scholarly journals Estimation of baboon daily travel distances by means of point sampling – the magnitude of underestimation

2017 ◽  
Vol 4 (2) ◽  
pp. 143-151 ◽  
Author(s):  
Holger Sennhenn-Reulen ◽  
Langhalima Diedhiou ◽  
Matthias Klapproth ◽  
Dietmar Zinner
Keyword(s):  
Movement Ecology ◽  
Relative Increase ◽  
Food Distribution ◽  
Time Intervals ◽  
Sampling Protocols ◽  
Path Distance ◽  
Daily Travel Distance ◽  
Tracking Time ◽  
Interval Lengths ◽  
Daily Travel

Abstract. Daily travel distance (DTD), the distance an animal moves over the course of the day, is an important metric in movement ecology. It provides data with which to test hypotheses related to energetics and behaviour, e.g. impact of group size or food distribution on DTDs. The automated tracking of movements by applying GPS technology has become widely available and easy to implement. However, due to battery duration constraints, it is necessary to select a tracking-time resolution, which inevitably introduces an underestimation of the true underlying path distance. Here we give a quantification of this inherent systematic underestimation of DTDs for a terrestrial primate, the Guinea baboon. We show that sampling protocols with interval lengths from 1 to 120 min underestimate DTDs on average by 7 to 35 %. For longer time intervals (i.e. 60, 90, 120 min), the relative increase of deviation from the true trajectory is less pronounced than for shorter intervals. Our study provides first hints on the magnitude of error, which can be applied as a corrective when estimating absolute DTDs in calculations on travelling costs in terrestrial primates.

scholarly journals 10. Estimation of Daily Travel Distance and Home Range

2002 ◽  
Vol 18 (3) ◽  
pp. 326-333 ◽  
Author(s):  
Juichi YAMAGIWA ◽  
Yukiko SHIMOOKA
Keyword(s):  
Home Range ◽  
Travel Distance ◽  
Daily Travel Distance ◽  
Daily Travel

scholarly journals Predicting a Vehicle's Distance Traveled from Short-duration Data

2019 ◽  
Author(s):  
Ruohan Li ◽  
Kara M Kockelman
Keyword(s):  
Short Duration ◽  
Travel Distance ◽  
Full Time ◽  
Gini Coefficients ◽  
Total Distance ◽  
Daily Travel Distance ◽  
Annual Total ◽  
Distance Data ◽  
Instrumented Vehicles ◽  
Daily Travel

This article uses one year’s worth of daily travel distance data for 252 Seattle households’ vehicles to ascertain that one day’s distance (plus day of week and month of year information) accounts for 10.7% of the variability in that vehicle’s annual (total) distance traveled, while two and seven consecutive days’ distance values predict 16.7% and 33.6%, respectively. In analyzing Gini coefficients (which average 0.546 + / − 0.117 across these instrumented vehicles), one finds that full-time employed females have the most stable day-to-day driving patterns, allowing for shorter-duration surveys of such households.

scholarly journals Suasana Mendung di Cempaka Sari

2020 ◽  
Vol 19 ◽  
pp. 73-77
Author(s):  
Noor Azizan Rahman Paiman
Keyword(s):  
Travel Distance ◽  
Daily Activities ◽  
Visual Elements ◽  
Environmental Experience ◽  
Daily Travel Distance ◽  
Daily Travel

This work entitled “Suasana Mendung di Cempaka Sari” in terms of ideas is held through environmental experience encountered by the artist since residing in Perak (from 2001 until now). The artist lives in Seri Manjung district and works at Universiti Teknologi MARA (UiTM) Perak Branch, Seri Iskandar (in Bota sub-district). Hence the daily travel distance of the artist goes back and forth from home to work and vice versa is about 100 kilometres. Through “daily activities” back and forth, the artist indirectly has been served with various shapes and visual elements pertaining to “social products” that are having “potential” to be questioned such as politics, economics, culture, religion, or environment in supporting the formation of his ideas for designing artwork.

Optimal battery capacity for an electric-vehicle-sharing-model in the People’s Republic of China

2016 ◽  
Vol 231 (11) ◽  
pp. 1471-1488 ◽  
Author(s):  
Ning Wang ◽  
Runlin Yan ◽  
Gangzhan Fu
Keyword(s):  
Life Cycle ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Economic Benefits ◽  
Government Subsidy ◽  
Republic Of China ◽  
Battery Electric Vehicles ◽  
Battery Capacity ◽  
Daily Travel Distance ◽  
Daily Travel

A project on electric vehicle sharing has been previously carried out as a demonstration operation in Shanghai, Beijing, Hangzhou and Shenzhen in the People’s Republic of China. The high initial investment caused by the high cost of batteries limits commercialization of an electric-vehicle-sharing model. Therefore, a key problem that the operators must solve is to choose the appropriate battery capacity for shared electric vehicles based on different urban driving cycles. Based on three new energy vehicles (i.e. electric vehicles) for demonstration cities of different scales as represented by Shanghai, Shenzhen and Hefei, a whole-life-cycle evaluation model of economic benefits for shared battery electric vehicles was established in this paper. The optimal battery capacity for different substitution rates was calculated using MATLAB software. Then, the influences that the substitution rate, the urban driving cycle, the average daily travel distance, the service price, the charging price, the battery (cycle) life, the battery pack cost and the government subsidy have on the optimal battery capacity in the life-cycle economic benefit model was explained. Suggestions for the optimal battery capacity are provided for operators in different cities. The results indicate that the purchasing cost, the energy consumption cost and the battery depreciation cost are the three main components of the life-cycle cost, which account for more than 80%. The average daily travel distance and the local government subsidy affect the optimal battery capacity only for certain substitution rates. The life-cycle economic benefits of one shared electric vehicle is found to have the most influence on the service price. This paper suggests that shared battery electric vehicles with different battery sizes of 44.5 kW h, 34.9 kW h and 36.96 kW h are suitable for use in metropolitan cities, in large-sized to medium-sized cities and in medium-sized to small-sized cities respectively, as represented correspondingly by Shanghai, Shenzhen and Hefei.

scholarly journals Range and Battery Depletion Concerns with Electric Vehicles

2017 ◽  
Vol 2017 ◽  
pp. 1-12
Author(s):  
Tomio Miwa ◽  
Hitomi Sato ◽  
Takayuki Morikawa
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Battery Electric Vehicle ◽  
Questionnaire Data ◽  
Charging Station ◽  
Intention To Purchase ◽  
Probabilistic Distribution ◽  
Daily Travel Distance ◽  
Charging Stations ◽  
Daily Travel

This study investigates the effects of the range of a battery electric vehicle (EV) by using questionnaire data. The concern about battery depletion changes according to charging station deployment. Firstly, the methodology for deriving the probabilistic distribution of the daily travel distance is developed, which enables us to analyze people’s tolerance of the risk of battery depletion. Secondly, the desired range of an EV is modeled. This model considers the effect of changing charging station deployment and can analyze the variation in the desired range. Then, the intention of a household to purchase an EV is analyzed by incorporating range-related variables. The results show that people can live with a risk of battery depletion of around 2% to 5%. The deployment of charging stations at large retail facilities and/or workplace parking spaces reduces the desired range of an EV. Finally, the answers to the questionnaire show that the probability of battery depletion on a driving day has little effect on the intention to purchase an EV. Instead, people tend to evaluate the range by itself or directly compare it with their desired range.

The Role of Subcentres for Commuting and Non-Work Travel Distances and Modes in the Copenhagen Metropolitan Region

2019 ◽  
Vol 45 (4) ◽  
pp. 462-475
Author(s):  
Thomas A. Sick Nielsen
Keyword(s):  
Short Distance ◽  
Smart Growth ◽  
Travel Behaviour ◽  
Metropolitan Region ◽  
Daily Travel Distance ◽  
Micro Level ◽  
Travel Distances ◽  
Daily Travel ◽  
Behaviour Data

Understanding the functional geography of the metropolitan region, and developing location criteria for smart growth, requires analysis of subcentres and their effects. Subcentres were identified in the Copenhagen area based on spatial analysis of micro-level employment and retail data. Subcentres' effects on transport in addition to regional centrality were studied with regression analysis of work and nonwork travel behaviour data. Distance to employment subcentres with a minimum of 10,000 jobs and distance to subcentres identi fied from retail data and having a minimum of 400 retail jobs affects residents' daily travel distance and/or transport modes. A short distance to a subcentre allows for shorter daily travel distances and, in the case of retail subcentres, for a higher probability of using public transport or walking/cycling. However, the effects of subcentres are well below the still strong and significant effect of regional centrality upon travel distances as well as mode choice.

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