17-05 Effects of Safe Bicycle Passing Laws on Drivers\u27 Behavior and Bicyclists\u27 Safety

This report identifies the effect of passing distance laws on drivers’ behaviors and bicyclist’s safety during an overtaking maneuver. Using an instrumented bicycle and driver survey, the study measured bicycle passing in a naturalistic field experiment using video recording, an ultrasonic distance measuring device, and a LiDAR. In order to evaluate the effect of passing distance laws, the study examined jurisdictions with a three-foot passing law, with a five-foot passing law, and without a passing law. The experiment required a bicyclist to ride the instrumented bicycle in two-lane and three-lane roads to capture the distance between the bicycle and the overtaking motor vehicle. Moreover, a new analysis algorithm is presented to assess the speed and distance transformation of the vehicles approaching and entering the passing zone of the bicycle in micro level transportation systems. The results demonstrated that drivers’ overtaking distances were significantly greater in locations with the five-foot passing law than in other areas. The study also found that roads with paved shoulders, wider travel lanes, and a greater number of lanes were associated with greater passing distances. In contrast, we found that passing distance was shorter on roads with shared lane markings (i.e., sharrows) or higher truck composition. By comparing the surveys conducted in locations with different passing laws, the study illustrates that drivers usually overestimate the distance that they pass bicyclists. These results can be useful to transportation engineers, policymakers, and legislators who intend to provide efficient designs of road infrastructure to better accommodate bicycles

Secure Harmonized Speed Under Byzantine Faults for Autonomous Vehicle Platoons Using Blockchain Technology

Autonomous Vehicle (AV) platooning holds the promise of safer and more efficient road transportation. By coordinating the movements of a group of vehicles, platooning offers benefits such as reduced energy consumption, lower emissions, and improved traffic flow. However, the realization of these advantages hinges on the ability of platooning vehicles to reach a consensus and maintain secure, cooperative behavior. Byzantine behavior [1,2], characterized by vehicles transmitting incorrect or conflicting information, threatens the integrity of platoon coordination. Vehicles within the platoon share vital data such as position, speed, and other relevant information to optimize their operation, ensuring safe and efficient driving. However, Byzantine behavior in AV platoons presents a critical challenge by disrupting coordinated operations. Consequently, the malicious transmission of conflicting information can lead to safety compromises, traffic disruptions, energy inefficiency, loss of trust, chain reactions of faults, and legal complexities [3,4]. In this light, this thesis delves into the challenges posed by Byzantine behavior within platoons and presents a robust solution using ConsenCar; a blockchain-based protocol for AV platoons which aims to address Byzantine faults in order to maintain reliable and secure platoon operations. Recognizing the complex obstacles presented by Byzantine faults in these critical real-time systems, this research exploits the potential of blockchain technology to establish Byzantine Fault Tolerance (BFT) through Vehicle-to-Vehicle (V2V) communications over a Vehicular Ad hoc NETwork (VANET). The operational procedure of ConsenCar involves several stages, including proposal validation, decision-making, and eliminating faulty vehicles. In instances such as speed harmonization, the decentralized network framework enables vehicles to exchange messages to ultimately agree on a harmonized speed that maximizes safety and efficiency. Notably, ConsenCar is designed to detect and isolate vehicles displaying Byzantine behavior, ensuring that their actions do not compromise the integrity of decision-making. Consequently, ConsenCar results in a robust assurance that all non-faulty vehicles converge on unanimous decisions. By testing ConsenCar on the speed harmonization operation, simulation results indicate that under the presence of Byzantine behavior, the protocol successfully detects and eliminates faulty vehicles, provided that more than two-thirds of the vehicles are non-faulty. This allows non-faulty vehicles to achieve secure harmonized speed and maintain safe platoon operations. As such, the protocol generalizes to secure other platooning operations, including splitting and merging, intersection negotiation, lane-changing, and others. The implications of this research are significant for the future of AV platooning, as it establishes BFT to enhance the safety, efficiency, and reliability of AV transportation, therefore paving the way for improved security and cooperative road ecosystems

Adaptive Airborne Separation to Enable UAM Autonomy in Mixed Airspace

The excitement and promise generated by Urban Air Mobility (UAM) concepts have inspired both new entrants and large aerospace companies throughout the world to invest hundreds of millions in research and development of air vehicles, both piloted and unpiloted, to fulfill these dreams. The management and separation of all these new aircraft have received much less attention, however, and even though NASAs lead is advancing some promising concepts for Unmanned Aircraft Systems (UAS) Traffic Management (UTM), most operations today are limited to line of sight with the vehicle, airspace reservation and geofencing of individual flights. Various schemes have been proposed to control this new traffic, some modeled after conventional air traffic control and some proposing fully automatic management, either from a ground-based entity or carried out on board among the vehicles themselves. Previous work has examined vehicle-based traffic management in the very low altitude airspace within a metroplex called UTM airspace in which piloted traffic is rare. A management scheme was proposed in that work that takes advantage of the homogeneous nature of the traffic operating in UTM airspace. This paper expands that concept to include a traffic management plan usable at all altitudes desired for electric Vertical Takeoff and Landing urban and short-distance, inter-city transportation. The interactions with piloted aircraft operating under both visual and instrument flight rules are analyzed, and the role of Air Traffic Control services in the postulated mixed traffic environment is covered. Separation values that adapt to each type of traffic encounter are proposed, and the relationship between required airborne surveillance range and closure speed is given. Finally, realistic scenarios are presented illustrating how this concept can reliably handle the density and traffic mix that fully implemented and successful UAM operations would entail

Business Case and Technology Analysis for 5G Low Latency Applications

A large number of new consumer and industrial applications are likely to change the classic operator's business models and provide a wide range of new markets to enter. This article analyses the most relevant 5G use cases that require ultra-low latency, from both technical and business perspectives. Low latency services pose challenging requirements to the network, and to fulfill them operators need to invest in costly changes in their network. In this sense, it is not clear whether such investments are going to be amortized with these new business models. In light of this, specific applications and requirements are described and the potential market benefits for operators are analysed. Conclusions show that operators have clear opportunities to add value and position themselves strongly with the increasing number of services to be provided by 5G.Comment: 18 pages, 5 figure

Powering Future Transport in Scotland: A Review for the Scottish Association for Public Transport

This report discusses energy costs and emissions associated with transport in Scotland and reviews options for future power sources for different modes of public transport. Transport provides a major contribution to greenhouse gas and other harmful emissions worldwide and efforts to reduce these are important for all forms of public transport, as well as for private cars and for the movement of freight. The effects of transport policy decisions are recognised, increasingly, as being very important for the electricity supply industry at national and local levels, largely because of the growth in the numbers of electric and hybrid road vehicles. Moving from oil to low carbon energy for transport raises important issues for electrical power generation and distribution systems in addition to challenges already being faced by the electrical power industry as the proportion of generating capacity involving renewables increases. The report starts by considering current energy costs and emissions for different forms of passenger transport and then outlines some current developments in areas such as internal combustion engine technology, battery storage systems and hydrogen fuel cells. Systems involving short-term energy storage and recovery of energy that would otherwise be dissipated as heat during braking are also discussed. Such systems generally involve the use of super-capacitors, flywheels or hydraulic devices. References are provided to the sources of data used in the analysis carried out for this review and, also, to sources of information about relevant developments in science and engineering. For all the new developments mentioned, there is a brief review of some transport applications in the United Kingdom and elsewhere. The possible impact of autonomous vehicles on future car ownership is still not known and the effects of this technology on public transport remain uncertain. As well as discussing autonomous road vehicles, the report makes brief mention of the potential of autonomous systems and increased automation for rail transport and for tramway operations. The benefits of further conventional railway electrification are reviewed in terms of energy usage, costs and emissions and the advantages of a more integrated approach to the provision of public transport in Scotland are emphasised. The value of using mathematical modelling and simulation methods to explore options in transport systems developments and planning is discussed, and the importance of testing simulation models in ways that are appropriate for the intended application is emphasised. This review presents the first results from a continuing study which was started in 2018 and is intended to provide information that should be relevant for those involved in decision-making in Scotland at the time of publication. The quantitative information contained within it clearly needs to be updated on a regular basis. The review concludes with recommendations for the Scottish Association for Public Transport about possible priorities for its efforts to increase public awareness about transport issues and is intended to be the first of a series of publications on transport and energy issues in the Scottish context. The references form an important part of the report and provide a potentially important bibliography which must be augmented and updated regularly

A Multimodal Approach for Monitoring Driving Behavior and Emotions

Studies have indicated that emotions can significantly be influenced by environmental factors; these factors can also significantly influence drivers’ emotional state and, accordingly, their driving behavior. Furthermore, as the demand for autonomous vehicles is expected to significantly increase within the next decade, a proper understanding of drivers’/passengers’ emotions, behavior, and preferences will be needed in order to create an acceptable level of trust with humans. This paper proposes a novel semi-automated approach for understanding the effect of environmental factors on drivers’ emotions and behavioral changes through a naturalistic driving study. This setup includes a frontal road and facial camera, a smart watch for tracking physiological measurements, and a Controller Area Network (CAN) serial data logger. The results suggest that the driver’s affect is highly influenced by the type of road and the weather conditions, which have the potential to change driving behaviors. For instance, when the research defines emotional metrics as valence and engagement, results reveal there exist significant differences between human emotion in different weather conditions and road types. Participants’ engagement was higher in rainy and clear weather compared to cloudy weather. More-over, engagement was higher on city streets and highways compared to one-lane roads and two-lane highways