Backcasting Analysis of Autonomous Vehicle Implementation: A Systematic Review

Exploring parking choices under the coexistence of autonomous and conventional vehicles

Given the rapid technological advances in developing autonomous vehicles (AV), the key question appears not so much anymore how, but when AVs would be ready to be commercially introduced. Therefore, it is very timely to explore how the new way of travelling will shape the traffic environment in the future. Questions regarding the environmental impact, changes in infrastructure and policy measures are widely discussed. Most likely, the introduction of AVs will not only add an option to the traveller’s choice of means of transport, but also shape how people interact with the traffic environment. From a transport planning point of view, key questions concerning the introduction of AVs as a new means of transport are how it will influence travel behaviour, how supply and demand for AV will balance, how it impacts the viability of existing public transport services and how AVs will impact congestion and demand for parking. In this report, a new simulation framework based on MATSim is presented, allowing for the simulation of AVs in an integrated, network- and population-based traffic environment. The demand evolves dynamically from the traffic situation rather than being a static constraint as in numerous previous studies. This allows for the testing of various scenarios and concepts around the introduction of AVs while taking into account their feedback on the travellers’ choices and perceptions. Using a realistic test scenario, it is shown that even under conservative pricing a large share of travellers is attracted by autonomous vehicles, though it is highly dependend on the provided fleet size. For sufficiently large supplies it has been found that for the autonomous single-passenger taxis in this report the vehicle miles travelled increase up to 60%.

A Model-to-Decision Approach for the Autonomous Vehicle (AV) Ethical Dilemma: AV Collision with a Barrier/Pedestrian(s)

The introduction of autonomous vehicles (AVs) in the near future will have a significant impact on road traffic. AVs may have advantages in efficiency and convenience, but safety can be compromised in mixed operations of manual vehicles and AVs. To deal with the issues associated with mixed traffic and to avoid its negative effects, a special purpose lane reserved for AVs can be proposed to segregate AVs from manual vehicles. In this research, we analyze the effect on efficiency and safety of AVs in mixed traffic and in a situation where an AV-only lane is deployed. In the analysis, we investigate the average speed, the throughput, and the inverse time-to-collision (ITTC). We differentiate the behaviors of manual vehicles and AVs through the reaction time, desired speed, and car-following models. As a result, we observe that the efficiency is improved when the market penetration rate of AVs increases, especially when the highway throughput increases by up to 84% in the case of mixed traffic. However, safety worsens when the market penetration of AVs is under 40%. In this case, the average speed can be improved and the frequency of dangerous situations (ITTC > 0.49) can be reduced drastically in the merging section by making the innermost lane AV-only. Accordingly, we conclude that AV-only lanes can have a significant positive impact on efficiency and safety when the market penetration rate of AVs is low.

Automated driving systems are an emerging technology expected to transform the transportation industry due to reduced human involvement. While the introduction of autonomous vehicles (AVs) can significantly improve road safety, increase mobility, and reduce road crashes, there are also associated disadvantages. Policymakers have the ability to implement legislation that maximizes the benefits of AVs and minimizes their risks. Through an evaluation of barriers to AV adoption and regulations worldwide, this study aims to provide an overview of AV equity, liability, and safety policies globally. The results revealed that safety was the primary factor influencing public perception and hindering widespread adoption of autonomous vehicles. Furthermore, it was determined that governments have refrained from implementing stringent measures to encourage the advancement of AV technologies. Instead of enacting AV related laws, most countries have developed guidelines or formed councils to encourage further deliberation on safety and liability concerns associated with autonomous driving systems. Transportation professionals, AV consumers, and manufacturers will develop an understanding of AV accessibility, liability, and safety policies through this review. This paper can also help policymakers and drive future enacted legislation.

The rapid development of autonomous vehicles (AVs) has depicted a promising future of a safer and more efficient transportation system. To better induce this revolution, massive efforts have been spent on the technical competence of AVs. However, the human comfort in AVs has been an under-discussed yet important topic to the user acceptance of AVs. For the detection of human comfort, existing studies focus more on the physical influential factors of comfort such as sitting posture, vibration, and noise. With the introduction of AVs, psychological factors also have gained greater influence on human comfort. Despite existing studies of exploring correlations between human comfort and some physiological signals in automated driving contexts, there is few study on how human comfort level in AVs can be detected with these physiological signals. In this paper, we developed effective human comfort study approaches in autonomous vehicles with wearable sensors. We also proposed a machine learning based approach with adaptive feature selection to detect human comfort levels based on the wearable sensing data. The experimental results illustrated the effectiveness of the proposed approaches in studying human comfort in AVs.

Traffic congestion has become increasingly prevalent in many urban areas, and researchers are continuously looking into new ways to resolve this pertinent issue. Autonomous vehicles are one of the technologies expected to revolutionize transportation systems. To this very day, there are limited studies focused on the impact of autonomous vehicles in heterogeneous traffic flow in terms of different driving modes (manual and self-driving). Autonomous vehicles in the near future will be running parallel with manual vehicles, and drivers will have different characteristics and attributes. Previous studies that have focused on the impact of autonomous vehicles in these conditions are scarce. This paper proposes a new cellular automata model to address this issue, where different autonomous vehicles (cars and buses) and manual vehicles (cars and buses) are compared in terms of fundamental traffic parameters. Manual cars are further divided into subcategories on the basis of age groups and gender. Each category has its own distinct attributes, which make it different from the others. This is done in order to obtain a simulation as close as possible to a real-world scenario. Furthermore, different lane-changing behavior patterns have been modeled for autonomous and manual vehicles. Subsequently, different scenarios with different compositions are simulated to investigate the impact of autonomous vehicles on traffic flow in heterogeneous conditions. The results suggest that autonomous vehicles can raise the flow rate of any network considerably despite the running heterogeneous traffic flow.

Public transportation ridership and walkability of urban district can be enhanced through high quality of TOD(Transit Oriented Development) elements. Generally, TOD have been evaluated several physical components such as the diversity of land use pattern, accessibility of public transportation and aspects of urban design around the station area. Especially, Spatial characteristics of TOD planning elements have many potential dependent when considering the characteristics of Rail Station-Influenced Area Development which is performing around subway station. Therefore, researchers should be considering the variation of spatial properties for planning elements according the set of spatial area and their socioeconomic factors. However, existing many cases related TOD does not consider about this point. In this paper, the changes of TOD characteristics were analyzed by different spatial units surrounding subway station in Busan Metropolitan City. Multiple Regression Analysis was performed for an investigation of effective spatial unit of TOD planning elements in this area using subway ridership data. In addition, the application validity of socioeconomic variables was examined through a comparative analysis of regression results with the multiple regression that implied only physical TOD elements. As the result, the variation of spatial properties for TOD planning elements according to the set of spatial unit was found. Furthermore, the specific spatial unit to applicable TOD elements in this area was derived. And the multiple regression model which added socioeconomic variables was derived more improved estimate results than the multiple regression model that implied only physical TOD elements. KEYWORDS : Transit Oriented Development(TOD), TOD Planning Elements, Spatial Characteristics, Subway Ridership

When people pick routes to minimize their travel time, the total experienced delay, or social cost, may be significantly greater than if people followed routes assigned to them by a social planner. This effect is accentuated when human drivers share roads with autonomous vehicles. When routed optimally, autonomous vehicles can make traffic networks more efficient, but when acting selfishly, the introduction of autonomous vehicles can actually worsen congestion. We seek to mitigate this effect by influencing routing choices via tolling. We consider a network of parallel roads with affine latency functions that are heterogeneous, meaning that the increase in capacity due to to the presence of autonomous vehicles may vary from road to road. We show that if human drivers and autonomous users have the same tolls, the social cost may be arbitrarily worse than when optimally routed. We then prove qualities of the optimal routing and use them to design tolls that are guaranteed to minimize social cost at equilibrium. To the best of our knowledge, this is the first tolling scheme that yields a unique socially optimal equilibrium for parallel heterogeneous network with affine latency functions.

The introduction of autonomous vehicles (AVs) and shared autonomous vehicles (SAVs) is projected to enhance network performance and accessibility. The future share distribution of AV and SAV is not yet apparent, nor is which of these two future transport modes will become dominant. Therefore, this research deploys a simulation-based dynamic traffic assignment using Visum software to investigate the impact of varying the share distribution of AVs and SAVs on Budapest’s network performance and consumer surplus in three projected future traffic scenarios for the years 2030 and 2050 compared to the Base scenario for 2020. The three future scenarios are presented and characterized by different penetration rates of AVs and SAVs to reflect the uncertainty in the market share of these future cars as follows: Mix-Traffic scenario for 2030, and AV-Focused and SAV-Focused scenarios for 2050. The results revealed that the emergence of AVs and SAVs would improve the overall network performance, and better performance was observed with increasing the share distribution of SAVs. Similarly, the consumer surplus increased in all future scenarios, especially with increasing the share distribution of AVs. Consequently, the advent of AVs and SAVs will improve traffic performance and increase consumer surplus, benefiting road users and authorities.

Developing a micro-simulation tool for autonomous connected vehicle platoons used in city logistics

The introduction of autonomous vehicles has the potential to reduce the number of accidents and save countless lives. These benefits can only be realized if autonomous vehicles can prove to be safer than human drivers. There is a large amount of active research around developing robust algorithms for all parts of the autonomous vehicle stack including sensing, localization, mapping, perception, prediction, planning, and control. Additionally, some of these research projects have involved the use of the Robot Operating System (ROS). However, another key aspect of realizing an autonomous vehicle is a fault-tolerant design that can ensure the safe operation of the vehicle under unfavorable conditions. The goal of this thesis is to evaluate the feasibility of adding a dedicated fault tolerance module into a ROS based architecture. The fault tolerance module is used to implement a safety controller that can take over safety-critical operations of the system when a fault is detected in the main computer. A Xilinx Zynq-7000 SoC with a dual-core ARM Cortex-A9 and an FPGA programmable logic region is chosen as the platform. The platform works in the Asymmetric Multiprocessing (AMP) configuration with a Linux based operating system on one core and a real-time operating system (RTOS) on the other. Results are gathered from an implementation done on a ROS based mobile robot platform.

Developing Context Sensitive Planning Criteria for Transit Oriented Development (TOD): A Fuzzy-Group Decision Approach

Autonomous vehicles and street design: Exploring the role of medians in enhancing pedestrian street crossing safety using a virtual reality experiment

The introduction of autonomous vehicles (AVs) is projected to increase safety and efficiency of transportation. However, climate change poses a challenge to the smooth integration of AVs to current transportation infrastructure. Increased extreme weather events, higher precipitation and temperature, and damages to infrastructure are challenges AVs will face. Therefore, the authors advocate for Planned Adaptive Regulation, and raise questions that they feel policymakers and driving assessment should consider.