Urban mobility heavily relies on private car use, yet public and active transport is on the rise

2017 ◽  
Keyword(s):  
Active Transport ◽  
Urban Mobility ◽  
Car Use ◽  
Private Car

Psychological resistance against attempts to reduce private car use

1998 ◽  
Vol 32 (3) ◽  
pp. 171-181 ◽  
Author(s):  
Gerard Tertoolen ◽  
Dik van Kreveld ◽  
Ben Verstraten
Keyword(s):  
Car Use ◽  
Private Car

scholarly journals Effects of the COVID-19 Lockdown on Urban Mobility: Empirical Evidence from the City of Santander (Spain)

2020 ◽  
Vol 12 (9) ◽  
pp. 3870 ◽  
Author(s):  
Alfredo Aloi ◽  
Borja Alonso ◽  
Juan Benavente ◽  
Rubén Cordera ◽  
Eneko Echániz ◽  
...  
Keyword(s):  
Public Transport ◽  
Traffic Control ◽  
Traffic Accidents ◽  
Urban Mobility ◽  
Environmental Sensors ◽  
Daily Mobility ◽  
Private Car ◽  
The Impact ◽  
The City ◽  
Northern City

This article analyses the impact that the confinement measures or quarantine imposed in Spain on 15 March 2020 had on urban mobility in the northern city of Santander. Data have been collected from traffic counters, public transport ITS, and recordings from traffic control cameras and environmental sensors to make comparisons between journey flows and times before and during the confinement. This data has been used to re-estimate Origin-Destination trip matrices to obtain an initial diagnostic of how daily mobility has been reduced and how the modal distribution and journey purposes have changed. The impact on externalities such as NO2 emissions and traffic accidents have also been quantified. The analysis revealed an overall mobility fall of 76%, being less important in the case of the private car. Public transport users dropped by up to 93%, NO2 emissions were reduced by up to 60%, and traffic accidents were reduced by up to 67% in relative terms.

The effect of marketing messages on the motivation to reduce private car use in different segments

2020 ◽  
Vol 90 ◽  
pp. 22-30
Author(s):  
Alfred Andersson ◽  
Lena Winslott Hiselius ◽  
Emeli Adell
Keyword(s):  
Car Use ◽  
Private Car ◽  
Marketing Messages

scholarly journals Analyzing Urban Residents’ Appraisal of Ridepooling Service Attributes with Conjoint Analysis

2018 ◽  
Vol 10 (10) ◽  
pp. 3711 ◽  
Author(s):  
Alexandra König ◽  
Tabea Bonus ◽  
Jan Grippenkoven
Keyword(s):  
Conjoint Analysis ◽  
Cox Regression ◽  
Information Provision ◽  
Walking Distance ◽  
Transport Systems ◽  
Urban Mobility ◽  
Private Car ◽  
German City ◽  
Sustainable Urban Mobility ◽  
Operational Concept

Public ridepooling systems could contribute to the reduction of traffic volume and emissions in cities by decreasing the number of rides by private car while increasing the average number of passengers per vehicle. Yet, it is unknown how urban travelers value different attributes of the ridepooling’s operational concept. Which characteristics of ridepooling concepts are most important to the users? In order to obtain a deeper understanding of travelers’ preferences concerning a ridepooling system, choice-based Conjoint Analysis was performed. Based on a literature review and a focus group, six relevant attributes of the operational concept of ridepooling systems were determined: fare, walking distance, time of booking, shift of departure time, travel time, and information provision. Data from 237 German city dwellers were analyzed with the help of Cox regression. Except for time of booking, all service attributes significantly affected the respondents’ choice. Besides the high relevance of fare, the results underline the particular importance of the attribute walking distance to the pick-up point for elderly. The results give guidance for the creation of user-centered public transport systems that meet the requirements of the prospective passengers and thus might contribute to the development of shared passenger transport systems for sustainable urban mobility.

scholarly journals Does Car-Sharing Reduce Car-Use? An Impact Evaluation of Car-Sharing in Flanders, Belgium

2020 ◽  
Vol 12 (19) ◽  
pp. 8155
Author(s):  
Donald A. Chapman ◽  
Johan Eyckmans ◽  
Karel Van Acker
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Experimental Methods ◽  
Car Ownership ◽  
Car Sharing ◽  
Car Use ◽  
Binomial Regression ◽  
Quasi Experimental ◽  
Private Car ◽  
The Impact

Private car-use is a major contributor of greenhouse gases. Car-sharing is often hypothesised as a potential solution to reduce car-ownership, which can lead to car-sharing users reducing their car-use. However, there is a risk that car-sharing may also increase car-use amongst some users. Existing studies on the impacts of car-sharing on car-use are often based on estimates of the users’ own judgement of the effects; few studies make use of quasi-experimental methods. In this paper, the impact of car-sharing on car-ownership and car-use in Flanders, Belgium is estimated using survey data from both sharers and non-sharers. The impact on car-use is estimated using zero-inflated negative binomial regression, applied to matched samples of car-sharing users and non-users. The results show that the car-sharing may reduce car-use, but only if a significant number of users reduce their car-ownership. Policy intervention may therefore be required to ensure car-sharing leads to a reduction in car-use by, for example, discouraging car-ownership. Further research using quasi-experimental methods is required to illuminate whether the promise of car-sharing is reflected in reality.

Urban mobility and private car dependency

Urban Forum ◽  
1995 ◽  
Vol 6 (2) ◽  
pp. 1-19 ◽  
Author(s):  
John Howe
Keyword(s):  
Urban Mobility ◽  
Private Car

scholarly journals Beijing’s Peak Car Transition: Hope for Emerging Cities in the 1.5 °C Agenda

2018 ◽  
Vol 3 (2) ◽  
pp. 82-93 ◽  
Author(s):  
Yuan Gao ◽  
Peter Newman
Keyword(s):  
Electric Vehicles ◽  
Government Policies ◽  
Car Ownership ◽  
Traffic Demand ◽  
Car Use ◽  
The Past ◽  
Peak Car ◽  
Private Car ◽  
Per Capita

Peak car has happened in most developed cities, but for the 1.5 °C agenda the world also needs emerging cities to go through this transition. Data on Beijing shows that it has reached peak car over the past decade. Evidence is provided for peak car in Beijing from traffic supply (freeway length per capita and parking bays per private car) and traffic demand (private car ownership, automobile modal split, and Vehicle Kilometres Travelled per capita). Most importantly the data show Beijing has reduced car use absolutely whilst its GDP has continued to grow. Significant growth in electric vehicles and bikes is also happening. Beijing’s transition is explained in terms of changing government policies and emerging cultural trends, with a focus on urban fabrics theory. The implications for other emerging cities are developed out of this case study. Beijing’s on-going issues with the car and oil will remain a challenge but the first important transition is well underway.

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