Private Car Drivers Research Articles

An Analysis of User Perceptions Towards Public Parking Management in Kampala City

The parking problems in Kampala City have become more pronounced due to the increasing vehicle numbers resulting from a growth in population and income levels. Understanding public perceptions and the various stakeholders’ parking needs and preferences is fundamental for identification of priority areas for improvement. This paper assessed the user perceptions of public parking management and the parking needs and preferences for various stakeholders in Kampala City. The study was evaluative and employed a cross sectional research design with a range of data diverse triangulation quantitative and qualitative techniques. From 328 questionnaires, participants were asked to assess fifteen (15) public parking management attributes from a point of view of their satisfaction. Also, a public parking stakeholder analysis was done and the level of influence by each stakeholder category in regards to parking management in the city and their parking needs and preferences were established. The study results revealed- that the customer satisfaction Index (CSI) of parkers was 52.4% indicating a relatively lower satisfaction level of the parking management in Kampala. From the fifteen public parking management attributes, four (4) of them to include affordability of parking, availability of parking spaces, accessibility to parking spaces and as well Safety and security were accorded the greatest importance. While thirteen (13) public parking stakeholders in Kampala City that included Ministry of Works and Transport (MoWT), Kampala Capital City Authority (KCCA), Multiplex Limited, Private Parking suppliers, public transport operators, Business Community, Commuters, Private Car Drivers, Logistics Vehicles, Traffic Police, Residents, shoppers and tourists and the academia were identified. The study recommends prioritization of those factors that parkers deem very important by the relevant authorities, stakeholder involvement in parking planning and management, establishment of an efficient enforcement and control mechanism, having a public parking vision with clear goals and objectives and as well the use of technology to enhance efficiency for both parkers and parking suppliers.

Rolling optimal scheduling for urban parcel crowdsourced delivery with new order insertion

The rapid development of mobile information technology has introduced numerous new solutions for delivery companies to enhance profits. One such solution employed by some companies is crowdsourced delivery. In this paper, we focus on rolling optimal scheduling for urban parcel crowdsourced delivery by utilizing private cars that will be in passing with the incorporation of new order insertion. The bonus incentive strategy is introduced to enhance the delivery probability of private car drivers. A static model and a rolling optimization model to maximize profits and the number of parcels delivered by private cars are established. To address the NP-hard problem, a hybrid genetic algorithm and insertion algorithm are designed. Numerical experiments are carried out to verify the proposed method in different scenarios, including the scattered network, clustered network, Dalian network, and Foursquare network. The computational results demonstrate that the method enhances the matching ratio and increases profits. Utilizing private cars that will be in passing for urban parcel delivery reduces the need for dedicated vehicles, mitigating traffic growth and alleviating traffic congestion. Increasing the private car-parcel ratio improves profits and the matching ratio while reducing traffic growth. Raising the incentive coefficient for bonuses increases the matching ratio and detour distance, but profits first increase and then decrease, and delivery distance by dedicated vehicles decreases. Our research findings offer a more rational basis for green urban parcel delivery decision-making by companies.

A crowdsourcing framework for green urban parcel delivery: Utilizing private cars that will be in passing

The strong increase of urban parcel delivery creates significant pressure on delivery enterprises. Nowadays, delivery enterprises do not only reduce operating costs, but also undertake a social responsibility: to reduce environmental costs caused by carbon emissions. This paper investigates the crowdsourcing framework to deliver urban parcels greenly by utilizing private cars that will be in passing. The bonus incentive strategy is introduced to improve the delivery willingness of private car drivers. Aiming at minimizing the sum of environmental costs caused by carbon emissions and enterprise costs, we establish a mixed-integer programming (MIP). To solve the problem, a hybrid genetic algorithm (GA) that combines adaptive large neighbourhood search (ALNS) and GA is proposed. The proposed approach is verified by standard instances. The results show that the green crowdsourcing framework with the participation of private cars will reduce the total costs. This approach has a great potential of reducing urban traffic growth and environmental pollution. Based on the real-word network in Dalian, the influences of the number of private cars, bonus incentive coefficient and time slack coefficient on the environmental costs and enterprise costs were investigated. Our research conclusion can provide a more reasonable decision-making basis of green urban parcel delivery for delivery enterprises.

An investigation into drivers' yielding behaviour at marked uncontrolled pedestrian crossings in Ghana

Given the dangers pedestrians are susceptible to when crossing the roadway, an investigation of motorists' yielding decisions at uncontrolled crossings should be prioritised. Some encounters between motorists and pedestrians turn into injuries or deaths due to excessive delay on the part of drivers, and pedestrians' impatience might lead them to opt for the rolling gap. Insights into drivers' yielding behaviour in developing countries are lacking. Meanwhile, developing countries contribute significantly to traffic deaths, particularly those in the African Region. Understanding drivers' yielding behaviour is necessary for effective interventions to safeguard pedestrians and encourage safe walking. Accordingly, by deploying a backward binary logit model, this study investigated drivers' yielding behaviour at marked uncontrolled pedestrian crossings through naturalistic observation. The results revealed that a small share of drivers, 258, were observed to yield to pedestrians, representing a 28% yielding rate in total. The model indicates that the chances of motorists yielding to pedestrians are enhanced by the following factors: pedestrian age, density, gender and traffic condition. Private car drivers had the lowest yielding rate of 18.2%, followed closely by public transport drivers. This research contributes to the discourse on drivers' yielding behaviour at pedestrian crossings with perspectives from a developing country. Further, it discusses policy implications for policymakers and enforcement agencies.

Predictive validity of the Multidimensional Driving Style Inventory in bus drivers’ crash involvement: A follow-up study

BackgroundThe Multidimensional Driving Style Inventory (MDSI, Taubman-Ben-Ari et al., 2004) is a widely used instrument that assesses private car drivers’ driving styles. However, a key validity check for the MDSI is whether the measurement of driving style is associated with drivers’ crash liability. MethodsA one-year follow-up study was conducted, and one thousand bus drivers were randomly recruited from three cities (Hangzhou, Beijing and Bazhong) in China. The participants were asked to complete the Chinese version of the MDSI and a demographic questionnaire, and they needed to report their traffic violation history 12 months after the survey. Violation history data only included traffic violations and crashes that were caused by the study participants rather than other road users. A confirmatory factor analysis (CFA) was conducted to assess the factorial structure of the MDSI. The relationships between the MDSI and traffic violation history over the previous 12 months and driving patterns over the 12 months immediately following the survey were investigated. ResultsCFA results show that the model fitness of the MDSI for bus drivers is acceptable. Both drivers’ traffic violations and crashes over the previous 12 months and driving patterns over the following 12 months were positively correlated with dissociative, risky and angry styles and negatively correlated with a careful style. Cluster analysis results show three clusters, with one unsafe driver group characterized by higher scores on dissociative, anxious, risky and angry styles and lower scores on careful driving styles. The number of drivers with traffic violations or crashes in the unsafe cluster is significantly higher than those in the other two clusters. More importantly, drivers in the unsafe cluster experience more traffic violations and crashes over the following 12 months than the other two driver clusters. ConclusionThe findings of the present study not only provide a reliable and valid instrument for assessing bus drivers’ driving styles but also show valid evidence for the predictive validity of the MDSI in measuring bus drivers’ crash involvement.

Assessment of the influence of the indicators of providing the quality of the transportation service of the city passenger enterprise on the transportation behavior of consumers in the city of Kyiv

Methods. The research results were obtained by applying a number of scientific approaches and methods, such as: multiple correlation – to determine satisfaction with the provided transport service of a trip by city passenger transport; the method of graphic factor analysis using the attributes of the quality of the transport service – to determine the quality of the process of providing the transport service and the quality of the result of receiving the transport service; methods of analysis, grouping – for the systematization of scientific and methodological approaches, determination of key indicators for evaluating the effectiveness of managerial influence on improving the quality of transport services for certain segments of customers of the city passenger carrier. Results. Evaluation of the relationship «quality – satisfaction» cannot be only point-wise: it is necessary to take into account at what point in time during the service process and how exactly a certain attribute of the quality of transportation affected a person’s impression. The short-term and continuous nature of the transport service for the transportation of passengers in the city makes it possible to evaluate its overall quality as an impression accumulated under the influence of attributes. Analysis of the dynamics of such accumulation allows identifying priority areas of management influence aimed at improving quality for individual segments of the city carrier’s customers. Novelty. The scientific novelty of the research results lies in the method of measuring the overall perceived quality of a trip through the city by isolating the quality of each of its attributes, the quality of its process, and the result, which made it possible to compare estimates of the level of quality of trips through the city for drivers of private cars and passengers of city transport, which meets the market requirements for quality of transport service provision. Practical value. The results of the study are of an applied nature, since the study of directions for evaluating the quality of the provided transport service in megacities will ensure the systematic application of tools with the stabilization of management approaches.

Back to the Present of Automated Mobility

This article focuses on how car drivers domesticate technologies of automation and the way this might inform our understanding of potential shifts to a more automated mobility system. The current literature on automated mobility has mainly addressed drivers’ roles in terms of their attitudes towards—and acceptance of—an anticipated shift to high-level driving automation. In this article, however, we take a step back from expectations around automated mobility to explore the domestication of driving assistance technologies and systems already in use. The analysis is built on qualitative interviews with drivers of private cars in Norway. Based on our findings, we develop a typology of user-technology characterizations highlighting three themes of the drivers’ use (comfort, safety, and novelty) as well as two modes of engagements (modulation and non-use). Our analysis suggests that automation is likely to be an incremental and gradual process and that its eventual application depends on the specificities of the practices that it seeks to disrupt. Moreover, we argue that the governance of automated mobility needs to be attentive to the dynamic and unpredictable roles technology will have in processes of socio-technical change. In this context, we highlight the key roles of users in shaping processes of appropriation of both new technologies and broader innovations and argue that knowledge about technology domestication provides important insights to changes towards automation in our current mobility systems.

How do the affective and symbolic factors of private car driving influence car users’ travel behavior in a car restriction policy scenario?

The number of private car trips a person makes is usually linked to external factors such as economic incentives or disincentives, legislation, infrastructure, and the quality of transport systems, among others. The impact of these options are typically analyzed to evaluate urban transport policies and projects. However, internal factors related to an individuals' attitudes and perceptions also play an essential role in the amount of private car driving they do and on urban mobility as well. Therefore, insight into private car driving's affective and symbolic aspects is important in order to formulate appropriate transport policies and strategies to reduce car-use dependency and encourage private car drivers to use public transport. Congestion charging schemes make drivers pay the full social cost of driving, they achieve congestion reduction, pollution reduction, they make cities more attractive for pedestrians and cyclists, and help improve quality of life. Congestion charging schemes are often difficult to implement and expensive to administer. As a result of these reasons, several cities worldwide have adopted a variety of car restriction schemes that try to reduce air pollution and congestion as well, instead of establishing congestion charges. The effects of driving restrictions in the short term are positive, but in the medium and long term, there are unwanted consequences. However, by giving private car drivers the option to pay a toll so that their cars are exempted from the restriction, these perverse incentives could be eliminated. This paper analyzes the impacts of internal factors related to individuals' attitudes and perceptions about the travel behavior of car users affected by car restriction policies in urban areas. We designed a stated preference survey conducted among car owners in Cali, Colombia, where a License Plate Restriction Charging (LPRC) policy has been in place since January 2017. Through hybrid discrete choice modeling, we demonstrated that latent variables, such as the feelings of being in control, independence, and higher social status, positively influence the decision to use cars for daily trips, thus impacting the urban modal split. The heterogeneity captured through these latent variables allowed us to understand more deeply how individuals deal with the LPRC policy in order to travel to their destination.

Pengaturan Terhadap Arogansi Pengendara Mobil Pribadi Di Jakarta

Traffic jams in Jakarta are indeed very severe, even Jakarta was once the city with the worst traffic jams in the world. So it is not uncommon for violations to occur when driving because of the dense and murky traffic conditions in Jakarta. Such as running through a red light, passing through a route that is not supposed to be, and some even intimidate other road users. This is done in order to get priority on the streets. This research is dedicated to finding out the regulation of driver arrogance in Indonesia, and to find out why the phenomenon of private car driver arrogance in Jakarta is increasingly prevalent. The research was carried out using normative juridical methods based on laws and regulations, related books, and legal research. It can be said, using a method through a statutory approach (statute approach) and a case approach (case approach). It is proven that there are still many cases of arrogance being committed. In Jakarta there are still arrogant private car drivers. Whereas in driving, drivers should have ethics in driving on the road. Most perpetrators of arrogance who dare to break the law on this highway are dominated by luxury car drivers. This is due to social hierarchies that make them feel higher than other drivers.

Strategy selection of ride-sourcing platform supply chain under the targets of “double carbon”: Integration or cooperation

Since the targets of “double carbon” (peak carbon dioxide emissions and carbon neutrality) was proposed, more and more ride-sourcing platform supply chains (RPSC) are committed to sustainable development. We consider a RPSC consisting of a ride-sourcing platform (platform), a new energy vehicle manufacturer (manufacturer), and a charging station service provider (service provider), where the government provides subsidies for building charging stations. Considering the integration and cooperation among the platform, the manufacturer and the service provider, we propose four strategies in combination with practical business practices. We find that: when the government provides the same subsidy level to the RPSC under each strategy, the platform is more inclined to select the strategy with a higher integration degree. Whether the service provider selects to cooperate with the platform in the integrated state or the cooperative state is related to the government subsidy. In the extension, based on the fairness among decision-makers, we investigated their optimal strategy selections. In addition, we discuss the optimal subsidy case of the government in terms of social welfare maximization, and the feasible range of the cooperative strategy is larger than other three strategies for three decision-makers. Robust results can still be obtained when considering private car drivers joining the platform and the electricity cost of the charging station.

Motivation of the enterprise in risks management of transport behavior of passengers in megapolises

Methods. The theoretical basis of the research is the scientific works of domestic and foreign scientists, where, along with general scientific methods, those determined by the specifics of the transport service. The basis of the study is the management concept as the art of changing people's transport behavior, which allows to avoid significant costs of the development of the transport system, transport risks and the negative impact of the increase in the number of private cars on the functioning of the metropolis as a place for a comfortable and safe human life. Analysis and synthesis were applied to identify the motives of transport behavior of residents of the metropolis; methods of grouping and classifications were used to identify behavioral intentions regarding the choice of the type of travel in the city; comparison – when identifying the factors affecting the choice of a vehicle according to the concept of Transportation Demand Management (TDM). Results. It has been shown that TDM campaigns often have low performance, which leads to the search for conditions and factors under which they can get the expected results. Motives for changing transport behavior are singled out, among which a separate group is formed by hidden motives. It was found that behavioral intentions regarding the type of city trip are dependent on satisfaction with previous trips, their consumer value and its predictors - sacrifices and benefits of the service. The main factor in the advantages of the transport service in the city is its quality. Novelty. It has been proven that the potential of TDM facilities in the cities of Ukraine is greater than in developed countries. The uniqueness of the state of urban transport development in Ukraine lies in the fact that the rapid improvement of its quality together with the introduction of transport demand management campaigns can create a strong influence on private car drivers and change their transport behavior. Practical value. Sustainable development of cities in ecological, economic and social dimensions in conditions of mass motorization of the population is possible only with the predominant use of public transport. The transition to the use of public transport or an increase in the frequency of its use is possible only if its quality is improved compared to the use of private cars. This requires the revision of all approaches to the evaluation of the quality of trips in the city by public transport, and therefore the results of the study can be useful for practice.

Reasons of university students' susceptibility to intelligent mobility and the use of mobility-as-a-service schemes

The transition from the current transportation system to intelligent mobility and the MaaS concept, through the introduction of Big Data analytics and digital innovation, is underway. Perceptions, attitudes and other internal factors often have a significant impact on the choice of human behavior in transportation. This paper discussed the characteristics of vehicle choice by type and depending on the goal of the trip. Private car drivers noted that they choose a car mainly because of accessibility, flexibility of use, safety and comfort. For public transportation passengers, safety and cost of travel were determining factors in their choice of public transportation. The main differences between trips with different goals were found for the indicators "time of a trip", "company trip", and "prestige". The results show that there is a positive perception of intellectual mobility among student youth, a tendency to switch from owning vehicles to other ways of using them and participating in MaaS schemes. It can be concluded that MaaS is positively perceived by the young generation of students. Based on the data obtained, proposals for the directions of sustainable development of urban public transport are made.

A study of aberrant driving behaviors and road accidents in Chinese ride-hailing drivers

This study aims at analyzing the factors of aberrant driving behaviors and road accidents among Chinese ride-hailing drivers. Four hundred and twenty ride-hailing drivers (Male = 65%) completed a web-based questionnaire survey that assessed personal attributes, work-condition factors, aberrant driving behaviors, and self-reported road accidents in the last three years. A 10-item violations Driver Behavior Questionnaire (DBQ) scale was adopted to explore the aberrant driving behaviors of ride-hailing drivers. The ordinal regression model was used to examine the effects of personal attributes and work-condition factors on aberrant driving behaviors. A binary logistic regression model was employed to investigate the predictors of road accidents. The descriptive statistics indicate that among ride-hailing drivers, the traditional taxi drivers were found to be more involved in aberrant driving behaviors than private car drivers. The results from the Principal Component Analysis (PCA) reveal that ride-hailing drivers were involved in "risky violations." Male and young ride-hailing drivers were found to be more involved in risky violations than their counterparts. Furthermore, it is revealed that a one-unit increase in risky violations increased the probability of being involved in road accidents by 60%. Furthermore, a one-unit increase in work-condition factors increased the likelihood of being involved in road accidents by 41%. The findings in this study can help better understand the aberrant driving behaviors of ride-hailing drivers and contribute to a more effective policy for reducing the road accidents caused by ride-hailing drivers.

Association between psychological symptoms and illegal driving behaviors in a sample of Chinese private car drivers.

BackgroundFindings on the associations between psychological symptoms and driving behaviors in private car drivers are inadequate.MethodThe study consisted of 3,115 private car drivers in Yulin, China. The measurements included socio-demographic data, traffic violations, accidents, and Symptom Checklist-90 (SCL-90). In addition, an ordered logistic regression model was employed to examine the association between each psychological symptom and risky driving behaviors.ResultsThe overall prevalence rate of any self-reported psychological symptom was 10.24%, with 9.22% for males and 11.49% for females. Among them, obsessive-compulsive, interpersonal sensitivity, additional items, hostility, and depression were the five most common psychological symptoms, with prevalence rates of 7.90, 6.29, 6.00, 5.91, and 5.62%, respectively. Any psychological symptom factor was associated with a higher risk of traffic violations and accidents. However, the intensity of the correlations varied, with obsessive-compulsive symptoms the strongest in general traffic violations and anxiety symptoms in traffic accidents. All psychological symptoms except phobic anxiety and paranoid ideation contributed to a higher risk of failing the driver's license test.ConclusionsThe prevalence rate of psychological symptoms was high in private car drivers. This study calls for an urgent need to establish a pilot tertiary prevention strategy to reduce risky driving behaviors through psychological symptom screening and interventions among private car drivers.

Meta-analysis of the results of researching the quality of city passenger transportation

Methods. The results of the work were obtained using the analysis and application of two areas of research on the quality of urban passenger transportation. The first approach deals with the measurement of transport system operating parameters, the second one focuses on researching the attitude of customers towards transport services. Results. It was found that the modern standards for evaluating the quality of transportation are not a sufficient methodological basis when stakeholders are faced with the task of reducing the frequency of using a private car in the metropolis. It requires the development of special tools for evaluating the quality of city trips. Here it is necessary to measure the difference in the quality of trips through the city, as experienced by passengers of city transport and drivers of private cars. Without such research, this kind of quality management will only be intuitive. Point studies allow to identify the main factors that stand in the way of quality and to understand the directions of managerial influence, however do not provide information for controlling measures for managing the demand for transportation. This also applies to the failure to take into account the hidden motives for evaluating the quality of passenger transportation in the content of the evaluation, which influence the decision to use private transport by city residents: the symbolic value of the car, the feeling of power over it, the preservation of a person’s personal space, etc. All these factors are also components of the quality of trips through the city, which expands the meaning of the quality of trips. Novelty. A special toolkit for evaluating the quality of city trips as an extended construct has been developed, according to which, in the monitoring mode, it is proposed to measure the difference in the quality of city trips based on the feelings of city transport passengers and private car drivers. Practical value. The results of the study are of an applied nature, since the study of directions for assessing the quality of passenger transportation in cities will ensure the systematic application of tools with the stabilization of management approaches. If we compare the importance for residents of the parameters of the service, the quality of which has reached a critical limit, we are convinced that they concentrate on the production parameters of the service process, and their methodological basis is not suitable for cases of managing the switch from traveling by private transport to city transport. The same applies to the regulatory framework according to which a city transportation must operate in Ukraine.

Lane-based Distance-Velocity model for evaluating pedestrian-vehicle interaction at non-signalized locations

Pedestrian vehicle conflicts at non-signalized crosswalks are a world-wide safety concern. Although the “pedestrian priority” policy is applied in some regions to improve pedestrian safety, its effect needs further investigation. This study proposes the Lane-based Distance-Velocity model (LDV) to investigate pedestrian-vehicle interaction at non-signalized crosswalks. Compared with the DV model, the LDV model considers the lateral distance between vehicles and pedestrians. Therefore, the LDV model extends the application of the DV model by allowing it to be applied not only on one-lane streets to multi-lane streets. The conflict severities of pedestrian-vehicle interaction in the LDV model are classified into four categories: safe-passage, mild-interaction, potential-conflict and potential-collision. Based on that, pedestrian crossing decisions are graded as safe-crossing, risky-crossing, and dangerous-crossing. The experimental data are collected at a non-signalized crosswalk through drone footage collected in Xi’an City (China) with a Machine Vision Intelligent Algorithm. The model is tested through a case study to evaluate pedestrian crossing safety when interacting with private cars and taxis. Results from the case study suggest that the proposed model works well in the pedestrian-vehicle interaction analysis. Firstly, 87.9% of drivers are willing to provide right-of-way to pedestrians when they have enough time to react and yield. Then, both the DV model and LDV model have reached consistent conclusions: the deliberate violation rate (DVR) of taxi drivers is 22.64%, which is double that of private car drivers. Last, taxis commit a higher percentage of pedestrians' dangerous or risky crossing situations than private cars. Relevant government departments can utilize the results of this study to manage urban traffic better and improve pedestrian safety.

Data-Driven Estimation of a Driving Safety Tolerance Zone Using Imbalanced Machine Learning.

Predicting driving behavior and crash risk in real-time is a problem that has been heavily researched in the past years. Although in-vehicle interventions and gamification features in post-trip dashboards have emerged, the connection between real-time driving behavior prediction and the triggering of such interventions is yet to be realized. This is the focus of the European Horizon2020 project “i-DREAMS”, which aims at defining, developing, testing and validating a ‘Safety Tolerance Zone’ (STZ) in order to prevent drivers from risky driving behaviors using interventions both in real-time and post-trip. However, the data-driven conceptualization of STZ levels is a challenging task, and data class imbalance might hinder this process. Following the project principles and taking the aforementioned challenges into consideration, this paper proposes a framework to identify the level of risky driving behavior as well as the duration of the time spent in each risk level by private car drivers. This aim is accomplished by four classification algorithms, namely Support Vector Machines (SVMs), Random Forest (RFs), AdaBoost, and Multilayer Perceptron (MLP) Neural Networks and imbalanced learning using the Adaptive Synthetic technique (ADASYN) in order to deal with the unbalanced distribution of the dataset in the STZ levels. Moreover, as an alternative approach of risk prediction, three regression algorithms, namely Ridge, Lasso, and Elastic Net are used to predict time duration. The results showed that RF and MLP outperformed the rest of the classifiers with 84% and 82% overall accuracy, respectively, and that the maximum speed of the vehicle during a 30 s interval, is the most crucial predictor for identifying the driving time at each safety level.

Considerations about an outbound bus lane in an urban area

This paper examines the feasibility of inserting a new exclusive bus lane in the public transport network of an urban area. It gives data and a case study example that demonstrate how a bus lane can be evaluated especially how a bus lane of a relatively limited length and of a relatively low bus frequency is worth being implemented – normally - in the case of a one-way street connecting the city center with the suburbs. The approach followed, analyses the findings from a case study in the eastern part of Thessaloniki, the second largest city in Greece with a population of approximately one million inhabitants. The bus lane used as the case study is focused on an outbound direction along a one-way street that connects the city center with the eastern suburbs of the city. This bus lane operates during part of the day according to the traffic conditions and the demand needs along the road corridor where it is located. The analysis includes field measurements of traffic data along the bus lane as well as a questionnaire-based survey that was mainly focused to investigate the quality of the service as perceived by the passengers. The paper shows that such bus lane can be fully justified (though with a reduced number of buses per hour), in terms of the travel time savings that it provides, the uninterrupted bus flow operation that it provides (that minimises the time they spend on the bus) and other characteristics. Parking restrictions and other traffic regulations enforcement is, however, necessary to prevent violations by drivers of private cars and minimise any adverse effects on the bus lane’s operation.

Environmental and social implications of incorporating carpooling service on a customized bus system

This study addresses one of the most challenging issues in designing a sustainable and efficient ride-sharing service. This paper uses an extensive computational study to quantify the behavior of carpooling in customized bus routing problems. This mechanism allows organizations to draw on the potential of their employees’ private cars to provide convenient alternative rides for other employees, thereby reducing air pollution and greenhouse gas emissions as well as increasing overall satisfaction with the transportation system offered. The objective functions minimize: (i) total transportation costs and incentives paid to drivers of private cars, (ii) dissatisfaction as determined by staff walking distance, travel time, and delays in arriving at work, and (iii) total carbon emissions generated by commuting. We propose a resolution algorithm based on Pareto Strength Ant Colony Optimization (PSACO) as an effective meta-heuristic method for solving the multi-objective mathematical model and compare it with the results obtained by an exact method. The effectiveness and applicability of the proposed problem have been evaluated by performing computational experiments on a real case study in Paris using a number of comparative metrics with appropriate assumptions. Different parameters affecting the performance of the algorithm are also investigated. The concluding section presents a comparison of the results achieved. The test outcomes confirm that the formulation and the solution methods can be useful references for practice. The insights obtained from the research could provide the basis for designing incentive schemes and information campaigns aimed at making ride-sharing systems more successful and improving their performance.

A Double-Layered Belief Rule Base Model for Driving Anger Detection Using Human, Vehicle, and Environment Characteristics: A Naturalistic Experimental Study.

“Road rage,” namely, driving anger, has been becoming increasingly common in auto era. As “road rage” has serious negative impact on road safety, it has attracted great concern to relevant scholar, practitioner, and governor. This study aims to propose a model to effectively and efficiently detect driving anger states with different intensities for taking targeted intervening measures in intelligent connected vehicles. Forty-two private car drivers were enrolled to conduct naturalistic experiments on a predetermined and busy route in Wuhan, China, where drivers' anger can be induced by various incentive events like weaving/cutting in line, jaywalking, and traffic congestion. Then, a data-driven model based on double-layered belief rule base is proposed according to the accumulation of the naturalistic experiments data. The proposed model can be used to effectively detect different driving anger states as a function of driver characteristics, vehicle motion, and driving environments. The study results indicate that average accuracy of the proposed model is 82.52% for all four-intensity driving anger states (none, low, medium, and high), which is 1.15%, 1.52%, 3.53%, 5.75%, and 7.42%, higher than C4.5, BPNN, NBC, SVM, and kNN, respectively. Moreover, the runtime ratio of the proposed model is superior to that of those models except for C4.5. Hence, the proposed model can be implemented in connected intelligent vehicle for detecting driving anger states in real time.