## 7 Commuters' Acceptance of the Multimodal Traffic Recommendation System
### Field Trials  
Motivated by the positive outcomes of the pilot study, we carried out two large-scale field trials to assess the effectiveness of our system in inducing sustainable travel behavior. To this end, we subjected the traffic management system to testing in two real environments, namely Nottingham (United Kingdom) and Sofia (Bulgaria). We started by recruiting participants who fulfill two criteria: (1) they live within the specified areas of the maps depicted in Figure 16; and (2) the participants usually commute to work by driving, cycling, walking, or public transport such as buses and trans. It is worth noting that the selected areas exhibit high traffic density and support the use of multiple modalities. Participants were recruited by distributing brochures and flyers in parking lots and metro stations, social media channels, two large SMS-campaigns, and emails targeting more than 10,000 users. The trials were executed in two consecutive phases; the first phase consisted of at least five whole trips, while the second phase consisted of at least ten whole trips. Essentially, each trip involves going from location (A) to location (B) and returning from (B) to (A). Therefore, the participating commuters were requested to specify their departure location (A), coinciding with their home, and arrival location (B), coinciding with their workplace, before starting the actual trial. The trials were designed to inspect how our system could result in an effective travel behavior change during the trial period. The commuting trips were made during the weekdays (Monday to Friday). Weekends were excluded from the trials to avoid collecting noisy data in the travel behavior. To keep our commuters motivated and engaged in the trials, we offered an incentive in return for their participation at the end of the experiments. Participants were requested to download our app, enable location tracking, input their routes, and record their daily journeys. At the end of the trials, participants were interviewed and asked to provide feedback about their commuting experience. All collected data were stored in a secured database and treated in strict confidentiality. We varied the trial scenarios to accommodate and test varying traffic demands. Our exemplary scenarios were as follows:  
* Scenario 1: commuters driving in a congested area within the city. * Scenario 2: drivers switching to green modes of transport. * Scenario 3: commuters mixing several modes of transportation. We were interested in investigating the below recommendations by our system, namely, alternative route planning, multimodal solutions, eco-friendly route guidance, real-time routing, and fast routing to avoid congestion. A total of 280 potential commuters registered to take part in our experiments. Only 92 (32.85%) of the applicants fulfilled our selection criteria (i.e., filled out all trip details and lived or worked within the test sites). Thirty participants were registered in the Nottingham area and 62 participants were registered in the Sofia area. The age of the trial users varied between 19 and 65 years. When asked about their favorite modes of transportation, Nottingham participants indicated that taking the bus (93%) and walking (87%) were their preferred commuting modes. Similarly, Sofia participants selected the metro (89%) and trans (73%) as their preferred modes of transportation, as depicted in Figure 17. The exact locations of our participants in the trial cities are depicted in Figure 18.  
Figure 16: Study areas and commuting corridors in (a) Nottingham (United Kingdom) and (b) Sofia (Bulgaria). The total number of trips made in the first phase amounted to 408 (i.e., 56 trips in Nottingham and 317 trips in Sofia), while the trips made in the second phase amounted to 588 (i.e., 70 trips in Nottingham and 476 in Sofia). Therefore, the number of trips tallied to 126 in Nottingham and 795 in Sofia.