scholarly journals Anticipating land-use impacts of self-driving vehicles in the Austin, Texas, region

2020 ◽  
Vol 13 (1) ◽  
pp. 185-205
Author(s):  
Tyler Wellik ◽  
Kara Kockelman
Keyword(s):  
Land Use ◽  
Autonomous Vehicles ◽  
Land Use Impacts ◽  
Final Model ◽  
Average Work ◽  
Travel Time Savings ◽  
Residential Land Use ◽  
Work Trip ◽  
Model Year ◽  
The City

This paper used an implementation of the land-use model SILO in Austin, Texas, over a 27-year period with an aim to understand the impacts of the full adoption of self-driving vehicles on the region’s residential land use. SILO was integrated with MATSim for the Austin region. Land-use and travel results were generated for a business-as-usual case (BAU) of 0% self-driving or “autonomous” vehicles (AVs) over the model timeframe versus a scenario in which households’ value of travel time savings (VTTS) was reduced by 50% to reflect the travel-burden reductions of no longer having to drive. A third scenario was also compared and examined against BAU to understand the impacts of rising vehicle occupancy (VO) and/or higher roadway capacities due to dynamic ride-sharing (DRS) options in shared AV (SAV) fleets. Results suggested an 8.1% increase in average work-trip times when VTTS fell by 50% and VO remained unaffected (the 100% AV scenario) and a 33.3% increase in the number of households with “extreme work-trips” (over 1 hour, each way) in the final model year (versus BAU of 0% AVs). When VO was raised to 2.0 and VTTS fell instead by 25% (the “Hi-DRS” SAV scenario), average work-trip times increased by 3.5% and the number of households with “extreme work-trips” increased by 16.4% in the final model year (versus BAU of 0% AVs). The model also predicted 5.3% fewer households and 19.1% more available, developable land in the city of Austin in the 100% AV scenario in the final model year relative to the BAU scenario’s final year, with 5.6% more households and 10.2% less developable land outside the city. In addition, the model results predicted 5.6% fewer households and 62.9% more available developable land in the city of Austin in the Hi-DRS SAV scenario in the final model year relative to the BAU scenario’s final year, with 6.2% more households and 9.9% less developable land outside the city.

scholarly journals Will autonomous vehicles undermine Ontario provincial policies to concentrate jobs and housing? Evidence from the Greater Toronto-Hamilton area

2021 ◽  
Author(s):  
Tyler Olsen
Keyword(s):  
Land Use ◽  
Key Words ◽  
Autonomous Vehicles ◽  
Land Use Patterns ◽  
High Quality ◽  
Travel Mode ◽  
Use Patterns ◽  
Transit Use ◽  
The City ◽  
The Way

Fully autonomous vehicles (AVs) may drastically alter the way people travel and where they choose to live and work. AVs could lead to either more dispersed or concentrated land use patterns. The concentration of employment and residences—along with travel mode emphasis on transit, cycling and walking—is a central priority for Ontario’s Growth Plan for the Greater Golden Horseshoe. This study explores responses to a 2016 survey of residents of the Greater Toronto and Hamilton Area, regarding the potential relocation of work or residence in response to AVs, to understand the locations and characteristics related and the potential impacts on land use that may result. There is potential for high-quality shared AV service to act as a concentrating force for residences in the City of Toronto and its western and northern suburbs. But there is also potential for AVs to disrupt travel mode-based objectives, eroding pedestrian and transit use. Key Words: Autonomous Vehicles, Land Use, Toronto

scholarly journals Will autonomous vehicles undermine Ontario provincial policies to concentrate jobs and housing? Evidence from the Greater Toronto-Hamilton area

2021 ◽  
Author(s):  
Tyler Olsen
Keyword(s):  
Land Use ◽  
Key Words ◽  
Autonomous Vehicles ◽  
Land Use Patterns ◽  
High Quality ◽  
Travel Mode ◽  
Use Patterns ◽  
Transit Use ◽  
The City ◽  
The Way

Fully autonomous vehicles (AVs) may drastically alter the way people travel and where they choose to live and work. AVs could lead to either more dispersed or concentrated land use patterns. The concentration of employment and residences—along with travel mode emphasis on transit, cycling and walking—is a central priority for Ontario’s Growth Plan for the Greater Golden Horseshoe. This study explores responses to a 2016 survey of residents of the Greater Toronto and Hamilton Area, regarding the potential relocation of work or residence in response to AVs, to understand the locations and characteristics related and the potential impacts on land use that may result. There is potential for high-quality shared AV service to act as a concentrating force for residences in the City of Toronto and its western and northern suburbs. But there is also potential for AVs to disrupt travel mode-based objectives, eroding pedestrian and transit use. Key Words: Autonomous Vehicles, Land Use, Toronto

scholarly journals Estimation of trip generation rates for residential land use in Uyo, Nigeria

2021 ◽  
Vol 39 (4) ◽  
pp. 972-980
Author(s):  
I.N. Usanga ◽  
R.K. Etim ◽  
V. Umoren
Keyword(s):  
Land Use ◽  
Household Income ◽  
Household Size ◽  
Transport Infrastructure ◽  
Car Ownership ◽  
Trip Generation ◽  
Residential Land ◽  
Residential Land Use ◽  
Cross Classification ◽  
Work Trip

Change in trip rates affects a transportation system and could lead to the redesign of the transport infrastructure in order to satisfy the new demand. This study estimates trip generation rates for residential land use in Uyo using cross classification method. Five (5) residential estates were considered and household survey carried out to collect trip data from 500 households on purpose and mode of travel through household interview and their response recorded in questionnaire. Four independent variables (household size, household income, car ownership, number of employed persons) were used for the study based on the prevailing conditions of theresidential land use. Cross-classification trip rates were developed from the most significant variables; household size, household income and car ownership. The analysis indicated that work trip produced the highest reported trip rates of 29.6% followed by religious trip of 24.7%. Similarly, private car trips contributed 42.8% of trips made by mode of travel as the highest trip. It was found that household size is the strongest socio-economic variable that influence trip generation in residential land use in Uyo. The cross-classification trip rates developed in this study could provide basis for the estimation of trip generation in residential land use in Uyo. Keywords: Trip generation; analysis of variance, ANOVA; cross classification 

scholarly journals Socio-economic factors of high trash generation in the city of Los Angeles

2019 ◽  
Vol 80 (3) ◽  
pp. 408-417
Author(s):  
Xiaoyu Liang ◽  
Mi-Hyun Park ◽  
Michael K. Stenstrom
Keyword(s):  
Land Use ◽  
Los Angeles ◽  
Human Impacts ◽  
Economic Status ◽  
Quantitative Model ◽  
Control Measures ◽  
Final Model ◽  
The Impact ◽  
The City ◽  
Socio Economic Factors

Abstract Trash is one of major pollutants in urban runoff. Some studies have been conducted to verify the different impacts of land use on trash generation in a qualitative way and focused on the performance of trash control measures. Few studies have explored the human impacts on trash generation or developed a quantitative model to describe the phenomenon. This paper examined the impact of human activity on trash generation. Spatial regimes on high trash generation areas were identified using the selected variables from best subset model regression and validated with Moran's I scatter plot and spatial analysis of variance. Bidirectional spatial lag regression with regimes was performed to develop the final model to explain the spatial distribution of trash generation and identify its major causes. The result showed that economic status and occupation of the population were correlated with trash accumulation and the dominant land use type, and the distance to rivers most affected trash generation. The effects of these indicators were different within and outside the high trash generation areas.

Optimal Land Use Analysis Using Lindenmayer Grammars

2013 ◽  
Vol 8 (2) ◽  
pp. 163-175
Author(s):  
Urszula Żukowska ◽  
Grażyna Kalewska
Keyword(s):  
Land Use ◽  
Urban Development ◽  
Computer Program ◽  
L System ◽  
L Systems ◽  
The City

In today's world, when it is so important to use every piece of land for a particular purpose, both economically and ecologically, identifying optimal land use is a key issue. For this reason, an analysis of the optimal land use in a section of the city of Olsztyn, using the L-system Urban Development computer program, was chosen as the aim of this paper. The program uses the theories of L-systems and the cartographic method to obtain results in the form of sequences of productions or maps. For this reason, the first chapters outline both theories, i.e. the cartographic method to identify optimal land use and Lindenmayer grammars (called L-systems). An analysis based on a fragment of the map of Olsztyn was then carried out. Two functions were selected for the analysis: agricultural and forest-industrial. The results are presented as maps and sequences in individual steps.

scholarly journals Modeling the Impacts of Autonomous Vehicles on Land Use Using a LUTI Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1608
Author(s):  
Rubén Cordera ◽  
Soledad Nogués ◽  
Esther González-González ◽  
José Luis Moura
Keyword(s):  
Land Use ◽  
Urban Sprawl ◽  
Autonomous Vehicles ◽  
Interaction Model ◽  
Urban Systems ◽  
Unwanted Effect ◽  
Urban Center ◽  
Positive Effects ◽  
Current Paradigm ◽  
Shed Light

Autonomous vehicles (AVs) can generate major changes in urban systems due to their ability to use road infrastructures more efficiently and shorten trip times. However, there is great uncertainty about these effects and about whether the use of these vehicles will continue to be private, in continuity with the current paradigm, or whether they will become shared (carsharing/ridesharing). In order to try to shed light on these matters, the use of a scenario-based methodology and the evaluation of the scenarios using a land use–transport interaction model (LUTI model TRANSPACE) is proposed. This model allows simulating the impacts that changes in the transport system can generate on the location of households and companies oriented to local demand and accessibility conditions. The obtained results allow us to state that, if AVs would generate a significant increase in the capacity of urban and interurban road infrastructures, the impacts on mobility and on the location of activities could be positive, with a decrease in the distances traveled, trip times, and no evidence of significant urban sprawl processes. However, if these increases in capacity are accompanied by a large augment in the demand for shared journeys by new users (young, elderly) or empty journeys, the positive effects could disappear. Thus, this scenario would imply an increase in trip times, reduced accessibilities, and longer average distances traveled, all of which could cause the unwanted effect of expelling activities from the consolidated urban center.

scholarly journals Changing Land Use and Population Density Are Degrading Water Quality in the Lower Mekong Basin

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1948
Author(s):  
Flavia Tromboni ◽  
Thomas E. Dilts ◽  
Sarah E. Null ◽  
Sapana Lohani ◽  
Peng Bun Ngor ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Population Density ◽  
Local Population ◽  
Reference Conditions ◽  
Mekong River ◽  
Land Use Impacts ◽  
Wet Season ◽  
Mekong Basin ◽  
Lower Mekong Basin

Establishing reference conditions in rivers is important to understand environmental change and protect ecosystem integrity. Ranked third globally for fish biodiversity, the Mekong River has the world’s largest inland fishery providing livelihoods, food security, and protein to the local population. It is therefore of paramount importance to maintain the water quality and biotic integrity of this ecosystem. We analyzed land use impacts on water quality constituents (TSS, TN, TP, DO, NO3−, NH4+, PO43−) in the Lower Mekong Basin. We then used a best-model regression approach with anthropogenic land-use as independent variables and water quality parameters as the dependent variables, to define reference conditions in the absence of human activities (corresponding to the intercept value). From 2000–2017, the population and the percentage of crop, rice, and plantation land cover increased, while there was a decrease in upland forest and flooded forest. Agriculture, urbanization, and population density were associated with decreasing water quality health in the Lower Mekong Basin. In several sites, Thailand and Laos had higher TN, NO3−, and NH4+ concentrations compared to reference conditions, while Cambodia had higher TP values than reference conditions, showing water quality degradation. TSS was higher than reference conditions in the dry season in Cambodia, but was lower than reference values in the wet season in Thailand and Laos. This study shows how deforestation from agriculture conversion and increasing urbanization pressure causes water quality decline in the Lower Mekong Basin, and provides a first characterization of reference water quality conditions for the Lower Mekong River and its tributaries.

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