Car Trips Research Articles

Shifts in perspective: Operational aspects in (non-)autonomous ride-pooling simulations

On-demand ride-pooling systems have gained increasing attention in science and practice in recent years. Simulation studies have shown an enormous potential to reduce fleet sizes and vehicle kilometers traveled if private car trips are replaced with ride-pooling services. However, existing simulation studies assume operation with autonomous vehicles, with no restrictions on operational tasks required when the vehicles are operated by manual drivers. In this article, we simulate and evaluate the operational challenges of non-autonomous ride-pooling systems through driver shifts and breaks and compare their capacity and efficiency to autonomous on-demand services. Based on the existing ride-pooling service MOIA in Hamburg, Germany, we introduce shift and break schedules and implement a new hub return logic to perform the respective tasks at different types of vehicle hubs. This way, currently operating on-demand services are modeled more realistically and the efficiency gains of such services through autonomous vehicles are quantified. The results suggest that operational challenges substantially limit the ride-pooling capacity in terms of served rides with a given number of vehicles. While results largely depend on the chosen shift plan, the presented operational factors should be considered for the assessment of current operational real-world services. The contribution of this study is threefold: From a technical perspective, it is shown that the explicit simulation of operational constraints of current services is crucial to assess ride-pooling services. From a policy perspective, the study shows the operational challenges of a ride-pooling service with non-autonomous vehicles and the potential of future autonomous services. Lastly, the paper adds to the literature a practical ride-pooling simulation use case based on observed real-world demand and shift data.

Testing Individuals’ Ability to Compare Emissions from Public Transport and Driving Trips

To make informed environmental choices, individuals must first understand the potential environmental impacts of the modes of transport available and be able to relate this information to their own internal reference points. This study examines the results of an on-line survey conducted to assess the ability of individuals in the Greater Dublin Area to estimate their potential carbon footprint for a variety of modes of transport. The results indicate that nearly one third of those surveyed stated that they simply did not know the carbon footprint of the modes in question, while those who provided emissions estimates showed a wide range of variance. Comparison with existing emissions factors indicates that respondents overestimate the environmental impact of bus journeys and underestimate the impact of small car and tram trips. The results of this study indicate the need for more specific emissions information to allow individuals to make informed and sustainable mode choices.

Potentials of Light Electric Vehicles for Climate Protection by Substituting Passenger Car Trips

For the transformation of the mobility sector, small and light electric vehicles (LEV) show great promise, owing to their efficiency and low vehicle weight resulting in low energy consumption and lower greenhouse gas emissions per driven kilometer. The presented study focuses on the theoretical potential of substitutability of passenger car trips in Germany by varied LEVs based on the “Mobilität in Deutschland 2017” (“Mobility in Germany 2017”) dataset, for the year 2030. A detailed approach for identifying substitutable car trips was developed, reflecting age, trip purpose, number of passengers, and other decision criteria. By conducting a life cycle assessment of the considered LEVs and passenger cars, potential emission savings were analyzed. In the considered baseline scenario, it is found that emissions could be reduced by 44 % with 50% of passenger car mileage being substituted by LEVs. This study, thereby, gives way to further research on LEVs, and would urge both policy makers and general users to steer towards comprehensive measures that encourage a switch from cars to LEVs.

City-Level E-Bike Sharing System Impact on Final Energy Consumption and GHG Emissions

Bike-sharing systems implemented in cities with good bike lane networks could potentiate a modal shift from short car trips, boosting sustainable mobility. Both passenger and last-mile goods transportation can benefit from such systems and, in fact, bike sharing (dockless or with docking stations) is increasing worldwide, especially in Europe. This research focused on a European city, Lisbon, and the e-bike sharing system GIRA, in its early deployment, in 2018, where it had about 409 bikes of which 30% were non-electric conventional bikes and 70% were e-bikes. The research aims at answering the main research questions: (1) What is the number of trips per day and travel time in conventional bikes and e-bikes?; (2) Do the daily usage peaks follow the trends of other modes of transport in terms of rush hours?; (3) Are there seasonality patterns in its use (weekdays and weekends, workdays and holiday periods)?; (4) How do climate conditions affect its use?; and finally, (5) What would be the impact on final energy consumption and GHG emissions? The dataset for 2018 regarding GIRA trips (distance, time, conventional or e-bike, docking station origin and destination) and weather (temperature, wind speed, relative humidity, precipitation) was available from Lisbon City Hall by means of the program “Lisboa aberta”. Data regarding the profile of the users (which trips GIRA replaces?) and data regarding electricity consumption were not available. The latter was estimated by means of literature e-bike data and electric motor specifications combined with powertrain efficiency. Greenhouse gas (GHG) emissions were estimated by using the latest Intergovernmental Panel on Climate Change (IPCC) CO2 equivalents and a spreadsheet simulator for the Portuguese electricity GHG intensity, which was adaptable to other countries/locations. In a private car fleet dominated by fossil fuels and internal combustion engines, the e-bike sharing system is potentially avoiding 36 Ton GHG/year and reducing the energy consumption by 451 GJ/year. If the modal shift occurs from walking or urban bus to an e-bike sharing system, the impact will be detrimental for the environment.

Topological relationship model for geographical flows

ABSTRACT Geographical flows depict the movement of geographical objects from origin to destination. They can be applied to represent activities such as commuting, commodity trade, information exchange, and migration. The topological relationship model of geographical flows can provide information on the interactions between objects by describing whether two flows are disjoint or coincide partially or completely. For example, it can be applied to determine whether car trips within a city can be shared, identify takeout orders that can be delivered together, and prevent drone collisions. The ability to describe the topological relationship and relative direction between flows is important for analyzing the interaction between two objects. However, although many topological relationship models exist for lines, they are unable to describe both the topological relationship and the relative direction between lines accurately. To address this issue, this study developed a topological relationship model for geographical flows through the formalism of the 9-intersection model that can describe both the topological relationship and the relative direction between two flows. By removing non-existent relationships based on certain constraints, fifteen topological relationships are obtained and classified into six topological predicates. A method for determining the topological relationships was also developed that compares the section IDs and offsets of flows. The developed topological relationship model for flows was evaluated by examining a carpooling scheme based on taxi origin–destination flow data. The results show that the topological relationship model can describe the interactions among objects and select the flows that have specific interactions with other flows.

Sustainable development assessment of incentive-driven shared on-demand mobility systems in rural settings

BackgroundIn the light of the sustainable development goals, a set of operationalizable criteria quantifying societal benefits versus costs is needed to prepare for the introduction of an incentive-driven, high adoption shared on-demand mobility service in a rural transportation area. Aiming to reduce still-existing uncertainty about the impacts of a market entry and to balance substantial monetary incentives for suppliers of pooled rides with the progress in net GHG emission reduction and accessibility gain, the framework is applicable at the transactional and/or aggregate level.ResultsThe presented set of indicators is decision-oriented, and applicable both at the transactional and macro level. Scenarios and user choice situations for two regulatory options of demand responsive transport—one in line with the current legislation in Germany, avoiding overlap with existing fixed-route scheduled public transport and one not strictly complementary which assumes direct competition—are formalized. By the help of a case study, the outcome of the different organizational models at three levels of incentivization can be systematically compared. The implementation effort of the assessment method is examined in view of the forthcoming sustainability compliance reporting in this sector.ConclusionsA system-optimal constrained public private DRT deployment offers the opportunity of a reduction of uneconomic routes and parallel services upon selection of eligible rides. As shown, a crowding out of existing, publicly financed offerings in an unsaturated mobility market should not be the primary concern. At the contrary, resorting to supply-side incentives, a proportion of the high volume of solo car trips could be consolidated while levels of service improve in total. However, this may be associated with considerable expense, as demonstrated by the quantity structure of the provided case study.

Characteristics of Everyday Leisure Trips by Car in Sweden – Implications for Sustainability Measures

In search for measures to reduce greenhouse gas emissions from transport, insights into the characteristics of all sorts of trips and specifically trips by car are needed. This paper focuses on everyday leisure trips for social and recreational purposes. Travel behaviour for these purposes is analysed considering individual and household factors as well as properties of the trip, based on Swedish national travel survey data. The analysis reveals that everyday leisure trips are often of joint character and that the average distance travelled per person and day increases with, for example, income, cohabitation, children in the household and residence in rural areas. The result also shows that the studied characteristics vary between studied trip purposes, influencing the sustainability potential of a reduction in car use and suggested measures. For instance, the largest share of passenger mileage comes from social trips, whereas trips for exercise and outdoor life have the largest share of car trips below 5 km. Several characteristics indicate difficulties in transferring trips by car to, for example, bicycle or public transport due to convenience, economy, start times, company etc. The study indicates that there is a need to take a broader view of the effective potential.

Characteristics of Everyday Leisure Trips by Car in Sweden – Implications for Sustainability Measures

In search for measures to reduce greenhouse gas emissions from transport, insights into the characteristics of all sorts of trips and specifically trips by car are needed. This paper focuses on everyday leisure trips for social and recreational purposes. Travel behaviour for these purposes is analysed considering individual and household factors as well as properties of the trip, based on Swedish national travel survey data. The analysis reveals that everyday leisure trips are often of joint character and that the average distance travelled per person and day increases with, for example, income, cohabitation, children in the household and residence in rural areas. The result also shows that the studied characteristics vary between studied trip purposes, influencing the sustainability potential of a reduction in car use and suggested measures. For instance, the largest share of passenger mileage comes from social trips, whereas trips for exercise and outdoor life have the largest share of car trips below 5 km. Several characteristics indicate difficulties in transferring trips by car to, for example, bicycle or public transport due to convenience, economy, start times, company etc. The study indicates that there is a need to take a broader view of the effective potential.

INFLUENCE OF URBAN FORM CHARACTERISTICS ON TRAVEL BEHAVIOR: EVIDENCE FROM AUSTIN, TEXAS

Understanding the relationship between the physical form of the built environment and how people travel from origin to destination is vital to formulate policies to reduce the distance traveled and promote public transit. This study has used Austin activity-travel survey data to explore the influence of urban form characteristics on travel behavior. It has been hypothesized that mixed-use high-density development significantly impacts people's travel behavior in this area. Urban form variables like increase in density, better street connectivity, and mixed land use TAZ as origin and destination have been found to be significant in reducing the distance traveled and car dependency. Even after controlling the trip makers' and alternative specific characteristics, urban built form is showing a clear and strong impact on mode choice behavior. Though personal characteristics remain important after including the built form variables, built form variables also show significant influence on mode choice behavior. The results support the hypothesis of this study that mixed-use high-density development has a significant impact on the mode choice behavior of the people of the Austin area. These findings suggest that transportation policy formulation is not only an economic decision but also a land use planning decision. City authorities aiming to reduce automobile trips and distance travelled need to consider these built form characteristics to determine suitable areas to invest to yield the highest return in promoting transit use and active transportation.

Mobility impacts of a new metro system with transit-oriented development features

Few studies have analyzed the mobility impacts of TOD using a longitudinal research approach, and even fewer incorporated origin–destination (OD) information in the analysis. In this paper, we examine the impacts of a metro system with TOD features on the share of car and bus trips using Metro do Porto as a case study. The application of an autoregressive beta regression modeling approach to parish and OD data from two mobility surveys (2000 and 2017) allowed to detect changes in travel behavior accounting for pre-metro mode shares. Metro implementation was associated with strong reductions of the share of car trips in OD pairs with metro at both trip ends, especially when stations were TOD. Metro influence on the share of bus trips varied from neutral to positive, suggesting that bus and metro complement each other rather than compete for passengers.

Can shared E-scooters reduce CO2 emissions by substituting car trips in Germany?

This paper explores which trips currently made in Germany by personal motorized transportation could be replaced by e-scooters and what effect this would have on greenhouse gas emissions. This potential for substitution is estimated on the basis of data from the national household travel survey in Germany. Our analysis shows that 13% of the daily car trips, corresponding to 2% of the car kilometers in Germany, are suitable for replacement. Based on these results, we show that saving potentials of greenhouse gas emissions are heavily dependent on the general conditions of the specific use case (e.g. e-scooter lifetime) and the type of vehicle replaced. At best, a saving potential of about 5.8 kt of CO2eq per day could be achieved when trips with conventional cars are replaced by e-scooter driving. However, if battery electric cars are replaced, an increase in emissions may even occur under certain conditions.

The impact of new metro on travel behavior: Panel analysis using mobile phone data

The impact of urban rail transit on changes in various travel behavior outcomes has long been debated. However, few studies have used large-scale panel data to investigate how urban rail transit affects travel behavior. In the case of the new metros in Shenzhen, China, we constructed a four-wave panel of 7,799 residents across two years by using mobile phone data. We used a treatment–control group research design and a difference-in-differences analysis to evaluate the impact of the new metros on travel behavior in catchment areas of 0–1, 1–2, and 2–3 km, respectively. The results show that the appearance of the new metros increased the metro trips and activity space for the residents living in the 0–3 km range, but only increased total trip frequency and distance for the residents living in the 0–1 km range. New metro trips mainly replaced bike, e-bike, and bus trips, and slowed the growth trend of car trips. The findings help planners and policymakers better understand the impact of urban rail transit on the residents’ mobilities.

Choosing a Mode in Bangkok: Room for Shared Mobility?

Individual motorized vehicles in urban environments are inefficiently oversupplied both from the perspective of transport system efficiency and from the perspective of local and global environmental externalities. Shared mobility offers the promise of more efficient use of four-wheeler vehicles, while maintaining flexible routing. Here, we aim to understand the travel mode choices of commuters in Bangkok and explore the potential demand for shared mobility through examining both revealed and stated choices, based on our survey (n = 1239) and a systematic comparison of mode choice situations. Our multinomial logistic regression analysis indicates that commuters value time in their vehicles and accept fuel costs, but that they dislike wasting time walking, waiting, and searching for parking or pay for road use and parking. Our model results imply that shared taxi has a higher chance of being used as a door-to-door mode rather than as a competitor to motorcycle taxis as a feeder to the metro stations. Ride sharing gains substantial potential when private motorized cars are charged with the social external costs they cause via congestion charges and parking fees. Replacing cars with shared taxis as the daily choice for those living in detached houses will result in a 24–36% reduction of car trips on Bangkok roads.

Why would people want to travel more with automated cars?

The use of automated vehicles (AVs) may enable drivers to focus on non-driving related activities while travelling and reduce the unwanted efforts of the driving task. This is expected to make using a car more attractive, or at least less unpleasant compared to manually driven vehicles. Consequently, the number and length of car trips may increase. The aim of this study was to identify the main contributors to travelling more by AV.We analysed the L3Pilot project’s pilot site questionnaire data from 359 respondents who had ridden in a conditionally automated car (SAE level 3) either as a driver or as a passenger. The questionnaire queried the respondents’ user experience with the automated driving function, current barriers of travelling by car, previous experience with advanced driving assistance systems, and general priorities in travelling. The answers to these questions were used to predict willingness to travel more or longer trips by AV, and to use AVs on currently undertaken trips. The most predictive subset of variables was identified using Bayesian cumulative ordinal regression with a shrinkage prior (regularised horseshoe).The current study found that conditionally automated cars have a substantial potential to increase travelling by car once they become available. Willingness to perform leisure activities during automated driving, experienced usefulness of the system, and unmet travel needs, which AVs could address by making travelling easier, were the main contributors to expecting to travel more by AV. For using AVs on current trips, leisure activities, trust in AVs, satisfaction with the system, and traffic jams as barriers to current car use were important contributors. In other words, perceived usefulness motivated travelling more by AV and using AVs on current trips, but also other factors were important for using them on current trips. This suggests that one way to limit the growth of traffic with private AVs could be to address currently unmet travel needs with alternative, more sustainable travel modes.

How Should Vehicle Miles Traveled Displaced by E-Scooter Trips be Calculated?

A dominant practice in assessing mode shift for scooter sharing is to survey scooter riders on what transportation mode they otherwise would have taken. Trip share displacing car modes and average scooter trip distance are common metrics used to support calculations like vehicle miles traveled (VMT) and emissions reductions. This practice assumes a 1:1 relationship between trip and mile replacement, implying no relationship between mode replaced and scooter trip distance. In our study, we test this assumption. An in-app end of trip survey was answered by nearly 12,000 e-scooter riders using Spin e-scooter sharing in four U.S. cities: San Francisco, Tampa, Washington D.C., and Portland. Trip GPS breadcrumb distance was linked to survey responses, enabling scooter distance traveled to be calculated by mode displaced. We calculate scooter distance share and average trip distance conditional on mode displaced for scooter trips that displaced personal car, taxi, and transportation network company trips as alternative metrics to trip share and average trip distance, respectively. To account for the effects of built environment, we cluster scooter trips on the U.S. Environmental Protection Agency National Walkability Index for trip start location. We find that across cities and walkability index clusters, the conventional trip share and average trip distance metrics consistently overestimate walk-mode shift and underestimate car VMT displacement by e-scooter use. To ensure an accurate representation of mode shift, we recommend that cities, operators, and researchers report average trip distance conditional on mode displaced or scooter distance share. The mode shift observed across the four cities in this study, for example, revealed that about one-third of the distance travelled by scooters displaced car VMT.

Management of a patient with cardiac arrest: a clinical case of massive pulmonary embolism in an obese young man

Pulmonary artery thromboembolism is one of the few life-threatening conditions. Today, with less mobility due to their professional activities (prolonged sitting at a computer) and social behavior, the number of cases of venous thromboembolism has increased. The recommendations of the European Society of Cardiology for pulmonary embolism (2008, 2014, 2019) have become a powerful tool for diagnosing, treating and stratifying the risk of death. Prevention of recurrence of thromboembolic complications and its duration depends on the fact of provocation of pulmonary embolism. Recommendations for the development of thromboembolic complications take into account the presence of heart failure, coronary heart disease, atrial fibrillation (AF), which to some extent blurs the distinction between arterial and venous thrombosis. The fact that the incidence of pulmonary embolism increases with age is indisputable, but in contrast to atherothrombosis, venous thrombosis occurs much earlier, in the younger population. Thus, venous thrombosis is somewhat “younger” than arterial. Regarding gender differences, it is more common in men with age, and women tend to “rejuvenate”. Contraceptives play an important role in this, the risks of venous thromboembolism are pregnancy and childbirth. Although less influential in the development of venous thromboembolism and pulmonary embolism are bed rest (more than three days), immobilization in a sitting position (long flight, car trip), old age, in real clinical practice should not be neglected laparoscopic surgery and concomitant conditions— obesity, diabetes mellitus, hypertension and varicose veins. At the slightest suspicion of pulmonary embolism, it is important for the physician to consider the above factors. A clear algorithm for diagnosis and timely treatment will ensure the effectiveness of such patients and the process of their recovery. In recent years, obesity at the angle of low-intensity inflammation began to be considered involved in the processes of increased thrombosis. Although certain mechanisms of thrombosis in obesity have been elucidated, the frequent fatal thrombotic consequences of severe COVID-19 remain unclear, mainly in the category of patients with obesity, carbohydrate metabolism disorders, and diabetes. In this clinical case, the authors demonstrate the total stratification of risk factors, even at first glance insignificant effects of obesity of the first degree, but in combination with varicose veins of the lower extremities, which caused massive pulmonary embolism in young men.

Operational Efficiency Comparison and Transportation Resilience: Case Study of Nanjing, China

With the changes in global climate, adverse weather events appear to be more frequent. The efficiency, reliability, and safety of transportation operations can be compromised by extreme weather conditions. It is critical to analyse the spatiotemporal effects of extreme weather on the operational efficiency of transportation operational efficiency for meeting people’s travel and transport needs and formulating emergency management operation to prevent road congestion. It is also important to improve the resilience of transportation system. We compared the changes in transportation operational efficiency in Nanjing during normal weather on January 23 and snowstorm on January 25, 2018, using real-time travel data from Gaode Map. The results indicate that there are differences in the distribution of accessibility changes from different residential areas to the main city area in the morning peak. Overall, 90% of the accessibility change values are concentrated in −10 to 10 minutes, while 65% are concentrated in −5 to 5 minutes, and 70% of the rangeability of accessibility is concentrated in −20% to 20%. In a word, the travel in Nanjing in the snowstorm weather is basically normal. This observation is mainly due to the overnight snow removal and the reduction in the number of small car trips. In addition to the Xinjiekou area, the Hexi business district and the exit area of the cross-river tunnel should also be included in the key management areas for taking emergency management operation in the future.

Sustainable Urban Mobility Boost Smart Toolbox Upgrade

SUMBooST2 research develops universally applicable data science methodology which extracts key urban mobility parameters and origin/destination matrices from the anonymized big data set gathered from telecom operator. The methodology (toolbox) provides transport planners with a method for fast, efficient, and reliable provision of data on movements within the certain area. Origin/destination matrices with modal split will provide transport planners with valid input data for the planning of urban transport systems. The algorithms which separate relevant mobility data from the overall dataset are the unique part of the toolbox. The algorithms to identify passenger car trips are developed in 2020 project SUMBooST, and they are being upgraded in 2021 to detect trips made by active mobility modes and public transport. For the methodology to be valid, it must be implemented in representative number of cities. Previous SUMBooST project included implementation and validation in the City of Rijeka, and SUMBooST2 continues with two other cities, City of Zagreb, and City of Dubrovnik. The aim of the paper is to present innovative toolbox for the boost of sustainable urban planning based on big data science.

Understanding the Shortest Route Selection Behavior for Private Cars Using Trajectory Data and Navigation Information

Traffic information and driving preference play critical roles in the route selection of drivers and further impact transport management in practice. Some studies have explored the difference between actual and shortest paths for private cars during route selection. However, the quantification of the difference and deviation as well as the impacts of the date on route selection is still seldom investigated. The study proposed a method to quantify the deviation between actual and shortest paths based on big trajectory data and the digital map. Firstly, the rules of private car travel are determined according to the definition of a trip, and the travel trajectory is divided based on these rules to attain many trips. Then, the trip routes and their attributes are generated by geographical information methods. Baidu Map’s path planning collects the shortest routes with the optimal distance and time, and the deviation between actual and recommended paths is compared. Finally, the results of 2860 private car trips of nearly 400 drivers in Chongqing, China, reveal that only about 67% of the actual trips match well with the shortest path, which was significantly higher compared to existing studies. However, the deviation between the actual and shortest paths is limited to 9 minutes or 2 kilometers. There was no significant difference between the weekday and weekend in the proportion. Compared with the weekday, the indicators of the weekend are more deviated. Path selection and the deviation vary in travel modes, OD types, drivers’ preferences, travel time intervals, and distance intervals.

Air pollution and CO2 from daily mobility: Who emits and Why? Evidence from Paris

Urban road transport is an important source of local pollution and carbon emissions. Designing effective and fair policies tackling these externalities requires understanding who contributes to emissions today. We estimate individual transport-induced pollution footprints combining a travel demand survey from the Paris area with NOx, PM2.5 and CO2 emission factors. We find that the top 20% emitters contribute 75%–85% of emissions on a representative weekday. They combine longer distances travelled, a high car modal share and, especially for local pollutants, a higher emission intensity of car trips. Living in the suburbs, being a man and being employed are the most important characteristics associated with top emissions. Among the employed, those commuting from suburbs to suburbs, working at a factory, with atypical working hours or with a manual, shopkeeping or top executive occupation are more likely to be top emitters. Finally, policies targeting local pollution may be more regressive than those targeting CO2 emissions, due to the different correlation between income and the local pollutant vs. CO2 emission intensity of car trips.