cars, public transportation, and nonmotorized modes. To do this, we estimate and analyze the dynamic random effects probit model that explains the selection of each transportation mode after controlling for the unobserved individual heterogeneity. Our results indicate that despite the rise of oil prices, behavior of habitual use (i.e., state dependence) of transportation modes is found in all three modes. The amount of state dependence of nonmotorized modes was the largest, followed by passenger cars and public transportation. From the estimated models, important policy implications can be drawn from the fact that the presence of state dependence and the importance of early habit formation are important not only in nonmotorized modes but also in public transportation. In other words, if policy makers want to encourage people to use public transportation in a new city, it suggests that a sufficient and convenient public transportation network should be built before people move to the city. Once cities are built without sufficient public transportation networks and people have become accustomed to using private cars, then it will be more difficult to change their transportation modes, requiring much more social efforts and costs.

Preferred Mode Choice Model for Commuter Purpose Based on Multinominal Logit Model

2011 ◽  
Vol 97-98 ◽  
pp. 570-575
Author(s):  
Yan Han ◽  
Hong Zhi Guan ◽  
Meng Xue
Keyword(s):  
Travel Behavior ◽  
Traffic Congestion ◽  
Goodness Of Fit ◽  
Choice Model ◽  
Mode Choice ◽  
Forecast Accuracy ◽  
Vehicle Ownership ◽  
Mode Choice Model ◽  
Public Traffic ◽  
Fit Index

As a quasi-public traffic mode, more and more attention has been paid to the commuter bus to ease the traffic congestion. To get the travel behaviors of the commuters to which the commuter bus is available, The RP and SP survey about the travel behavior of commuters were carried out and the influencing factors of mode choice are discussed. The commuting mode combinations were found to exist during the decision-making process and there exist the preferred mode and secondary mode for each individual for one trip mode choice. The preferred mode choice model is established based on the multinomial logit mode. The results show that gender, month income, vehicle ownership, commuter cost, and commuter time have marked influences on the result of preferred mode choice for commuter purpose. The goodness of fit parameter ρ2 and goodness-of fit index adjusted by freedom ρ2 of the preferred mode choice model are 0.407 and 0.369 respectively, which implies that the forecast accuracy of the model is high. The VOT of the respondents in the survey is 29.9RMB/h and the results can provide a good reference for designing and optimizing of the commuter bus.

Smart Driving System for Improving Traffic Flow

2017 ◽  
Vol 7 (7) ◽  
pp. 236
Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Adaptive Cruise Control ◽  
Human Perception ◽  
Cruise Control ◽  
Driving System ◽  
V2v Communication ◽  
Traffic Conditions ◽  
Cooperative Adaptive Cruise Control

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

scholarly journals Constrained Urban Airspace Design for Large-Scale Drone-Based Delivery Traffic

Aerospace ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 38
Author(s):  
Malik Doole ◽  
Joost Ellerbroek ◽  
Victor L. Knoop ◽  
Jacco M. Hoekstra
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Large Scale ◽  
Cost Savings ◽  
Future Research ◽  
Fast Time ◽  
Potential Cost ◽  
Horizontal Structure ◽  
Traffic Demand ◽  
Demand Patterns

Large-scale adoption of drone-based delivery in urban areas promise societal benefits with respect to emissions and on-ground traffic congestion, as well as potential cost savings for drone-based logistic companies. However, for this to materialise, the ability of accommodating high volumes of drone traffic in an urban airspace is one of the biggest challenges. For unconstrained airspace, it has been shown that traffic alignment and segmentation can be used to mitigate conflict probability. The current study investigates the application of these principles to a highly constrained airspace. We propose two urban airspace concepts, applying road-based analogies of two-way and one-way streets by imposing horizontal structure. Both of the airspace concepts employ heading-altitude rules to vertically segment cruising traffic according to their travel direction. These airspace configurations also feature transition altitudes to accommodate turning flights that need to decrease the flight speed in order to make safe turns at intersections. While using fast-time simulation experiments, the performance of these airspace concepts is compared and evaluated for multiple traffic demand densities in terms of safety, stability, and efficiency. The results reveal that an effective way to structure drone traffic in a constrained urban area is to have vertically segmented altitude layers with respect to travel direction as well as horizontal constraints imposed to the flow of traffic. The study also makes recommendations for areas of future research, which are aimed at supporting dynamic traffic demand patterns.

scholarly journals META-HEURISTIC APPROACH FOR HIGH-DEMAND FACILITY LOCATIONS CONSIDERING TRAFFIC CONGESTION AND GREENHOUSE GAS EMISSION

2016 ◽  
Vol 24 (4) ◽  
pp. 233-244 ◽  
Author(s):  
Taesung HWANG ◽  
Minho LEE ◽  
Chungwon LEE ◽  
Seungmo KANG
Keyword(s):  
Greenhouse Gas ◽  
Facility Location ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Greenhouse Gas Emission ◽  
Memetic Algorithms ◽  
Distribution Centers ◽  
Ghg Emission ◽  
High Demand ◽  
Facility Locations

Large facilities in urban areas, such as storage facilities, distribution centers, schools, department stores, or public service centers, typically generate high volumes of accessing traffic, causing congestion and becoming major sources of greenhouse gas (GHG) emission. In conventional facility-location models, only facility construction costs and fixed transportation costs connecting customers and facilities are included, without consideration of traffic congestion and the subsequent GHG emission costs. This study proposes methods to find high-demand facility locations with incorporation of the traffic congestion and GHG emission costs incurred by both existing roadway traffic and facility users into the total cost. Tabu search and memetic algorithms were developed and tested with a conventional genetic algorithm in a variety of networks to solve the proposed mathematical model. A case study to determine the total number and locations of community service centers under multiple scenarios in Incheon City is then presented. The results demonstrate that the proposed approach can significantly reduce both the transportation and GHG emission costs compared to the conventional facility-location model. This effort will be useful for decision makers and transportation planners in the analysis of network-wise impacts of traffic congestion and vehicle emission when deciding the locations of high demand facilities in urban areas.

scholarly journals Review of Whole System Simulation Methodologies for Assessing Mobility as a Service (MaaS) as an Enabler for Sustainable Urban Mobility

2021 ◽  
Vol 13 (10) ◽  
pp. 5591
Author(s):  
Mark Muller ◽  
Seri Park ◽  
Ross Lee ◽  
Brett Fusco ◽  
Gonçalo Homem de Almeida Correia
Keyword(s):  
Urban Areas ◽  
Mode Choice ◽  
Urban Mobility ◽  
City Region ◽  
Sustainable Mobility ◽  
Simulation Tools ◽  
Future Assessment ◽  
Transportation Simulation ◽  
Sustainable Urban Mobility ◽  
The Impact

Mobility as a Service (MaaS) is an emerging concept that is being advanced as an effective approach to improve the sustainability of mobility, especially in densely populated urban areas. MaaS can be defined as the integration of various transport modes into a single service, accessible on demand, via a seamless digital planning and payment application. Recent studies have shown the potential reduction in the size of automobile fleets, with corresponding predicted improvements in congestion and environmental impact, that might be realized by the advent of automated vehicles as part of future MaaS systems. However, the limiting assumptions made by these studies point to the difficult challenge of predicting how the complex interactions of user demographics and mode choice, vehicle automation, and governance models will impact sustainable mobility. The work documented in this paper focused on identifying available methodologies for assessing the sustainability impact of potential MaaS implementations from a whole system (STEEP—social, technical, economic, environmental, and political) perspective. In this research, a review was conducted of current simulation tools and models, relative to their ability to support transportation planners, to assess the MaaS concept, holistically, at a city level. The results presented include: a summary of the literature review, a weighted ranking of relevant transportation simulation tools per the assessment criteria, and identification of key gaps in the current state of the art. The gaps include capturing the interaction of demographic changes, mode choice, induced demand, and land use in a single framework that can rapidly explore the impact of alternative MaaS scenarios, on sustainable mobility, for a given city region. These gaps will guide future assessment methodologies for urban mobility systems, and ultimately assist informed decision-making.

scholarly journals EXTRACTION AND VISUALIZATION OF 3D BUILDING MODELS IN URBAN AREAS FOR FLOOD SIMULATION

2019 ◽  
Vol XLII-2/W11 ◽  
pp. 669-673 ◽  
Author(s):  
C. E. Kilsedar ◽  
F. Fissore ◽  
F. Pirotti ◽  
M. A. Brovelli
Keyword(s):  
Urban Areas ◽  
Three Dimensional ◽  
Decision Makers ◽  
Three Dimensions ◽  
Adaptation Measures ◽  
Flood Simulation ◽  
Domain Experts ◽  
Effective Strategies ◽  
Web Map ◽  
Building Models

<p><strong>Abstract.</strong> Floods pose a risk that is likely to worsen in the future due to climate change. Therefore, it is essential that decision makers and domain experts have the tools to evaluate the effects of floods. We developed a tool that visualizes the earth and buildings in three dimensions to simulate floods so that effective strategies can be developed to enhance resilience and mitigate the effects of floods. We opted to use open standards and free and open source software (FOSS) for Web to maximize interoperability, replicability, reusability, and accessibility. As a result of the literature review, we decided to use CityGML and CesiumJS for three-dimensional geospatial data visualization. However, as CityGML data is not available for the cities that our project focuses on, we developed software called shp2city that converts Esri shapefile to CityGML data in LOD1 or LOD2. Moreover, as CityGML data cannot be immediately used with CesiumJS, we used 3DCityDB to store, represent, and manage the CityGML data; 3DCityDB Importer/Exporter to export the CityGML data in KML/COLLADA/glTF format to be used within the 3DCityDB Web-Map-Client that is based on CesiumJS for visualization. Finally, we simulated floods to aid in the informed decision-making process regarding adaptation measures and mitigation of flooding effects.</p>

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