Bicycle Use Research Articles

Understanding children's cycling route selection through spatial trajectory data mining

A sustainable alternative transportation mode to address growing transportation and environmental stress is cycling, which is eco-friendly and healthy for humans. Improving the quality of the bicycling experience is crucial for increasing bicycle use. Good bicycling experience is more critical for child bicyclists because they are less experienced and need more space for error. Therefore, a scientific assessment of child bicyclist perception of selected route safety, comfort, and environment is of great interest. Finding an effective way to learn child bicyclist behavior and help them reduce cycling risk is necessary. In response to this need, we utilize a data mining model to develop a methodology for measuring children's bicycling route safety conditions by evaluating multiple road safety-related features. The proposed method uses a set of route features representing the situation of street environments extracted from state data and first-hand children’s bicycle trajectory data collected using Global Positioning Systems (GPS) from volunteer children bicyclists. A random forest (RF), a well-known classifier, is adopted to predict child bicyclists' behavior. We extract the different route segments between children’s selected routes and the shortest path to learn the child bicyclists' behavior and use the selected best features to interpret their changing cycling behavior. The result shows that children bicyclists' behavior could be analyzed by giving trajectory and nearby road safety situation data. Our model achieves a promising accuracy with an average rate of 92% over multiple scenarios, demonstrating the proposed method's feasibility and the effectiveness of selected features. In addition, we compare our feature effectiveness with the state's generated road safety score data to evaluate the feature robustness. Our features outperform the safety score feature with an average of 10% improvement in prediction accuracy. Furthermore, our method proposes a model framework that can be applied to different study regions and adult bicycling behavior learning.

Exploring cyclists’ travel behaviour in different attitudinal market segments: case study of Quelimane, Mozambique

ABSTRACT Distinguishing bicycle market segments is relevant to promote bicycle use, as customised policy strategies can be targeted to each submarket. This paper aims to adopt the attitudinal market segmentation approach to identify potential markets of bicycle commuters and their travel behaviour differences. A survey was conducted among 902 commuters in Quelimane, Mozambique. Factor analysis is used to identify key latent factors. Two-step cluster analysis is used to segment the bicycle commuting market into several submarkets. Then, Mann-Whitney U test is used to compare pairs of segments based on a set of travel behaviour factors such as cycling frequency, travel time and commuting mode. Three segments are obtained: Reluctant cyclists (S1), Livelihood cyclists (S2), and Demanding cyclists (S3). The study reveals that S1 cycle less frequently when compared to S2 and S3. S1 can be motivated to cycle more frequently by promoting educational campaigns to increase their perception towards cycling benefits. S1 and S3 commute long hours when compared to S2, thus, promoting distribution of land-use activities to reduce travel distance could motivate bicycle use. S1 frequently walk commute compared to S2 and S3, therefore policies to increase bicycle use were pointed to making bicycles more accessible to Reluctant cyclists.

The complexity of changes in modal choice: A quasi-experimental study

BackgroundChanges in modal choice is argued to be one way to reduce the emission of greenhouse gases. Increasing modal choices in favour of more environmentally friendly travel modes requires a better understanding of how these choices are actually made. The first aim of this study is therefore to examine how modal choice is related to subjective experiences as perceived accessibility, perceived satisfaction, and habit, both before and after an intervention promoting public transport. The second aim is to examine how modal choice is affected by the intervention. Finally, the third aim is to examine how subjective experiences as perceived accessibility, perceived satisfaction, and habit are affected by the intervention. MethodThe design used is a before- and after-study with free public travel passes as the intervention (30- or 14-days free travel pass). Altogether, 52 travelers – distributed on two intervention groups and one control group – participated in the study. The 30-days free travel pass group constitutes 18 participants, the 14-days free travel pass group constitutes 19 participants while the control group constitutes 15 participants. During the before-period the participants were asked to register their modal choice using a digitalized application downloaded on their smart phones (the TravelVu app), to complete a short app-based questionnaire, and a web-based questionnaire. During the after-period, they were once again asked to register their modal choice and to complete a web-based questionnaire. All data collected were analyzed by variance or correlation analyses using the change between before- and after period as the dependent variable. ResultsThe results show that walking was more common than the use of public transport and car, which in turn were more common than the use of bicycle. Perceived accessibility, perceived satisfaction, general health, life quality as well as habit were all rated fairly high. Over time, the use of public transport increased while the use of car decreased overall. With increased use of public transport, the perceived accessibility decreased, but on the other hand, the life quality increased. There was no difference in perceived accessibility, perceived satisfaction, or habit between the three groups, but the participants became overall more satisfied with the standard of their experiences of their everyday travel (cognitive evaluation). At the same time, they became less reflective of their choice of travel mode and less interested in trying out new alternative travel modes during the after- compared to the before period. ConclusionThe intervention did not affect the modal choice or the subjective experiences. Over time, the participants did however increase their use of public transport and their cognitive evaluation of their everyday travel overall, while they decreased their use of car and became less reflective and less interested in trying out new alternative travel modes. These changes might be attributed to their participation in the present study.

Active commuting and the health of workers

IntroductionResearch has shown that commuting is related to the health of workers, and that mode choice may have a range of effects on this relationship. We analyze the relationship between active commuting (walking and cycling) and the health status reported by US workers. MethodsWe use the 2014–2016 Eating and Health (EH) Module of the American Time Use Survey (ATUS). We estimate Ordinary Least Squares models on a measure of subjective health that is the self-reported assessment of individual general health status, and on the body mass index. Resultslonger commutes by bicycle are significantly related to higher levels of subjective health and to lower body mass index, while commuting by walking is only weakly related to both health measures. We test the robustness of our results to possible measurement error in commuting times, to the exclusion of compensating factors, to the estimation method, and to the inclusion of time devoted to leisure-based physical activities. ConclusionsOur results may help policy makers in evaluating the importance of infrastructures that facilitate the use of bicycles as a means of transport, boosting investment in these infrastructures, especially in larger cities.

Bicycle Sharing Travel Characteristics Analysis

The emergence of bicycle sharing has greatly impacted the urban transportation structure and residents' travel modes. The massive spatial-temporal data carried by it is of great significance for studying the characteristics of residents' slow travel and guiding the development of green transportation in cities. Through the analysis of Xiamen's bicycle sharing order data, this paper analyzes the riding characteristics of users and explores the urban functional elements that affect the use of bicycle sharing. This paper will use urban bicycle sharing data, Point of Interest (POI) data in internet maps, and population distribution data to carry out mining and analysis on the travel characteristics and spatial distribution features of bicycle sharing.

Lessons learned from evaluating complete streets project outcomes with emerging data sources

ABSTRACT Complete Streets projects can bring multifaceted benefits but before-and-after analysis regarding their mobility and accessibility outcomes is quite limited in practice. This study used emerging data sources to conduct longitudinal project outcome evaluations. Two projects from Louisiana were selected as case studies for demonstration. The two projects did not induce heavier congestion in a pilot analysis region. One project with sidewalks/bike lanes contributes to traffic calming in an urban context, while the other project consisting only of a widened shoulder marked for bicycle use may raise speeding concerns in a rural context. Both projects are likely to bring accessibility benefits as they attract more businesses and longer visits. The authors also noted data source and outcome measure challenges in different contexts. The proposed evaluation approach and identified data gaps will benefit the private sector in diversifying/improving their data products and facilitate the public sector in making more data-driven decisions.

Attitudinal Factors Associated with the Use of Bicycles and Electric Scooters

The use of personal mobility vehicles (PMVs) has increased, given the consumption characteristics of the population as well as the impact on the environment that other means of transport generate. In this work, the attitudinal factors associated with the use of PMVs are identified, making use of the theory of planned behaviour and a modified technological acceptance model. For the collection of information, a sample of 457 individuals was used. For the analysis of this information, a structural equation model was generated through SmartPLS 4. The results reveal that of the attitudinal factors associated with the use of these vehicles, green attitudes, perceived green value and loyalty stand out, with the latter being one of the latent predictive variables of the model, which is why feelings of enjoyment, usefulness generated and a perception of caring for the environment by PMV users have a greater influence on their loyalty to this type of green technology.

It’s snowing? Keep on rolling! Individual determinants of winter cycling in Québec

Bicycle commuting during the winter is an increasingly popular practice in Québec, Canada, that is associated with benefits for public and environmental health. Constructs of the Theory of Planned Behavior and habit are associated with modes of transport and active commuting. Researchers have not yet examined whether these psychological factors are associated with winter cycling in nordic climates. The aims of the study were to describe winter bicycle users’ socio-demographic and psychological characteristics as well as perceptions of environment and assess whether the Theory of Planned Behavior and habit constructs are longitudinally associated with winter bicycle commuting. A longitudinal design with two online questionnaires was implemented between January-March 2022. The first questionnaire assessed individual variables. Four weeks later, a second questionnaire collected data on the use of winter bicycle commuting in the last seven days. A structural equation model was performed to examine longitudinal associations between psychological constructs and weekly winter cycling. The study included 624 and 487 participants at baseline and follow-up, respectively. Participants mainly identified as men (60%) and mean age was 44 years old. Our results demonstrated that attitudes (β= 0.21; 95%CI [0.06, 0.36]), perceived control (β= 0.92; 95%CI [0.61, 1.12]), intention (β= 0.53; 95%CI [0.39, 0.66]), and habit (β= 1.12; 95%CI [0.60, 1.65]) exhibited significant positive associations with engaging in bicycle commuting during winter. The level of habit had a stronger association with behavior than intention. Findings suggest that future winter cycling intervention should combine behavioral change techniques (targeting attitudes, perceived control, intention, and habit) with winter bicycle-friendly infrastructures and policies.p { margin-bottom: 0.25cm; direction: ltr; color: #000000; line-height: 115%; text-align: left; orphans: 2; widows: 2; background: transparent }p.western { font-family: "Calibri", sans-serif; font-size: 11pt; so-language: fr-CA }p.cjk { font-family: "Calibri"; font-size: 11pt; so-language: en-US }p.ctl { font-family: "Times New Roman"; font-size: 11pt; so-language: ar-SA }a:visited { color: #954f72; text-decoration: underline }a:link { color: #0563c1; text-decoration: underline }

Advanced Smartphone-Based Identification of Transport Modes: Resilience under GNSS-Based Attacks

One of the main challenges for ticketing in Mobility as a Service is the integration of the public and individual transport modes into a unified ticketing service. To realize this concept, a trustworthy identification of transport modes that is resilient to possible attacks is required. In this work, we propose two smartphone-based methods to seamlessly identify the use of trams, buses, subways, walking and bicycles, which are able to detect GNSS-based attacks and continue to provide a trustworthy identification of transport modes. We have recorded real-world measurements with commercial smartphones using the transport network in Munich and Paris. Our results show that it is possible to provide trustworthy identification of transport modes even when the system is under attack. In conclusion, in this work we demonstrate the vulnerability of smartphone-based ticketing to GNSS-based attacks, propose two methods to overcome this vulnerability and demonstrate the validity of our methods with real-world measurements.

Identifying foci for safety messages targeting child injury from driving quad bikes: A critical beliefs analysis of parental beliefs in Australia

Introduction: In Australia, between 2017–2021, 16% of quad bike fatalities involved children. Trauma statistics highlight that public awareness of the risks associated with children driving quads is required. Consistent with the Step approach to Message Design and Testing (SatMDT) and, in particular, Steps 1 and 2, this study sought to identify critical beliefs influencing parental intentions to allow their children to drive a quad bike and develop message content. The critical beliefs analysis was based on eliciting the Theory of Planned Behavior’s (TPB) behavioral, normative, and control beliefs. Methods: An online survey was distributed via parenting blogs, social media posts, and snowballing of the researchers’ network list. Parents who participated (N = 71; 53F, 18 M), were aged between 25–57 years (M = 40.96, SD = 6.98), had at least one child aged between 3 to 16 years, and currently resided in Australia. Results: The critical beliefs analysis identified four critical beliefs that significantly predicted parental intentions to allow their child to drive a quad bike. These beliefs included a behavioral belief (the perceived advantage that allowing their child to drive a quad bike would enable tasks to be completed), two normative beliefs (the perception that one’s parents and partner would likely approve of allowing their child to drive a quad bike), and one control belief (a perceived barrier to allowing one’s child to drive a quad that was associated with being aware of an increasing cultural concern around the safety of quad bikes). Conclusions: Findings contribute to insights regarding parental beliefs underpinning their intention to allow their child to drive a quad bike, an area previously lacking in research evidence. Practical applications: With child-use posing a high-risk activity for children, this study provides an important contribution that may help to inform future safety messaging targeting children’s use of quad bikes.

E-scooter use continues to rev up fracture diagnoses and hospital admissions compared to other modes of transportation

IntroductionThe COVID-19 pandemic was associated with an increase in popularity of e-scooter usage and a rise in e-scooter related injuries. Recent studies have elucidated trends within e-scooter injuries but there are few epidemiological studies that evaluate injury rates amongst multiple modes of transportation. This study seeks to investigate trends of e-scooter orthopedic fracture injuries compared to other traditional methods of transportation using a national database. MethodsThe National Electronic Injury Surveillance System (NEISS) database was queried between 2014 and 2020 for patients who were injured after usage of e-scooters, bicycles, or all-terrain vehicles. Primary analysis included patients with a diagnosis of fracture and utilized univariate/multivariate models to evaluate risk of hospital admission. Secondary analysis included all isolated patients to evaluate the odds of fracture development amongst modes of transportation. ResultsA total of 70,719 patients with injuries associated with e-scooter, bicycle, or all-terrain vehicle use were isolated. 15997 (22.6%) of these patients had a fracture diagnosis. Both e-scooters and all-terrain vehicles reported increased odds of fracture-related injury and direct hospitalization when compared to bicycles. E-scooter users reported a greater odds of both associated fracture (OR 1.25; 95%CI 1.03–1.51; p = 0.024) and hospital admission (OR: 2.01; 95%CI: 1.26–3.21; p = 0.003) in 2020 compared to 2014–2015. DiscussionE-scooter related orthopedic injuries and hospital admissions had the largest incidence rate increase compared to bicycle and all-terrain vehicles between 2014 and 2020. E-scooter fractures were most commonly located in the lower leg in 2014–2017, the wrist in 2018–2019, and the upper trunk in 2020. In comparison, bicycle and all-terrain vehicle fractures was most commonly shoulder and upper trunk within the study period. Further research will help to promote further understanding of the e-scooter health care burden and in prevention of these injuries. Level of evidence3.

ANALISIS FASILITAS, TARIF DAN KUALITAS PELAYANAN PENGGUNAAN TRANSPORTASI BUS RAPID TRANS (BRT) DI KOTA SEMARANG

The purpose of this study was to analyze the influence of service quality, fares, facilities on the decision to use the Semarang Bus Rapid Trans (BRT) service. The problems faced are in the form of a lack of pedestrian facilities and the use of bicycles, less comfortable and safe shelters or bus stops, no digital or non-digital information media for notifications regarding the arrival of buses or the routes traversed by the Semarang BRT. In addition, the fare factor also plays an important role in public transportation, affordable fares for all people and the many benefits that can be obtained will increase public interest in using public transportation. This research uses descriptive analysis method with a quantitative approach. The population and samples were taken from 100 passengers of Semarang BRT. Data analysis was carried out by grouping data based on variables and types of respondents, tabulating data based on variables from all respondents, presenting data for each variable studied. The results of the study are that tariffs have a positive value and have a significant effect on the decision to use BRT services. Furthermore, the facility has a positive value and has a significant effect on the decision to use BRT services. The conclusion is that service quality is in a fairly high category in driving decisions to use Semarang BRT services. besides that the facility is included in the fairly strong category in the decision to use BRT Semarang services

Determinants of shared moped mode choice

A plethora of shared fleet services have been introduced in cities worldwide. Despite their increased presence in urban areas, it is insofar unknown what are the main determinants of travellers’ choices between the usage of shared-mopeds and cars and thereby the extent to which shared moped can substitute car travel. To this end, we design and conduct an SP choice model experiment. The estimated Panel Mixed Logit model is applied to explore the potential market share for shared moped, car and bike under several scenarios which are devised based on the expert interviews. Our findings demonstrate that the return availability of shared moped is the most influential travel time attribute. Walk time from home to the shared moped is an influential factor for people without moped experience. Moreover, model estimation results show that people who have used a shared moped before value the attributes differently than people without previous moped experience. We specifically focus on choice determinants and policy measures targeting car users to facilitate desirable behavioural changes. We present results from model application to demonstrate the effect of different policy packages on the market share of each mode, showing that certain policy interventions can attract car users to switch to shared moped while avoiding a strong reduction in bike use.

Bicycle use in Latin American cities: changes over time by socio-economic position

IntroductionWe aimed to examine utilitarian bicycle use among adults from 18 large Latin American cities and its association with socio-economic position (education and income) between 2008 and 2018.MethodsData came from yearly cross-sectional surveys collected by the Development Bank of Latin America (CAF). A total of 77,765 survey respondents with complete data were used to estimate multilevel logistic regression models with city as random intercept and year as random slope.ResultsIndividuals with high education and high-income levels had lower odds of using a bicycle compared with participants with lower education and income levels. These associations, however, changed over time with the odds of bicycle use increasing for all groups, especially among individuals with the highest education and income levels.DiscussionOur results confirm the broadening appeal of bicycling across socio-economic positions in several Latin American cities and reinforce the importance of considering policies aimed at supporting and enhancing bicycle travel for all users.

Patient-Reported Mobility, Physical Activity, and Bicycle Use after Vulvar Carcinoma Surgery

Patients treated for vulvar carcinoma may experience losses in mobility and physical activity. In this study, we assess the prevalence and severity of mobility problems using patient-reported outcomes of three questionnaires: EQ-5D-5L to estimate QoL and perceived health; SQUASH to estimate habitual physical activity; and a problem-specific questionnaire on bicycling. Patients treated for vulvar carcinoma between 2018 and 2021 were recruited, and 84 (62.7%) responded. The mean age was 68 ± 12 years (mean ± standard deviation). Self-reported QoL and perceived health were 0.832 ± 0.224 and 75.6 ± 20.0, respectively. Dutch physical activity guidelines were met by 34.2% of participants. Compared to baseline values, the times spent walking, bicycling, and participating in sports were all reduced. During bicycling, patients experienced moderate or severe pain in the skin of the vulva (24.5%), pain in the sit bones (23.2%), chafing (25.5%), or itching (8.9%). Overall, 40.3% experienced moderate or severe bicycling problems or could not bicycle, 34.9% felt that their vulva impeded bicycling, and 57.1% wished to make more or longer bicycling journeys. To conclude, vulvar carcinoma and its treatment reduce self-reported health, mobility, and physical activity. This motivates us to investigate ways to reduce discomfort during physical activities, and help women regain their mobility and self-reliance.

Health impacts of bike sharing system – A case study of Shanghai

BackgroundBike sharing systems have been promoted in many countries. Bike sharing can alleviate urban air pollution and reduce road congestion during peak hours in the morning and evening. In addition, using shared bicycles as a daily commuting tool can help users increase their daily exercise volume. This study evaluates the health effects of shared bicycle use. The evaluation of health is prospective, and we utilize current data to evaluate and analyze the health of future users. The primary health considerations for users include physical activity, PM2.5 levels, and collision rates. Physical exercise might be hindered by high concentrations of PM2.5. Thus, while riding in conditions of very high PM2.5 concentration, the pollutants taken by the traveler will hurt the body and counteract the advantages of physical exercise. This research demonstrates that cycling during periods of low or moderate PM2.5 concentrations should lead to an overall reduction premature mortality. Data and methodsWe perform a health assessment study to quantify the health risks and benefits of car trip substitution by bike trip. We collected the cycling data from Mobike shared bicycles operator in Shanghai established in August 2016. From August 1st to August 31st, 2018, there were 1,023,603 orders and 3,036,936 cycling users. During the computational analysis, we examined three factors: physical activity, PM2.5 pollution, and bicycle collision rate, and then summed the results to determine the cyclist's risk of early death. Three scenarios are created to estimate the annual expected number of deaths (increasing or reduced) due to physical activity, road traffic fatalities, and air pollution. ResultsAir pollution exposure was assessed using variations in the background fine particulate matter (PM2.5) concentration, which was 45 μg/m3 on average in August 2016 in Shanghai. Cycling under these settings, the advantages of physical exercise exceeded the hazards posed by pollution. When PM2.5 concentrations exceed 45 μg/m3, seven to eight people will avert early mortality for every 306,936 users. It means 23–26 per million cyclists would avoid premature death. When PM2.5 concentrations exceed 68 μg/m3, 1 to 2 people will be significantly harmed by air pollution and 4–7 out of every million cyclists are negatively affected by high PM2.5 concentrations. ConclusionsThese results demonstrate that shared cycling can avoid premature mortality. In addition, from the perspective of urban pollution, commuters choosing bicycles instead of cars to travel can reduce urban air pollution, improve air quality, and reduce traffic jams in the morning and evening peaks. Further research on the co-benefits of shared bicycles would be helpful to planners.

‘Why would you swap your nice warm van, where you can eat your butties and listen to the radio?’ Mainstreaming a niche of cycle logistics in the United Kingdom

Due to a high level of dependency on fossil fuels, transport is not only a priority for decarbonsation but also a particularly challenging sector to decarbonise. Significant low-carbon energy transitions in mobility will require changes in practices, technologies, infrastructure and policy. Cycle logistics is a growing economic sector. E-cargo bikes have the potential to replace some delivery and service journeys and to be used in combination with other transport modes to form a network of low-carbon deliveries. In comparison with conventional cargo bikes, e-cargo bikes are adapted with electric assist motors, thereby enabling the carriage of heavier loads over longer distances with lower physical strain on the rider.This study positions e-cargo bikes as an emerging technology within the Multilevel Perspective (MLP), a framework for understanding sustainable transitions that is structured around three levels: niche, regime and landscape. The Covid-19 pandemic has caused a landscape-level shock that has prompted an interest in increasing active travel and local deliveries. E-cargo bikes are a niche technology, and, although they respond to landscape-level trends, such as decarbonisation and air pollution reduction, the development of cycle logistics faces challenges stemming from the dominant automobility regime. There are limitations with e-cargo bikes themselves, although the technology and practice of e-cargo bike use are developing rapidly; there are factors that relate to the ability of the regime to accommodate and support the niche; there are considerations relating to practices and perceptions; and, finally, there are policy choices that reflect a lack of proactivity in encouraging and enabling e-cargo bike use. The paper explores experiences and perceptions of actual and potential e-cargo bike use and configures the MLP and the relationship between niche, regime(s) and landscape in relation to mobility transitions.

Last-Mile Logistics Network Design under E-Cargo Bikes

E-cargo bikes, i.e., electric bicycles equipped with baskets for transporting goods, are perceived as an advantageous solution for urban last-mile logistics. Particularly for short distances and low volumes of goods, the use of e-cargo bikes is ideal in urban areas where access of conventional cars may be prohibited. In this context, this study presents an e-cargo bike routing model for urban deliveries. The problem is formulated as a Capacitated Vehicle Routing Problem (CVRP), which takes several aspects into account, such as restrictions on bicycle capacity, road grade and workload balancing. A mathematical model is constructed to solve the problem, and a Genetic Algorithm (GA) is applied. Results on a case study in Athens, Greece are presented and analyzed, highlighting the applicability of the model in real-world operations, yielding reasonable results in short computational times.

Understanding the travel challenges and gaps for older adults during the COVID-19 outbreak: Insights from the New York City area

The COVID-19 pandemic has greatly impacted lifestyles and travel patterns, revealing existing societal and transportation gaps and introducing new challenges. In the context of an aging population, this study investigated how the travel behaviors of older adults (aged 60+) in New York City were affected by COVID-19, using an online survey and analyzing younger adult (aged 18–59) data for comparative analysis. The purpose of the study is to understand the pandemic's effects on older adults’ travel purpose and frequency, challenges faced during essential trips, and to identify potential policies to enhance their mobility during future crises. Descriptive analysis and Wilcoxon signed-rank tests were used to summarize the changes in employment status, trip purposes, transportation mode usage, and attitude regarding transportation systems before and during the outbreak and after the travel restrictions were lifted. A Natural Language Processing model, Gibbs Sampling Dirichlet Multinomial Mixture, was adopted to open-ended questions due to its advantage in extracting information from short text. The findings show differences between older and younger adults in telework and increased essential-purpose trips (e.g., medical visits) for older adults. The pandemic increased older adults’ concern about health, safety, comfort, prices when choosing travel mode, leading to reduced transit use and walking, increased driving, and limited bike use. To reduce travel burdens and maintain older adults' employment, targeted programs improving digital skills (telework, telehealth, telemedicine) are recommended. Additionally, safe, affordable, and accessible transportation alternatives are necessary to ensure mobility and essential trips for older adults, along with facilitation of walkable communities.

Energy Sufficiency in the Passenger Transport of Lithuania

This paper aims to understand the significance of energy sufficiency (ES) in passenger transport for the long-term resolution of energy, climate, and sustainable development issues in Lithuania. It computes related indicators, by fixing the passenger-kilometres (pkm) travelled by various modes of transportation and applying a scenario analysis with the MESSAGE model. The findings indicated that the country’s final energy consumption (FEC) in transportation could be reduced by 21.8% by 2050 due to slowing growth rate of distances travelled by passenger car but increasing use of public transport and bicycles. This would result in a decrease in the growth rate of primary energy consumption (PEC) by half (to 0.3% a year), an increase in the use of renewable energy sources (RES) to 67.2% in the PEC structure, savings of oil products by 6.4 TWh, and savings of new electricity generation capacity by 550 MW. Furthermore, 20 MtCO2eq. in greenhouse gas (GHG) emission reductions could be realised between 2021 and 2050. To take advantage of the potential of ES, the policy measures of passenger car demand containment and a shift to non-motorised and less polluting modes of transportation should be implemented. Furthermore, priority should be given to policy measures that encourage use of public transportation.