Safety assessment of on-road cycling lanes: A comparative study of different layouts using driving simulator.

Over the past few decades, a growing attention has been directed toward cycling due to its positive impacts on social, economic, and health aspects. Various countries are adopting and implementing strategies to promote cycling as a daily mode of transport. The main objective of this study is to improve cyclists' safety by investigating the impact of different layouts of on-road cycle lanes at two-lane two-way roads on drivers' interactions with cyclists using driving simulator. Three layouts of on-road cycle lanes were tested and compared, namely, uncolored, colored, and island separation, along with a control case where no cycle lane was provided. In addition, the impact of road alignments (straight sections, left and right curves) and the presence of an opposing vehicle were investigated. The driving simulator at Qatar University was used to conduct this study. A total of 92 subjects participated in this study. According to the results, on-road cycle lanes can significantly increase the safety of cyclists compared to shared lanes with motorized traffic. Moreover, the results showed that the drivers' intrusion to the opposite lane in the presence of opposing vehicles can be eliminated by providing on-road cycle lanes. That is, drivers' crash risk can also be reduced through the provision of on-road cycle lanes. Comparison of different on-road cycle lane treatments showed that uncolored cycle lanes outperformed the other layouts in terms of lateral clearance between the driver and the cyclist for right and straight alignments. On the other hand, the colored cycle lane showed better results for the left alignment. The findings of this study could be useful for designing on-road bicycle infrastructure to eliminate possible vehicle-cyclist and vehicle-vehicle conflicts and minimize crash risk.

Pedestrian flow characteristics through different angled bends: Exploring the spatial variation of velocity.

Common geometrical layouts could potentially be bottlenecks, particularly during emergency and high density situations. When pedestrians are interacting with such complex geometrical settings, the congestion effect might not be uniform over the bottleneck area. This study uses the trajectory data collected through a controlled laboratory experiment to explore the spatial variation of speeds when a group of people navigates through bends. Four turning angles, i.e., 45°, 90°, 135° and 180°, with a straight corridor and two speed levels, i.e., normal speed walking and slow running (jogging), were considered in these experiments. Results explained that the speeds are significantly different over the space within the bend for all angles (except 0°) under both speed levels. In particular, average walking speeds are significantly lower near the inner corner of the bend as compared to the outer corner. Further, such speed variations are magnified when the angle of the bend and desired speed increase. These outcomes indicate that even smaller turning angles, e.g., 45° could create bottlenecks near the inner corner of the bend, particularly when the walking speeds are high. The findings of this study could be useful in understanding the congestion and bottleneck effects associated with complex geometrical settings, and calibrating microscopic simulation tools to accurately reproduce such effects.

Interactions between autonomous vehicles and pedestrians at unsignalized mid-block crosswalks considering occlusions by opposing vehicles.

Visibility can be identified as one of the critical determinants for the safety performance of autonomous vehicles (AVs) on unsignalized mid-block crosswalks (UMC), which may be significantly influenced by build-up environment and surrounding vehicles. This study investigates the safety performance when AVs interact with pedestrians approaching from far-side sidewalks to UMCs considering the visual occlusion of opposing vehicles. A mathematical model is proposed for judging the visibilities of objects from observers' location under the impact of visual obstacles and is embedded into an agent-based pedestrian-vehicle interaction framework. Two yielding decision modules is assumed for AVs: The normal decision module implements the pedestrian priority rule simply based on the current detectable information, whereas the memory aid decision module extends AVs' detection abilities by incorporating the memory data. Through simulation experiments, it is found that the percentages of short post encroachment time (%SPET) between AVs and far-side pedestrians reach peaks when the pedestrian flow rate is 300-400 ped/h. When opposing vehicles are in stationary queue conditions, %SPETs are only sensitive to the net distance between the last opposing vehicles in the queue and crosswalks (Dqueue). As the Dqueue decreases to lower than 15 m, %SPETs start to increase drastically. However, when opposing vehicles are in free flow conditions, %SPETs are influenced by multiple factors such as pedestrians' crossing decisions, sizes and flow rates of opposing vehicles. Furthermore, only when opposing vehicles are in free flow conditions, memory aid AVs can significantly eliminate the impacts of opposite vehicles. Finally, several countermeasures are developed to enhance the visibility and safety at UMCs based on the findings of this study.

Structural equation modeling of public transport use with COVID-19 precautions: An extension of the norm activation model.

This study aims to identify the travelers' attitudes and preferences towards the use of public transport during COVID-19 through the Norm-Activation Model (NAM). A questionnaire survey was designed to assess the traveler's awareness, sense of responsibility, and moral obligations to comply with safety norms or guidelines while using public transport in Lahore, Pakistan. The Structural Equation Modeling method was applied to analyze the collected 1516 complete responses. The survey results and measurement equations confirmed the association between observed and corresponding latent variables. The results of SEM revealed that the travelers' Awareness of Consequences (AC) and Ascription of Responsibility (AR) are positively correlated with Personal Norms (PN), whereas attitudes towards public transport are negatively related to the PN. The perceived behavioral control (PBC) and PN have negative structural correlations with public transport use. However, the attitudes towards public transport are strong predictors of travelers' behavior towards public transport. The current motorcycle users and high-income people have low preferences, whereas current users of public transport modes and middle-income people have high preferences to choose public transport during a pandemic. The travelers' perceived difficulty of complying with safety guidelines while traveling, such as wearing a facemask, use of sanitizers, and maintaining a social distance, have a significant impact on their public transport use. The travelers' better awareness, responsibility, and trust in using public transport may have a strong influence on their preferences towards public transport during a pandemic situation.

Improved traffic safety at work zones through animation-based variable message signs.

Work zones are established to provide a safe environment for all road users and road workers. However, based on the statistics, they can be considered as crash prone zones due to changes in the road alignments and the posted speed limits. In this driving simulator study, we aimed at investigating the safety impacts of a newly proposed system composed of graphical and animation-based variable message signs (VMSs) in the state of Qatar. The proposed VMS condition was compared with a control condition that was designed following the Qatar Work Zone Traffic Management Guide. A total of seventy subjects were invited to participate in the experiment voluntarily. Study results showed that in the VMS condition, drivers reduced their traveling speeds in advanced compared to the control condition. Drivers' traveling speed in the VMS condition was significantly reduced by 6.3 and 11.1 km/h on the leftmost and the second leftmost lanes, respectively. Next, the results uncovered that the proposed system motivated drivers to initiate early lane changing maneuvers, i.e., 150 m earlier than the control condition. Finally, the VMS condition was effective in stimulating drivers to keep larger headways with a merging vehicle. In sum, the proposed VMS system outperformed the control condition in terms of speed reduction, early merging, and higher headways between the through and the merging vehicle.

Exploring the impacts of COVID-19 on travel behavior and mode preferences.

Various measures were recommended or imposed by the governments to control the spread of COVID-19. Travel behaviors are significantly influenced due to such measures. However, people have various travel needs ranging from grocery shopping to work. This study examines the changes that occurred in travel behavior due to the COVID-19 pandemic. Data were collected through an online questionnaire survey that included questions on trip purpose, mode choice, distance traveled, and frequency of trips before and during COVID-19. 1203 responses were collected from various countries around the world. Results explained that trip purpose, mode choice, distance traveled, and frequency of trips for the primary travel were significantly different before and during the pandemic. Further, the majority of trips were made for shopping during the pandemic. There was a significant shift from public transport to private transport and non-motorized modes. People placed a higher priority on the pandemic related concerns while choosing a mode during the pandemic as compared to the general concerns. Gender, car ownership, employment status, travel distance, the primary purpose of traveling, and pandemic-related underlying factors during COVID-19 were found to be significant predictors of mode choice during the pandemic. Outcomes of this study could be useful in transport planning and policymaking during pandemics based on the travel needs of people. In particular, government authorities could utilize such knowledge for planning smart and partial lockdowns. Service providers, e.g., taxi companies and retailers, could use such information to better plan their services and operations.