1. Introduction
China is prospecting a larger proportion of elderly people in the total population, and this trend is expected to increase in coming years, which has brought a challenge to society. The travel problem related to the quality of life for the elderly has especially attracted researchers [
1]. Traffic travel behavior is the fundamental guarantee for the elderly to maintain their daily activities. The physical condition of the elderly and the current traffic modes have become obstacles to their travel activities. The regulations concerning drivers stipulated that older people over 70 years cannot apply for a license before 2020. Some elderly people report problems such as “squeeze, unstable, and not to come” on the bus, which weakens their mobility. Mobility is closely related to the physical condition and quality of life of the elderly [
2,
3] and promotes society’s overall development [
4].
Hu et al. found that an average of 80% of the elderly in China prefer to use walk and public transport, which would increase more than 90% with age, while only less than 3% choose driving [
5]. On the contrary, older travelers are almost 90% car-oriented, with low public transport usage levels, less than 2% in North America [
6]. That indicates there are enormous different travel patterns for the elderly between China and North America. Therefore, we excluded the mode of driving in this study. However, with Chinese economic development and increased individual income, more people are accustomed to driving. In 2020, the Chinese elderly, more than 70 years old, could still apply for their license if they have a good physical condition. We could anticipate that the percent of the elderly choosing to drive a car will increase shortly in China. Therefore, the exclusion of driving from the elderly’s travel mode choice set is the limitation of this study. We will introduce the driving option in our future research as a benchmark.
The effect of Autonomous Vehicles (AVs, we listed all the Glossary) on the transport system, such as travel behavior, traffic safety, and congestion, has been much discussed in the past half-decade [
7]. Harper et al. proposed that the emergence of AVs and Shared Autonomous Vehicles (SAVs) will provide more choices for the elderly, enhance their travel convenience and mobility [
8]. AVs will replace traditional cars and become an emerging travel choice, bringing the ultimate experience of comfort, safety, and convenience to travelers in the future. AVs are faster and can improve road capacity and alleviate urban traffic congestion; they are more environmentally-friendly and can improve fuel efficiency and reduce exhaust pollution [
9]. At the same time, Nuzzolo et al. found AVs could provide an opportunity to reduce air pollution in the cities’ central areas [
10]. Tan et al. also demonstrated the driverless cars’ potential implications on sustainable tourism [
11]. Liu et al. reported that the public would intend to accept AVs’ risk when AVs are more environmentally-friendly [
12]. The integration of AVs and “shared travel” will be realized with the development of autonomous driving technology and the sharing economy. Experts predict that SAVs will also become an emerging travel mode, which will replace traditional taxis and net cars in the future [
13].
However, whether AVs or SAVs may take a long time from the current development stage to mature promotion and full popularity stage. Technology developments should be accompanied by researching individuals’ habits and consumption motivations in the population [
14]. When the technology becomes mature, the implementation of legislation and social mentality adjustment should be solved to enable travelers to enjoy safe, comfortable, and free travel on their own [
15]. For the elderly, the emergence of AVs and SAVs is indeed a boon to meeting the need for independent travel, but the ability to accept and adapt to new things is still unknown, the long-term use of buses will not change immediately. Levin and Stephen proposed that AVs and SAVs will coexist with public transport for a long time in the future transportation system [
16]. To our best knowledge, there are few literatures concerning AVs’ impact on the elderly’s mode choice behavior, which is essential for the elderly’s later life quality in the future. Therefore, it is meaningful to investigate the elderly’s mode choice between public transport, AVs, and SAVs.
In recent years, the ecological model has been gradually applied to the elderly’s travel behavior. Hough, Cao, and Handy proved the ecological model’s applicability in the elderly’s travel behavior [
17]. Mifsud, Attard, and Ison found that three types of independent variables in the ecological model: personal factors, social factors, and environmental factors affect older people’s travel behaviors [
18]. Several articles indicated that the ecological model has the explanation strength in the elderly’s travel behaviors. However, researchers have focused on the impact of observable variables without further considering their psychological state. In particular, observable variables may not be sufficient to predict future older populations’ travel mode choice behavior, given their escalating physical and mental level demands in modern society. Therefore, one of the major gaps in the elderly’s travel behaviors is the lack of psychological variables in applying the ecological model. In this study, an extended ecological model involving psychological variables and travel attributes was proposed to comprehensively analyze the elderly’s mode choice behavior.
Furthermore, elders’ travel modes vary due to the differences between individual countries regarding social systems and cultural backgrounds. To our knowledge, significant development and experiments of the ecological model about the elderly’s travel behaviors have been obtained in developed countries, including travel behavior of older women in the USA [
13], public transport use among older adults in Australia [
19], and the elderly’s mode choice between cars and buses in Malta [
18]. However, the study of the elderly’s travel behavior through ecological modeis rarely conducted, leading to another gap in this field.
The majority of current research into the elderly’s travel behavior was realized by examining travel mode choices related to buses, walking, cycling, and cars. As a forthcoming advanced transport, autonomous driving technology would provide great convenience to the elderly or disabled [
8]. The authors also proposed that AVs and SAVs could be used as an alternative to traditional cars, and eventually become one of the most dominating mode choices among older adults. Surprisingly, AVs and SAVs were very few in the elderly travel mode choices domain.
Overall, this study attended to supplement research on elderly travel behavior. It may be the first to take the Chinese elderly as the research object and put forward an extended ecological model to explore their mode choices among public transport, AVs, and SAVs.
The objective of this study includes: (1) exploring the adaptability and application of the extended ecological model in the elderly’s mode choice behavior in the future; (2) making a deeper understanding of the elderly’s attitude towards the AVs and SAVs, and discovering the mechanism concerning the relationship among constructs affecting travel mode choice behavior; (3) proposing suggestions for manufacturers to develop AVs and SAVs to serve for the elderly’s travel need and providing support for the government to introduce policies and measures to promote the application of AVs and SAVs in the market. We found that the elderly believe that public transport, AVs, and SAVs are useful and convenient travel modes for themselves, affecting intention significantly. In addition, the elderly’s well-being and social influence during travel are also significant constructs for their mode choice intention.
The remainder of this paper proceeds as follows.
Section 2 reviews the background;
Section 3 illustrates the extended ecological model;
Section 4 presents the data survey and models, and
Section 5 describes the results and discussions. Finally,
Section 6 reveals the limitation and conclusion.
6. Limitations and Conclusions
Some limitations need to be resolved in our future work. Firstly, we analyze the elderly’s mode choice behavior among three modes: public transport, AVs, and SAVs. Although less than 3% of the elderly in China drive [
5], we could predict that the percentage of driving for the elderly would increase sharply due to the elderly’ license with no age limitation and growth in the living standard. Therefore, we will introduce driving into our research and explore the potential constructs affecting the elderly’s driving behavior in the future study. Secondly, most participants did not ride AVs and had no field experience with AVs’ benefits or drawbacks. The participants’ knowledge concerning AVs from the internet and other channels may mislead their perspectives or attitudes. In our future research, we will use a video or AVs’ simulator to make the participants have a more real feeling for AVs. Thirdly, the research sample comes from Suzhou survey data, and the result may not be generalizable to the entire population. We may pay attention to the difference among various regions for the elderly’s travel behavior.
Based on the elderly’s travel needs and the extended ecological model, we analyze the mode choice behaviors of the elderly towards public transport, AVs, and SAVs in the future. The research conclusions are as follows:
(1) We integrate the relevant factors that affect the travel of the elderly and expand the ecological model by introducing the constructs, which provide a theoretical framework for the elderly. Moreover, we analyze the modeling results of empirical data and verify the theoretical framework’s applicability to the elderly’s travel behavior.
(2) The MIMIC model is used to analyze the relationship between the extended latent variables and the original observed variables of the ecological model. We can see that the observed variables have different degrees of influence on the constructs in the MIMIC model for public transport, AVs, and SAVs. The interaction and internal mechanism of expanded constructs were analyzed with the MIMIC model. Seven hypotheses proposed in this paper were proved to understand the elderly’s travel psychology.
(3) Through the analysis and discussion of relevant influencing factors, we can have a deeper understanding of the views and acceptability of the elderly towards AVs and SAVs. Given the psychological characteristics and elderly’s behaviors, enterprises can develop corresponding AVs to better meet and serve the travel needs in the future.
We also proposed practical suggestions according to our research results.
(1) We suggest that the local government could make policies or measures to create a good living environment and safeguard the elderly’s physical health, which significantly influences their attitude towards AVs and SAVs. In other words, policies concerning the elderly’s physical health have a potential opportunity to increase their acceptance of AVs and SAVs.
(2) SWB has a significant positive correlation with BI. We advise enterprises to install an entertainment system with a large screen, making the elderly enjoy leisure and happiness, which could improve their SWB during the travel in AVs and SAVs.
(3) Travel variability time is significantly correlated with the travel behavior of the elderly. To improve travel time reliability and decrease the elderly’s travel variability time, we suggested that the public transport agencies could improve bus system efficiency, such as optimizing bus routes net, increasing departure frequency, and reducing waiting time.
(4) In our study, PU refers to the degree to which the elderly believe that using a transport mode would enhance their travel performance. Meanwhile, PE indicates the degree to which the elderly believe that using public transport, AVs, and SAVs would be free of physical and mental effort. The study results show that PU and PE significantly impact attitude for the three travel modes, and PU influences BI significantly for SAVs. To accelerate the extensive application of AVs and SAVs for the elderly, the enterprises could install a small slide and provide enough space to help disabled elderly get on or off to improve their PU and PE.