Initiatives and challenges in using gamification in transportation: a systematic mapping

The main purpose of this article is to understand the latest view of gamification in the field of transportation. We aim to outline where and how gamification elements have been used in the field of transportation. This overview includes the main gamification elements that are used, in which research topic they are used, how to change traffic behavior to achieve sustainability by using them, what research methods are used, and the difficulties and challenges in implementing gamification.

This study has two objectives. First, we determine which gamification elements are used and why. Second, we determine which traffic research topics use gamification and how to change traffic behavior to achieve sustainability by using them. To better guide the research, the main objectives are mapped to specific research issues as follows:

RQ1.What gamification elements are used in the field of transportation?

RQ2.Which research topics of transportation adopt gamification?

RQ3.How does gamification change traffic behavior to achieve sustainability?

RQ4.What research methods are used?

RQ5.What are the difficulties and challenges in deploying gamification in transportation?

The literature search was carried out in the Web of Science (WOS) database. This database was selected because it is one of the most important sources of global academic information. It contains more than 18,000 of the most authoritative and influential academic journals in the world and contains many kinds of database resources. For the sake of rigor and clarity, it is better to search as few comprehensive databases as possible rather than searching in multiple databases [64]. In addition, compared with other databases, experts in this kind of analysis choose to analyse this database to present a greater amount of literature [61, 71, 74]. In addition, the database contains a large number of studies related to social sciences, i.e., knowledge fields related to gamification and transportation [21, 48].

When searching, we did narrow the time range of the search results because research on the use of gamification in the field of transportation began only recently, and any such restrictions might have resulted in overlooking relevant content. To construct the search string, we selected the main terms and synonyms found in previous known studies. After some preliminary tests, we decided to supplement the string with additional synonyms to make it as comprehensive as possible, as shown in Table 1. The search for literature in the WOS database was conducted using the search query: TITLE-ABS-KEY [(gamification OR gamifying OR gamify OR gamified OR funware OR “serious games”) AND (transportation OR traffic OR transit OR transport OR “urban mobility” OR “mobility behavior” OR “smart city” OR “urban accessibility”)].

This study excluded papers, programs, and book chapters that developed gamification in areas other than transportation or applied games to solving computing problems as well as those in the form of abstract only or a presentation. Table 2 summarizes the inclusion and exclusion criteria.

Table 3 summarizes the selection strategy and the following steps:

To answer the research questions listed in Sect. 3.1, we established six data extraction steps and classification schemes:

The literature search was conducted in April 2021. The search engine investigated was WOS. The search included the title, abstract and keywords of the research.

There were four main steps in the retrieval process, as shown in Fig. 1. In the first step, the search was applied to the database, and a total of 211 articles were retrieved. The second step was to delete the duplicate papers. The third step was to apply inclusion and exclusion criteria. We then read the title, keyword and abstract of each article and discarded game-related search results in other fields. In addition, due to the improper use of different terms, we discarded papers that had been incorrectly included, resulting in 66 papers. Finally, through full-text reading, we identified 30 major studies, as shown in Table 5. Works that applied game theory or showed mature games or serious games in non-transportation activities were discarded.

Figure 2 shows the distribution of major research on gamification in the field of transportation, divided by journals, conferences, workshops and book chapters. The earliest study was in 2015, which shows that the application of gamification in the field of transportation is a new problem. Figure 3 illustrates how the mapping of articles was distributed among these categories. It shows that the number of journals was the highest, followed by meetings, book chapters and workshops.

For the author's country/region, Table 6 shows that Australia had the largest number of published studies (4), followed by Spain (3) and the United Kingdom (3).

To answer this research question, we completed the search for each gamification element in the basic results. Table 7 shows the number of times each gamification element was applied as well as the relevant studies that applied it. Note that the calculation is based on explicit references in the study.

As shown in Table 7 and Fig. 4, the most common gamification elements are goals/challenges and points, followed by rewards. Next are the leaderboard and social engagement elements, which appeared 15 and 12 times, respectively.

Goals/challenges: Setting goals/challenges can effectively "attract" users to their desired behaviour according to the gamification goals and maintain users' interest and participation over time [S30]. Allowing users to set their own goals and indicators can have a substantial impact because when they challenge their chosen goals, they create a self-competitive environment that can lead to personal efforts and progress [S17]. With reasonable efforts to achieve self-set goals within a reasonable time frame, you can obtain a sense of satisfaction and achievement. For example, in [S3] [S20], the gamification application invites travellers to set their personal goals from five pre-set goal options ("reduce car use", "increase public transport", "reduce energy consumption", "increase slow travel" and "reduce carbon dioxide emissions").

Points: In a gamification application that encourages drivers to drive ecologically, the points are the environmental protection scores calculated according to the driving style of drivers on the way, and the scores encourage good driving behaviour [S7] [S20]. In a gamification application that changes the travel mode of travellers, points are obtained based on the travel distance and the sustainable level of the means of transportation used for each trip [S5] [S16] [S21] [S30]. Generally, the more sustainable the model is, the more points participants receive. In general, gamification applications allocate points proportionally as long as they detect the number of kilometres travelled by participants using sustainable vehicles. This means that participants who ride bicycles in their spare time while commuting to work by car will be rewarded with points. Such a point system may encourage participants to travel more just to earn more points. Instead, this eventually exacerbates rather than improves the impact of their liquidity [S17].

Rewards: When participants reach certain milestones, incentive measures for rewards can be tangible or intangible, can be expressed in money or in kind, and must be strictly related to individual performance. Rewarding participants who perform well can enhance the motivation of individuals to engage in a certain behaviour [S17]. For example, if the driver completes the task, he will receive a trophy [S15]. The top three users per week will receive monetary rewards [S15]. In addition to direct rewards, other rewards can be provided in a random manner to promote positive behaviour. For example, accidental positive rewards are occasionally obtained in a gaming environment [S20].

Leaderboards: Leaderboards rank the progress and achievements of users and other members similar to themselves to create a sense of competition [S21]. In relevant research on ecological driving gamification, drivers are ranked according to the ecological scores obtained during their travel. This ranking reflects the extent to which drivers are moving towards becoming high-performance drivers. In the study of changing travellers' travel behaviour, leaderboards provide individuals with the opportunity to compare their choices and performance with other people or groups they think are similar to themselves (such as members of the same community), which will generate peer pressure and imitation desire [S17]. The leaderboard is updated every week [S15], and users can view the points compared with other members or groups in the ranking system [S5].

Social engagement: The main motivation of social participation is to provide participants with a means of communication and share their experience and information with each other. Allowing participants to analyse their performance can improve their sense of achievement and trigger competition, help promote group behaviour and improve trust among users [S3]. The main form is team challenge, which realizes social contact and peer pressure by sharing information through social media [S21].

Rapid feedback: Quick feedback shows how close or how far participants are from reaching their goals [S2]. In ecological/safe driving research, to effectively stimulate users to behave in the desired manner, gamification applications should provide information so that users can evaluate their behaviour and raise their awareness of the possible negative effects [S20]. Feedback is essential not only to achieve the goals set but also to help participants stay engaged and make progress. In the study of changing travel patterns, personalized feedback on individual travel behaviour is provided. These aims are to provide comprehensive and practical evidence for travellers to improve their understanding of the impact of travel patterns. The metrics used usually include cost, time, distance and carbon footprint. This feature provides users with a way to monitor their behaviour. Suggestions can also be made to users according to their performance and by determining appropriate alternatives [S3].

Badges: In ecological/safe driving research, badges show achievements related to specific driving skill areas and show the progress made by each driver in their own and others' achievements [S20]. In the study of changing travel patterns, travellers will be rewarded with badges when they use a sustainable mode of transportation to achieve certain achievements [S30]. In addition, when the system detects specific sustainable transportation options, such as long-distance travel by bike or train every day for at least five consecutive days, the user will receive a surprise badge reward. This also has a guiding role. Spontaneous actions will receive unexpected rewards, which will make users aware of the positive actions they perform and stimulate them to repeat them in the future.

Levels: The driver or traveller needs to gradually increase the experience value to obtain the level [S3] [S20].

Personalization: In ecological/safe driving research, gamification mobile applications can easily record physiological, behavioural, environmental and vehicle parameters through sensors to form an ecological driving index and then provide personalized active tips to drivers to introduce how to adjust their current driving style to a more environmentally friendly driving style [S20]. In the study of changing traveller modes, the gamification mobile application designs personalized information based on the travel diary data provided by participants or the data obtained from surveys or interviews. It can also provide users with real-time information about the status of the transportation network, such as delay information. The information under these conditions can be combined with personal habitual travel to provide personalized information for each traveller [S3]. It can also introduce highly personalized weekly challenges. These challenges are designed to improve or maintain travellers' game performance by requiring users to achieve their goals (e.g., number of trips and kilometres travelled) through some form of transportation (e.g., cycling, walking, bus or train) [S30]. Such personalized units of playable content have a significant positive impact on user participation and retention.

Storyline/new identities: The elements of storyline/new identities greatly promote the importance of users' participation and subsequent impact on the environment and behaviour in stimulating users to explore the epic meaning call and boarding stage [S20]. When the storyline resonates with users, it can enhance the expected effect of their immersion and participation [S7].

Unlocking content: If upgrading involves accessing new content, users will have additional motivation to unlock new content through progress, such as advanced data analysis tools or decorative elements [S20].

Avatars: Avatars are provided to users by gamification mobile applications. This provides users with their own virtual version in the gamification platform. When they achieve certain goals in the application, they have the opportunity to upgrade their avatar according to its appearance or other functions. Avatar clothing can be traded with other users in the virtual community platform. Users can view the avatars of other users competing with them, which means that users want their avatars to be better than others [S20].

Progress bars: Clear and definite progress should be provided throughout the gamification stage. In the case of progress stagnation, users should be continuously encouraged to further participate by generating a sense of disappointment [S20].

Table 8 shows the research topics supported by gamification. It is worth noting that currently, changing travellers' travel behaviour is the most common gamification-supported topic (10 studies). The second improving driving behaviour (6 studies). Other transportation topics supported by gamification include encouraging bicycle commuting (4 studies), collecting transportation-related information (3 studies), supporting carpooling (2 studies), goods transportation (2 studies), identifying whether parking spaces are available (1 study), providing support for the development of gamification through a game survey of EV charging willingness (1 study) and data collection on road quality (1 study).

Figure 5 shows the relationship between gamification elements and transportation research topics. It shows how many studies refer to a particular element as support for a particular topic. It should be noted that the same element may have been reported in multiple studies, and multiple elements may have been mentioned in one study. Figure 5 provides evidence of the widespread use of goals/challenges and points as gamification elements and great support for research topics. In addition, it is worth noting that avatars, progress bars and time constraints have not been explored much. Therefore, Fig. 4 shows gamification elements that are widely or rarely explored in transportation research topics.

To answer RQ3, we determine the direct and indirect changes of using gamification. The results are classified and summarized in Table 9 by topic, revenue from gamification, and reported revenue.

The main contribution of changing travel behaviour is realizing the changed behaviour. For example, [S3] found that travellers change their travel time to avoid peak hours and travel modes and turn to sustainable bicycle travel. [S12] indicated that gamification encourages more sustainable modes of transportation. [S16] found that travellers use more public transportation and walking. The second advantage is reducing carbon dioxide emissions and energy consumption. The third advantage is reducing the dependence on cars and the use of cars.

The main effort of improving driving behaviour is promoting safe driving. [S1] indicated that gamification can be a powerful auxiliary tool for safe and efficient driving. [S4] found that gamification improves the risk perception ability of elderly drivers and promotes safe driving. [S7] indicated that gamification encourages safe driving, driving speed is significantly reduced, and deceleration is earlier and more stable. [S8] found that safe driving helps drivers maintain attention and remain alert throughout the journey. The second advantages are reducing energy consumption and carbon dioxide emissions, making driving more enjoyable, and reducing boredom while driving. The third advantage is improving drivers’ skills and interest in fuel saving.

The main contribution of encouraging bicycle commuting is promoting bicycle commuting. The second advantage is making cycling more enjoyable.

Regarding collecting traffic-related information, [S2] collected public transport information, [S19] collected road traffic information, and [S28] collected accessible information on public transportation infrastructure. The greatest contribution of gamification to these studies is improving users’ participation and the usability of software. The second advantage is improving users’ trust in software and information.

Regarding supporting carpooling activities, the main contributions are reducing traffic congestion, reducing fuel consumption, and reducing carbon dioxide emissions. The second advantage is reducing the number of cars on the road and increase participation.

Regarding cargo transportation activities, the main contributions are reducing fuel consumption, reducing carbon dioxide emissions, reducing the number of kilometres travelled, and reducing logistics costs. The second advantage is improving the quality of service.

Regarding identifying whether a parking space is available, the main change is that it saves the time and money spent finding a parking space, reduces the number of kilometres driven to find a parking space, and correspondingly reduces the emissions of carbon dioxide without requiring a great investment in sensors and other equipment.

Regarding the game survey of electric vehicle charging intention, the main contribution is making the gamified survey more attractive, thus improving the response rate and the quality of enjoyment.

Regarding road quality data, the main change is that gamification improves participation and provides open data for traffic and road conditions.

Table 10 shows the distribution of study types. We noticed that evaluation research and solution proposals were the most popular types of research, with 9 studies each, accounting for 60% of the selected studies. These two categories represent studies at an earlier stage, which may reflect the short time that gamification has been used in the field of transportation, and some studies are still in the exploratory stage and immature. The other 12 studies were distributed among philosophical papers (4), validation research (3), experience papers (3) and opinion papers (2).

Table 11 shows the distribution of research methods. Nearly half of the studies used experimental research methods, and 13 studies used survey methods. It is worth noting that [S3], [S6], [S8], [S17] and [S27] used both experimental and investigative methods. [13] used both case study and survey methods.

As shown in Table 10, a large number of studies are classified as evaluation research and solution proposals. Table 11 shows that a large number of studies used experimental and survey methods. This shows that most of the selected studies were in the early stage of exploration; thus, they inevitably encountered various difficulties and challenges in the implementation of gamification.

The difficulties and challenges in implementing gamification in these selected studies are listed in Table 12. As the table shows, one of the main challenges for these studies was how to design attractive applications. Ten studies commented that it was not easy. [S17] pointed out that the design should be ingenious and user centred. [S30] noted that the design should be convincing.

Another major difficulty was recruiting and retaining users. All 10 studies encountered the problem of insufficient recruitment. [S14] indicated that participation would consume users' resources, such as mobile phone batteries and computing power, which is one of the main obstacles that makes many users reluctant to participate. Therefore, an incentive mechanism is needed to ensure the participation of users. However, eight studies indicated that offering an effective incentive for users is a challenge. [S18] and [S21] pointed out that it is very important to motivate users to achieve the predetermined goal, and the gamification rule with monetary rewards plays an important role.

One of the goals of these application programs is always to make the design of the interface as simple and easy to use as possible. Eight studies pointed out that simplifying the interface design and making the application as simple as possible are very important.

Seven studies suggested that an important issue in implementation is the challenge of personalization, that is, tailoring an application to the personal data of each participant. [S30] proposed an automatic generation of a personalized challenge method. Although automation has always been the goal, it is not easy to build different automation methods according to different situations.

The accuracy and reliability of information and feedback information are also among the most important difficulties. [S1] pointed out that it is very important to provide correct feedback to the driver, as gamification could otherwise have a negative impact on driving. [S20] pointed out that providing correct information can enable users to evaluate their own behaviour and can effectively motivate them to engage in the expected behaviour. [S17] pointed out that the provision of information should avoid numbers because users prefer graphical and visual information.

Six studies pointed out that the experimental time was limited and the observation time was too short. Four studies on driver behavioural improve noted that reducing interruptions and distractions is a problem. [S1] and [S11] pointed out that gamification should produce as little disturbance as possible to avoid distracting the driver. [S7] pointed out that the trade-off between environmental information and driver distraction should be considered to avoid excessive dispersion of vision, and the form of sound should be considered. [S8] commented that attention should be paid to the position of the screen, which may affect visual attention. Two studies on driver behavioural improve also noted that high cognitive load should be avoided.

Three studies mentioned privacy issues. Two studies pointed out the problem of data collection. [S7] noted that the data were self-reported by participants, which was not objective enough. It is necessary to collect objective data, such as physiological and driving performance information. [S16] commented that carefully tracking people's travel and conducting an in-depth investigation of their attitudes and behaviours are arduous tasks.

Finally, it is also a challenge to categorize players. [S10] pointed out that attention should be paid to the classification of players, which must be weighted and standardized in various categories. Integrating data with gamification is also a major challenge.

Therefore, based on the results summarized in Table 13, we re-examine RQ5 and conclude that there are still many difficulties and challenges in the implementation of gamification. The results of this study can provide a reference for other gamification studies.

Driving style directly affects the fuel consumption of the vehicle. Drivers that drive without exceeding the speed limit, decelerate/accelerate smoothly, change gears appropriately and maintain a relatively constant speed, representing an efficient driving mode, can save up to 25% of fuel, reduce greenhouse gas emissions, improve comfort and reduce the risk and severity of accidents.

Therefore, improving driving skills is a promising way to explore gamification driving. It can maintain a sense of challenge by providing different gamified themes and various difficulty levels, competing with other users or proposing new driving challenges. Driving challenges can be designed around driving smoothly to maximize passenger comfort, solving the mileage anxiety of electric vehicles around efficient driving, improving the situational awareness of semiautomatic driving or maintaining the skills of drivers because vehicle automation may have adverse effects.

When testing gamified themes, we recommend evaluating user preferences to establish potential matches and mismatches. Gamification elements can be applied with various themes, so custom personalized themes may be an option.

Gamified driving can be activated by certain elements in the road environment. For example, a speed sign or a set of traffic lights can activate a gamified driving task. These interventions can add additional participation based on a continuous feedback cycle.

When the vehicle is not moving, driving challenges or feedback can be displayed before or after driving. For example, ask about a challenge at the beginning of driving ("try to use less than x fuel when driving to work today"), and the challenge mainly occurs on the road. Detailed feedback can be provided after the trip, and leaderboards or similar statistics can be displayed so that users can evaluate their behaviour and raise their awareness of possible negative effects.

To avoid excessive visual dispersion during driver challenges, a trade-off should be made between providing environmental information and driver distraction. Information should be nonintrusive and can be achieved through abstract information visualization, which skillfully conveys information through simple colour, brightness or sound. For example, environmental red may reflect speeding violations, which can reduce cognitive load.

Drivers themselves can be a source of social entertainment. The application may target other road users to reward achievements, allow social expression, allow accidental encounters or promote a shared road travel experience. Users who drive gamification can compete with each other and compare their progress on the leaderboard.

The main objective of many cities and transport authorities is not only to operate effective public transport services and effectively manage transport infrastructure but also, more strategically, encourage millions of their users to travel more effectively and sustainably in cities. More specific goals are usually to reduce the use of private cars in cities and to promote greater absorption of public transport use and human powered travel, such as walking or cycling, by providing appropriate incentives for travellers. An effective incentive measure is to encourage individual travellers to change their travel behaviour to achieve the overall goal, that is, to reduce the use of cars during peak commuting hours, protect the environment and promote people's well-being by reducing air pollution emissions.

Changing people's travel behaviour can be a difficult task, especially when there are many factors affecting people's behaviour. Therefore, we should consider the combination of the four stages of change and gamification to promote changes in people's travel behaviour. The first stage is the pre-consideration stage, in which users have no motivation to reduce car use and do not intend to take any action to change their daily travel mode. Gamification applications track the mobility data of users and provide users with automatic feedback on each route they travel, including distance, time, energy consumption and carbon dioxide emissions. In the second stage, the thinking stage, the above feedback is expected to improve users' understanding of the advantages and disadvantages of changing their behaviour to encourage them to establish the intention of change in the near future. By always choosing the feasible alternative route with the lowest CO2 emissions on the route, we summarize how they move to stimulate their feedback, that is, the available low-carbon alternative route for any system route they take and its overall "transformation potential". The third stage, the preparation stage, encourages users to set their own personalized goals and challenges and urges them to move forward freely according to their own pace and direction to achieve their own reform goals. The fourth stage, the operation and maintenance stage, helps users achieve their goals and encourages them to put sustainable travel modes into practice. Effective points, rewards and badges will drive users to implement their action plans. Note that monetary incentives are more likely to promote car sharing, park and ride, rather than monetary incentives, are more likely to promote alternatives related to public transport. The level of reward will affect individual behaviour changes. For example, with age, the higher the reward is, the stronger the behavioural change towards promoting sustainable travel patterns [16].

Social participation and peer influence can be used to change people's travel behaviour. Therefore, social networks and leaderboards can encourage sharing, comparisons and competition with others, which is usually considered to be an effective way to increase the driving force of change. Social networks seem to be a very useful medium for people to exchange skills and experiences.

It is suggested that future gamification applications should better follow the process of behaviour change by publishing application functions in stages.

Cycling gamification applications aimed at promoting cycling among urban residents are encouraged. They focus on promoting and motivating self-regulated behaviour change by providing a variety of planning tools, feedback, rewards and experience sharing. Their main functions include bicycle route planning and route tracking linked to badges, challenges and rewards and community experience sharing systems. Commuting to work (or school) every day is the main choice of this intervention. This can not only improve people's health but also improve the liveability of cities by reducing car use and ownership.

It is suggested to provide in kind rewards and a small amount of money to promote cycling. The study found that by linking online stores with physical rewards, people may be more interested in physical rewards than monetary rewards because physical rewards may make users feel more enjoyable and make users more satisfied [37, 70]. Some studies have also found that providing a small amount of money as a reward for users who ride bicycles to work (or school) every day can effectively encourage people to significantly increase the frequency of cycling [S27]. Although rewards can maintain the change of behaviour throughout the activity process, it is still an unknown question whether this change can continue in the long run [10].

Adopting the gamification elements of social participation is suggested. The study found that in urban environments, cyclists are less willing to compete and more willing to participate or interact. Gamification designers should create narrative links, a sense of community belonging, and a desire to participate in policy-making or have a better city, and motivation should be linked to the feelings of play, entertainment, comfort, well-being, freedom, social and interpersonal communication related to cycling.

Gamification elements of the goals are not recommended. Current bicycle promotion applications usually reward users by directly calculating the mileage of users riding bicycles. The use of goals elements often encourages people to make redundant trips to obtain more rewards, which goes against the original intention of bicycles as an alternative means of transportation for cars. Some studies have also found that setting specific goals for long-term projects may not be conducive to user participation because users will launch them immediately after completing the goals [32].

It is worth noting that some studies, especially those related to cycling promotion, are missing in the retrieval because they do not use the term gamification but use reward or incentive strategies in gamification. For example, Huang et al. [38] used mobile phone app to provide monthly cycling-related challenges for more than 6000 travellers in the Dutch region of Twente, and provided incentives such as point rewards and feedback information. This study analysed the travel behaviour tracked by mobile phone app in a real environment for more than a year and explored the impact of positive incentives on short-term and long-term travel behaviour changes. The results show that the challenge does encourage cycling and reduce car use in the short term. There is also some evidence that these interventions are effective for some long-term behaviour changes. However, due to the small sample size, it is impossible to draw a clear conclusion. At the same time, the paper lists mobile application projects and research examples that encourage voluntary travel behaviour change. The paper by de Kruijf et al. [25] reported the impact of the e-cycling incentive program in the province of North-Brabant, the Netherlands, on travel satisfaction. The program provides a small amount of monetary incentives for e-cycling participants per kilometre, aiming to stimulate car commuters to use e-cycling in their daily commuting. Through a longitudinal design, this study observed changes in travel behaviour and satisfaction. The study found that e-cycling travel satisfaction remained at a high level for up to six months, especially for people who often use e-cycling to work. After one month and six months, travel satisfaction greatly improved.