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This study aims to validate a model for estimating platoon delay due to pedestrian crossing for use in Kuwait City.

The model was modified slightly for the scenario used in Kuwait, in which the presence of raised crosswalk meant that all incoming traffic would slow down automatically. Using video footage to observe the site, several variables were collected, and a model was used to calculate the delays suffered by the vehicles because of pedestrian crossing. The model was validated using the actual footage and manual observation to measure the delays.

The model showed a good match fit to the observed data, as the average delays differed by 22.5% between the two methods. Following the comparison, a sensitivity analysis was made on three variables: the acceleration rate, deceleration rate, as well as the pedestrian walking time. The analysis has shown that deceleration rate has approximately twice the effect on the model than the acceleration rate has. It has also shown that the pedestrian walking time has a major effect on the model, in an almost one-to-one correlation. A 50% change of the pedestrian walking time is associated with approximately 50% change in the model’s output delay.

A model for estimating platoon delay because of pedestrian crossing was validated for use in Kuwait City. The model was modified slightly for the scenario used in Kuwait, in which the presence of raised crosswalk meant that all incoming traffic would slow down automatically.

The successful and commercial use of self-driving/driverless/unmanned/automated car will make human life easier. The paper aims to discuss this issue.

This paper reviews the key technology of a self-driving car. In this paper, the four key technologies in self-driving car, namely, car navigation system, path planning, environment perception and car control, are addressed and surveyed. The main research institutions and groups in different countries are summarized. Finally, the debates of self-driving car are discussed and the development trend of self-driving car is predicted.

This paper analyzes the key technology of self-driving car and illuminates the state-of-art of the self-driving car.

The main research contents and key technology have been introduced. The research progress as well as the research institution has been summarized.

This paper aims to present a summary of the performance measurement and evaluation plan of the Wyoming connected vehicle (CV) Pilot Deployment Program (WYDOT Pilot).

This paper identified 21 specific performance measures as well as approaches to measure the benefits of the WYDOT Pilot. An overview of the expected challenges that might introduce confounding factors to the evaluation effort was outlined in the performance management plan to guide the collection of system performance data.

This paper presented the data collection approaches and analytical methods that have been established for the real-life deployment of the WYDOT CV applications. Five methodologies for assessing 21 specific performance measures contained within eight performance categories for the operational and safety-related aspects. Analyses were conducted on data collected during the baseline period, and pre-deployment conditions were established for 1 performance measures. Additionally, microsimulation modeling was recommended to aid in evaluating the mobility and safety benefits of the WYDOT CV system, particularly when evaluating system performance under various CV penetration rates and/or CV strategies.

The proposed performance evaluation framework can guide other researchers and practitioners identifying the best performance measures and evaluation methodologies when conducting similar research activities.

To the best of the authors’ knowledge, this is the first research that develops performance measures and evaluation plan for low-volume rural freeway CV system under adverse weather conditions. This paper raised some early insights into how CV technology might achieve the goal of improving safety and mobility and has the potential to guide similar research activities conducted by other agencies.

Studies on the Transit-Oriented Development (TOD) for Bangkok are found sparingly. The TOD concept is a supportive development for the rapidly changing city in order to reduce urban transport problems while encouraging people to shift transport modes to use public transportations instead of private cars. This study discusses the context of TOD in the density, the design, and the diversity of land use around transit stations among successful stations in many countries. There were 18 station areas in Bangkok which, by using the TOD Readiness score, the assessment of the stations implies that the higher scoring transit stations are more compatible to supporting pedestrian use of the transit station with lower car dependency. The 4 top-scoring stations were assessing by using multinomial logistic regression model. The study has found TOD scores and the frequent uses of the stations consequently encourage the commuters around the station areas decided to rely on public transport instead of car dependency. This is an effort to overcome the understanding of the station areas by reducing the complexity of the TOD contexts to any transit station in Thailand to be eligible for future study.

This study aims to optimize the traffic capacity allocation to solve the problem of low share of public transit in the landside system so as to get rid of the congestion trouble in landside traffic. The optimal timetable for airport buses can be searched by changing the departure interval of each line and evaluating the corresponding performance continuously.

This paper constructs a simulation model based on the real-world situation in Beijing Capital International Airport (BCIA), which simulates the whole process of airport bus schedules and analyzes the connections among multiple steps for transferring. The evaluation system is constructed by considering the benefits of passengers, airports and companies comprehensively. The optimal timetable for airport buses can be searched by changing the departure interval of each line and evaluating the corresponding performance continuously.

According to the experimental results, an excellent evacuation effect can only be achieved when the majority of departure intervals of airport buses are shortened to 50% of their original values, and some busy routes such as the Beijing Station line are supposed to be reduced to one-third of their original fixed intervals. As the airport bus passenger flow presents an obviously periodic variation over days, the timetable of the airport bus is supposed to be redesigned every day. A flexible bus timetable can not only meet the dynamic passenger flow but also enhance the attractiveness of public transit.

This paper constructs a simulation model based on the real-world situation in BCIA, which can not only model the complex scenes in the whole process of airport bus schedules but also reflect the intricate interaction between transferring passengers and vehicles caused by dense streamlines.

Perception has been identified as the main cause underlying most autonomous vehicle related accidents. As the key technology in perception, deep learning (DL) based computer vision models are generally considered to be black boxes due to poor interpretability. These have exacerbated user distrust and further forestalled their widespread deployment in practical usage. This paper aims to develop explainable DL models for autonomous driving by jointly predicting potential driving actions with corresponding explanations. The explainable DL models can not only boost user trust in autonomy but also serve as a diagnostic approach to identify any model deficiencies or limitations during the system development phase.

This paper proposes an explainable end-to-end autonomous driving system based on “Transformer,” a state-of-the-art self-attention (SA) based model. The model maps visual features from images collected by onboard cameras to guide potential driving actions with corresponding explanations, and aims to achieve soft attention over the image’s global features.

The results demonstrate the efficacy of the proposed model as it exhibits superior performance (in terms of correct prediction of actions and explanations) compared to the benchmark model by a significant margin with much lower computational cost on a public data set (BDD-OIA). From the ablation studies, the proposed SA module also outperforms other attention mechanisms in feature fusion and can generate meaningful representations for downstream prediction.

In the contexts of situational awareness and driver assistance, the proposed model can perform as a driving alarm system for both human-driven vehicles and autonomous vehicles because it is capable of quickly understanding/characterizing the environment and identifying any infeasible driving actions. In addition, the extra explanation head of the proposed model provides an extra channel for sanity checks to guarantee that the model learns the ideal causal relationships. This provision is critical in the development of autonomous systems.

Public-Private Partnership (PPP) is a common practice in both the public and private sectors. PPP has been an important instrument to achieve Sustainable Development Goals (SDGs) at the national level. However, the role of PPP at the subnational level is often scarcely studied. Using Khulna city of Bangladesh as a case, this paper aims to assess the role of PPP projects in the attainment of SDGs.

The research was conducted in the Central Business District (CBD) of Khulna, on a total of 4.6 kilometers stretches of road medians in the CBD where landscaping was done through the PPP approach. Besides the collection of secondary data from official records, primary data were collected through site visits, field surveys and interviews of PPP project partners.

The result shows that 89 percent of the respondents (road users) were pleased with the landscaping done on the road medians. Similarly, about 86 percent of the respondents felt more comfortable and safer to use the roads. Well-maintained road medians allow road-crossing at a regular interval which reduces the chance of an accident. The private parties have installed promotional billboards on the road medians and saved BDT 10.82 million a year. The public authority saves the maintenance budget amounting to BDT 23 million a year. The project achieves a triple-win situation. Despite some limitations, this PPP project has taken Khulna a step forward to achieve SDGs.

The findings have policy implications as the PPP project has enhanced the resilience of Khulna by addressing the relevant SDGs.

This paper aims to examine the types of user misbehaviours in the sharing economy (SE) context. SE offers a fruitful study setting due to the scope of potential misbehaviour and the expanded role of consumers.

The study drew on online archival data from the AirbnbHell.com website, where people share their stories about their Airbnb-related negative experiences. The authors reviewed 405 hosts’, guests’ and neighbours’ stories and coded the identified forms of misbehaviours into categories. The typology thus developed was validated in the context of the Uber Rides service.

User misbehaviours in the SE context can be distinguished based on the domain in which the user role is violated and the nature of violated norms. These two conceptual distinctions delineate a four-fold typology of user misbehaviours: illegal, unprofessional, unbefitting and uncivil behaviours.

The trustworthiness of the stories could not be assessed.

The presented typology can be used as a mapping tool that facilitates detection of the full scope of misbehaviours and as a managerial tool that provides ideas for effective management of misbehaviours that correspond to each category.

The paper presents the first empirically derived comprehensive typology of user misbehaviours in SE settings. This typology enables classification of a broad set of misbehaviours, including previously overlooked unprofessional behaviours carried out by peer-service providers. The study also puts forward a revised definition of consumer misbehaviours that encompasses the impact of misbehaviours on parties not directly involved in the SE-mediated exchange.

This study aims to identify the challenges faced by urban destinations in Spain in the current transitional stage towards a new reality of tourism, caused by the outbreak of COVID-19 and the ongoing global changes in the tourism industry.

An extensive literature review and an analysis of current debates were conducted to identify the different factors that have influenced the recent tourism phenomenon and the development of destinations on a global, regional-national and local-urban scale.

Four main challenges are identified, including the new mobility patterns of the population; information and communication technologies and the digitalisation process in urban and tourism management; sustainability, as a factor of the competitiveness, stability and viability of urban destinations; and governance in urban destinations.

The study’s findings provide valuable insights for urban destination managers to make informed decisions and adapt to the new reality of tourism.

Railway-level crossings (RLCs) are the point of intersection between rail and road users and are therefore hotpots of road-rail user conflict and catastrophic collisions. The purpose of this study is to assess the risks associated with RLCs and suggest probable reduction measures. Through questionnaires and visual inspection, the authors identify the safety risks, hazards and hazardous events at some railway crossing of Addis Ababa light rail transit (AA-LRT) north-south (N-S) route. The identified risky events are then categorized based on As Low As Reasonably Practicable (ALARP) principle and generic risk ranking matrix. The authors then examine existing safety management measures at railway crossing and assess the need for additional safety management. Five major crossings on the 16.9 km (10.5 mi) N-S line, starting from Menelik II Square to Kality, were considered for the study. This study is carried out by data collection from about 145 stakeholders and the application of statistical data and risk analysis methods. The major findings of this study and the recommendations for improvement are suggested.

The research followed a case study approach. Through questionnaires and visual inspection, the authors identify the safety risks, hazards and hazardous events at some railway crossing of AA-LRT N-S route. The identified risky events are then categorized based on ALARP principle and generic risk ranking matrix. Collected data was then analyzed using SPSS to deduce relationships.

The study findings reveal human factors as the greatest cause of accidents, injury or death. About 22% of hazards identified by category are human factors, whereas 20% are because of technical problems. Intolerable risks stand at 42%, whereas the tolerable risks are at 36% according to risk classification results as per the ALARP model. Because the process of risk management is a long-term cycle, its importance should not be missed at any time.

Because of design considerations of RLCs and the difference in generalized human behaviors for people of a given region, the results are limited to AA-LRT RLCs. This study opens a discourse for detailed evaluations, qualitative and quantitative analysis into the categorized identified hazards. There is also room for additional research into the performance of RLCs aimed at formulating standard necessary features that should be included on RLCs for proper risk control especially in emerging economies.

The research paper is original and has not been submitted for consideration to other journals.