Transportation network

Modeling the effect of autonomous vehicles (AVs) on the accessibility of the transportation network

Abstract

The utilization of autonomous vehicles (AVs) has emerged as a pivotal factor in addressing the rising costs and safety concerns associated with modern travel. As technology advances and traffic challenges intensify, enhancing accessibility stands out as a critical goal for transportation experts. Accessibility, constrained by factors like travel time, underscores the increasing need for AVs to mitigate these limitations. This study aimed to model the influence of AVs on the accessibility index within transportation networks and discuss system optimization based on user equilibrium (UE) and system optimum (SO) outcomes. The research conducted numerical analysis employing the Hearn network as a fundamental system to validate a mixed assignment model and ascertain baseline accessibility. Additionally, the Sioux Falls network, a medium-sized network, was employed for analysis. A hybrid heuristic assignment algorithm was introduced, concurrently assigning different percentages of AV presence alongside the remaining non-AV percentage in three distinct scenarios. These scenarios ranged from 0 to 100% AV presence: the first scenario maintained constant network capacity, the second scenario adjusted network capacity based on AV presence, and the third scenario incorporated capacity adjustments in the assignment stage. In all three scenarios, network accessibility was evaluated using gravity and accessibility index methods derived from the hybrid assignment model output. The findings demonstrated that as the percentage of AVs increased, accessibility improved in both Hearn and Sioux Falls networks across all scenarios. The second and third scenarios exhibited higher accessibility increases compared to the first, attributable to augmented capacity resulting from increased AV presence. In the Sioux Falls network, the first scenario showed enhanced SO and UE due to increased AV presence and enhanced system operator management. Conversely, the second and third scenarios, with increased AVs and subsequent capacity increments, displayed reduced UE and SO results. Despite the decline in UE and SO, traffic flow assignment and overall network accessibility improved. These findings highlight the positive correlation between AV presence, network capacity, and enhanced accessibility. The study underscores the potential benefits of AV integration in optimizing transportation networks and improving overall accessibility, albeit with nuances in capacity adjustments impacting traffic flow dynamics. Further research avenues could explore complex traffic flow scenarios and delve into more specific optimization strategies.

Introduction

Autonomous vehicles (AVs) are vehicles that can cover all aspects of driving in any environmental condition. According to Litman's research, the use of AVs started before 2020, and the expansion of their use will probably be realized in 20401. AVs promise a fundamental change in transportation. Travel is expected to be safer, cheaper, easier, and more sustainable through the use of AVs, and as a result, travel costs will also decrease2,3. According to estimations, AVs will have a special place in urban and intercity transportation in the next ten years. It is clear that with the application of these vehicles and their positioning, the planning horizons for the coming years will change. Modeling tools give researchers the possibility of impact measurement in transportation networks and make it possible to understand the future better. Among the effects of AVs, increasing safety, reducing fuel consumption, and creating a happier and more active life for people can be mentioned. The development of AVs can also be imagined under the influence of the desire of large companies to invest and take over the market share.

AVs can identify their surroundings and move safely alone or with little assistance4,5. Different autonomy levels are envisioned for such vehicles6,7. AVs make it possible for those who are unable or unwilling to drive to move by themselves without needing a driver. These people include the disabled and elderly, or young people without a certificate. As a result of this capability, more destinations are available to these groups and the number of trips they can make will increase8. On the one hand, cheap trips and the competition created between shared and private vehicles provide the opportunity to access more distant destinations, including the suburbans, for this group of users9. Studies in the field of people’s desire to use AVs in different categories indicate that the degree of desire depends on factors such as gender, income, age, etc.10. On the other hand, shared AVs provide the possibility of multiple trips at a low cost and without worrying about the costs of owning a vehicle (such as depreciation, insurance and taxes, and repairs)11. In addition, it is possible for the passengers of such vehicles to do other activities unrelated to driving. Such an approach will certainly cause more users to favor such vehicles, and as a result, it will lead a wave of people to use such vehicles12.

Each vehicle can benefit from information obtained from other vehicles in its vicinity, especially information about traffic congestion and safety hazards. Vehicular communication systems use vehicles and roadside units as communication nodes in a peer-to-peer network and provide information to each other13. In a cooperative approach, vehicular communication systems can cooperate with all vehicles to be more effective. According to a study conducted by the National Highway Traffic Safety Administration, vehicular communication systems can prevent up to 79% of traffic accidents14.

Significant research has supported both the potential benefits of AVs in enhancing travel efficiency and the possibility of increased travel demand resulting from their adoption. AVs are equipped with communication systems that allow them to communicate with other AVs and roadside units to provide them with information about the road or traffic congestion. In addition, scientists believe that the future will be accompanied by computer programs that will manage each private vehicle as it passes through the intersection. This type of connection can replace traffic lights and stop signs. These types of features also create and develop the ability of AVs to cooperate with other services (such as intersection computer systems) in the AV market. This issue can lead to creation of a network of AVs that all use the same network and the information in that network. Finally, the application of this problem can lead to more use of AVs in the network because the information is verified by the use of other AVs. Such movements strengthen the value of the network, and these movements are called external factors of the network15.

Visit: https://civil-engineering-conferences.scifat.com/


Nominate Link: https://x-i.me/pravnom
Member Link: https://x-i.me/civilmem


Get Connected Here:

--------------------------------------
--------------------------------------

youtube.com/channel/UC3bk75P_uoV_D1uFxE9DbZw
instagram.com/leo.lily121/
youtube.com/channel/UC3bk75P_uoV_D1uFxE9DbZw
https://twitter.com/home