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Perceived car dependence

Eva Van Eenoo,  Koos Fransen and Kobe Boussauw, from the Cosmopolis Centre for Urban Research, Vrije Universiteit Brussel, Belgiumpublished an article in EJTIR on march 2022, regarding car dependence and multimodality. The article provides an a-up to date review on this issue. Here are some of the key issues.

The private car remains the main mode of personal transport in the EU and despite the considerable benefits that come with reducing motorized traffic, car  ownership in the EU increases. In 2019, the European Union car fleet grew by 1.8% compared to  2018, with the number of cars on the road reaching 242.7 million. In addition, car  ownership has increased from 2015 to 2019 from 553 to 569 cars per one thousand inhabitants.

The figures  mentioned hide variations in travel patterns and mode use. Against this backdrop, multimodality is increasingly gaining attention. Multimodality is most commonly defined as the use of at least two modes during a specific time period. It is found that multimodality is more prevalent in  areas with higher population densities.

Car dependence of individuals may be composed of two elements: the absolute need for a car, and the perception of reliance on a car. In the case of ‘structural’ car dependence there is absolutely no reasonable alternative for the car available. In the case of ‘conscious’ dependence, alternative transport modes are present but are not actively considered. The study points out that this distinction as perceived versus actual car dependence.

However, it is not clear if multimodal travel patterns lead to a lower perceived car dependence. Using cluster analysis, the research aims to fill this gap and explore if and in what way multimodality correlates with perceived car dependence.

Study area

The geographical scope of the research are urbanized areas in the Flemish region in Belgium. On average, 69.6% of the trips in the Flemish region are carried out by car (as a driver or as a passenger), although the car accounts  for 82.3% of the Vehicle Kilometers Traveled (VKT). Overall, 12.4% and  11.4% of all trips are carried out respectively by bicycle and on foot. Only 4.5% of all trips are  undertaken with public transport.

In the selected areas, the authors carried out an online survey between October 2019 and February 2020,  specifically targeting individuals with at least one car in the household and in the possession of a driving license.

Car-dependent motorists long distance (CDML)

From the group of car-dependent motorists, 89.5% use a car daily. This is the highest  score of all clusters. Their perceived car  dependence is the highest of all clusters: 92.6% agree with the statement. However, this does not  imply that this group is unimodal, as 41.2% ride a bicycle at least weekly.

Car-dependent motorists short distance (CDMS)

Similar to the car-dependent motorists long distance, for respondents of the car-dependent  motorists short distance cluster, the car is the dominant mode of transport. In the same vein, their perceived car dependence is high, although slightly less than for the CDML. This group does not frequently travel by bicycle. Nevertheless, we could also consider this group as multimodal, as  they compensate for their low bicycle use by a higher share of trips by bus or tram.

Their perceived car dependence is high, and it is conceivable they expect difficulties in the case of forced relinquishment of their car. They are more inclined to take the bus or tram than to ride a bicycle.  This group is lower educated, has the lowest average income of the four clusters. Higher age groups are overrepresented.

Car-independent cyclists (CIC)

As the name suggests, for the car-independent cyclists (CIC), the dominant mode of transport is the bicycle, and this is the group with the lowest perceived car dependence. This group is more multimodal than both motorists groups. Respondents from this group have a significantly higher propensity to travel by train or bus, although the percentages remain rather low, and for a majority, public transport is excluded from their travel mode set.

Compared to the sample average, respondents in CIC are more likely to have only one car in the household. Females and younger age groups are overrepresented here, as are couples with children. As far as education is concerned, we notice that the CIC are on average highly educated. The CIC tend to use a car primarily for leisure. This is a highly educated group, of all four the most willing to abandon a car if costs would increase drastically.

Car-dependent cyclists (CDC)

Finally, we turn to the car-dependent cyclists (CDC). As for the former cluster, the bicycle is the dominant mode choice. Nevertheless, 86.2% of this group travels by car at least once a week. Their perceived car dependence is equal to that of the CDMS. Use of public transport is more of an exception than a rule. With respect to socio-economics, most of the features of the CDC are close to that of the sample average, with two exceptions: highly educated respondents are overrepresented and households with children are underrepresented.

To summarize, the CDC is characterized by weekly car use, daily bicycle use, but a high perceived car dependence. They do not stand out socio-economically, although their high education is remarkable. This is the group most willing to start car sharing.

Discussion and conclusion

Firstly, the authors found that all clusters are to some extent multimodal.  In general, the research can conclude that, for our selected study area, car ownership does not necessarily induce perceived car-dependence for people who can easily get around by bicycle. Nevertheless, even in an urban setting and when exhibiting multimodal travel patterns, people can perceive their car as indispensable. Perceived car dependence is not necessarily correlated with high VKT or high frequency of car use, neither can this investigation conclude that multimodality necessarily  leads to less VKT. In this urbanized study area, at least for trips in the proximity of the dwelling to for instance services, people are willing to consider other modes than a car.

The four clusters reflect well-established correlations between travel behavior and socio economic characteristics. As income rises, it becomes more likely people undertake social and leisure trips. As far as education is concerned, we notice  that both groups of cyclists are highly educated.

As households with children are overrepresented in the car-independent cyclists group, and underrepresented in the car-dependent cyclists group, the results also illustrate that perceived car dependence goes not necessarily hand in hand with the presence of children.

Despite the presence of multimodality, the attachment to the car is strong.

This confirms the asymmetry Dargay discovered: once the household budget allows the purchase of a car,  people become accustomed to using it. When income drops (or in our case: a larger share of the  household budget needs to be transferred to maintaining the car), this does not necessarily lead to relinquishing the car. In that sense, financial incentives to reduce car use or to abandon the car risk not being very successful.

The car-independent cyclists are less dependent on a car for daily trips, and this might explain why their perceived car dependence is lower. For them, a car is more for convenience or to carry out flexible leisure trips.

Furthermore, the researchers find it remarkable that the willingness to start car sharing is limited in this group, as this could combine the convenience of a car with reduced costs.

Policy implications

An issue to address is whether policy attention should mainly focus on the groups with the highest likelihood of mode switching, like the car-independent cyclists, or should reducing VKT, crucial in the light of continuous increase of greenhouse emissions, be on top of the agenda. Of course, both are needed. The effectiveness of policy actions depends on the level of governance. The authors consider the local level more suited to politically intervene in straightforward measures like improving bicycle infrastructure and land use policies that strengthen proximity.

The results confirm that multimodality already prevails in urban areas, and that car owners display aspects of multimodal behavior, even when they travel by car frequently and they cover substantial VKT. As such, they are already experienced with sustainable modes like the bicycle or public transport. A stronger focus on making these modes more accessible could further reduce car use. In urban areas, to a certain extent, the bicycle is capable of replacing car trips in the proximity of the dwelling. However, the study stresses that older people, lower incomes and lower educated groups, are less inclined to cycle.

The research indicates that older people and lower incomes have the highest  propensity of using the bus or train. They could strongly benefit from an expansion of the network and higher frequencies. As higher VKT leads to higher greenhouse gas emissions, the authors think the train can have an important role, especially for leisure, with increased service provision during weekends and nighttime hours.

Measures that favor the bicycle and public transport, have to be combined with car-restrictive measurements.The car-dependent motorists group, a lower educated group with a lower income, are probably the most vulnerable to car restrictive financial  measures. They probably already reduce VKT as much as possible as a cost-saving strategy. Car-reducing regulations that rely on financial incentives, tend to disproportionately hit this group, while higher incomes can easily ‘buy their way out’. Policy should take these concerns into account.

Finally, policy makers should not consider multimodality as a goal in itself, as multimodality not necessarily leads to less VKT or less car use. The main goal needs to be reducing car ownership and car use and the implementation measures to reach that goal, taking into account equity concerns.

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