Mode choice analysis in urban transport with shared battery electric vehicles: A stated-preference case study in Beijing, China

2020 ◽  
Vol 133 ◽  
pp. 95-108 ◽  
Author(s):  
Fanglei Jin ◽  
Kun An ◽  
Enjian Yao
Keyword(s):  
Electric Vehicles ◽  
Stated Preference ◽  
Mode Choice ◽  
Urban Transport ◽  
Battery Electric Vehicles ◽  
Choice Analysis ◽  
Beijing China

scholarly journals Mode choice analysis using discrete choice model from transport user (Case study: Jakarta LRT, Indonesia)

2018 ◽  
Vol 181 ◽  
pp. 03001
Author(s):  
Dwi Novi Wulansari ◽  
Milla Dwi Astari
Keyword(s):  
Discrete Choice ◽  
Public Transportation ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Choice Models ◽  
Discrete Choice Models ◽  
Light Rail ◽  
Choice Analysis ◽  
Mode Choice Model

Jakarta Light Rail Transit (Jakarta LRT) has been planned to be built as one of mass rail-based public transportation system in DKI Jakarta. The objective of this paper is to obtain a mode choice models that can explain the probability of choosing Jakarta LRT, and to estimate the sensitivity of mode choice if the attribute changes. Analysis of the research conducted by using discrete choice models approach to the behavior of individuals. Choice modes were observed between 1) Jakarta LRT and TransJakarta Bus, 2) Jakarta LRT and KRL-Commuter Jabodetabek. Mode choice model used is the Binomial Logit Model. The research data obtained through Stated Preference (SP) techniques. The model using the attribute influences such as tariff, travel time, headway and walking time. The models obtained are reliable and validated. Based on the results of the analysis shows that the most sensitive attributes affect the mode choice model is the tariff.

Impacts of electricity mix, charging profile, and driving behavior on the emissions performance of battery electric vehicles: A Belgian case study

2015 ◽  
Vol 148 ◽  
pp. 496-505 ◽  
Author(s):  
Surendraprabu Rangaraju ◽  
Laurent De Vroey ◽  
Maarten Messagie ◽  
Jan Mertens ◽  
Joeri Van Mierlo
Keyword(s):  
Electric Vehicles ◽  
Driving Behavior ◽  
Battery Electric Vehicles ◽  
Electricity Mix

Investigating the Strategies for Reducing Motorcycle Mode Choice in Urban Trips: Case Study of Tehran City

2019 ◽  
Vol 2673 (10) ◽  
pp. 58-69 ◽  
Author(s):  
Babak Mirbaha ◽  
Fatemeh Mohajeri
Keyword(s):  
Choice Behavior ◽  
Stated Preference ◽  
Mode Choice ◽  
Noise Pollution ◽  
Nested Logit ◽  
Master Plan ◽  
Logit Models ◽  
Maintenance Costs ◽  
Survey Results

Motorcycles in Iran, especially in metropolises such as Tehran, are used extensively for various reasons such as low maintenance costs, high maneuverability, and the possibility of entering congestion priced zones without paying a toll. Nevertheless, motorcycles are involved in 25% of accidents and produce almost 30% of air and 50% of noise pollution in Tehran. Current research aims to investigate possible scenarios for reducing the use of motorcycles in Tehran’s traffic and transportation master plan strategies. After designing the scenarios, a stated preference method is used for gathering the required data from various groups of motorcycle riders in Tehran. More than 2,000 questionnaires were completed of which 1,766 were deemed acceptable for data entering and further analysis. Increasing the price of motorcycle maintenance and charging motorcycles to enter the congestion priced zone of Tehran (CPZT) were two main scenarios which were considered in this research. Multinomial and nested logit models were applied to analyze the trip choice behavior of motorcycle riders who had participated in the survey. Results indicated that strategies such as increasing motorcycle maintenance costs could be effective in reducing the use of motorcycles. For instance, increasing motorcycle maintenance costs by 4.7 times and imposing a 70,000 IRR toll price to enter the CP zone resulted in a 66% reduction in motorcycle mode choice by motorcycle riders.

scholarly journals Empirical Analysis of Parking Behaviour of Conventional and Electric Vehicles for Parking Modelling: A Case Study of Beijing, China

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3073 ◽  
Author(s):  
Zhuge ◽  
Shao ◽  
Li
Keyword(s):  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Parking Lot ◽  
Range Anxiety ◽  
Driving Range ◽  
Beijing China ◽  
Walking Time

An empirical study of the parking behaviour of Conventional Vehicles (CVs), Battery Electric Vehicles (BEVs), and Plug-in Hybrid Electric Vehicles (PHEVs) was carried out with the data collected in a paper-based questionnaire survey in Beijing, China. The study investigated the factors that might influence the parking behaviour, with a focus on the maximum acceptable time of walking from parking lot to trip destination, parking fee, the availability of charging posts, the state of charge of EVs and the range anxiety of BEVs. Several Multinomial Logit (MNL) models were developed to explore the relationships between individual attributes and parking choices. The results suggest that (1) the maximum acceptable walking time generally increases with the rise in the amount of saving for parking fee; (2) the availability of charging posts does not influence the maximum acceptable walking time when PHEVs and BEVs have sufficient charge, but the percentage of people willing to walk longer than eight minutes increases from around 35% to 46% when PHEVs are in a low stage of charge; (3) more than half of BEV drivers want the driving range of their vehicles to be one and a half times the driving distance before they depart, given the distance is 50 km. Based on the empirical findings above, a conceptual framework was proposed to explicitly simulate the parking behaviour of both CVs and EVs using agent-based modelling.

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