Utilizing Lane-Based Strategy to Incorporate Mixed Traffic in Interchange Control for Connected and Autonomous Vehicles

2019 ◽  
Vol 2673 (5) ◽  
pp. 454-465 ◽  
Author(s):  
Majeed Algomaiah ◽  
Zhixia Li
Keyword(s):  
Autonomous Vehicles ◽  
Penetration Rate ◽  
Traffic Signals ◽  
Heavy Vehicle ◽  
Market Penetration ◽  
Mixed Traffic ◽  
Traffic Demand ◽  
Communication Range ◽  
Throughput And Delay ◽  
Lane Based

This work examines the next-generation interchange control system (NIC) that aims to control connected and autonomous vehicles (CAV) at interchanges with the consideration of different mixed traffic cases. The first objective of the paper is to test several parameters including traffic demand, heavy vehicle percentage, communication range, and advance stop line (ASL) to investigate their impact on throughput and delay. The second objective is to incorporate mixed traffic in the NIC, utilizing a lane-based strategy that is responsive to market penetration rates. The NIC coordinates vehicles to traverse the interchange terminal by using a reservation-based control strategy with a first-come-first-served (FCFS) reservation protocol. The algorithm of this system was modeled in the simulation software package VISSIM using a slightly modified real-world scenario of interchange. The evaluation of the system starts with testing some key variables when market penetration rate is 100%. The results demonstrate that the increase in traffic demand and heavy vehicle percentage affects the performance of the NIC by increasing the delay. Although the effects of communication range and advance stop location do not have clear patterns, the communication range of 600 ft and ASL of 100 ft indicate a relatively lower delay. Throughput and delay results reveal that the NIC outperforms traffic signals when the market penetration rate is 75%, whereas a 25% market penetration rate provides similar performance to traffic signals.

Impact of Autonomous-Vehicle-Only Lanes in Mixed Traffic Conditions

2019 ◽  
Vol 2673 (9) ◽  
pp. 430-439 ◽  
Author(s):  
Hwapyeong Yu ◽  
Sehyun Tak ◽  
Minju Park ◽  
Hwasoo Yeo
Keyword(s):  
Autonomous Vehicles ◽  
Road Traffic ◽  
Positive Impact ◽  
Penetration Rate ◽  
Autonomous Vehicle ◽  
Market Penetration ◽  
Mixed Traffic ◽  
Negative Effects ◽  
Average Speed ◽  
Time To Collision

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.

scholarly journals High-Resolution Traffic Sensing with Probe Autonomous Vehicles: A Data-Driven Approach

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 464
Author(s):  
Wei Ma ◽  
Sean Qian
Keyword(s):  
High Resolution ◽  
Autonomous Vehicles ◽  
Penetration Rate ◽  
Data Driven ◽  
Traffic Information ◽  
Flow Density ◽  
Massive Data ◽  
Market Penetration ◽  
High Resolution Data ◽  
Data Driven Approach

Recent decades have witnessed the breakthrough of autonomous vehicles (AVs), and the sensing capabilities of AVs have been dramatically improved. Various sensors installed on AVs will be collecting massive data and perceiving the surrounding traffic continuously. In fact, a fleet of AVs can serve as floating (or probe) sensors, which can be utilized to infer traffic information while cruising around the roadway networks. Unlike conventional traffic sensing methods relying on fixed location sensors or moving sensors that acquire only the information of their carrying vehicle, this paper leverages data from AVs carrying sensors for not only the information of the AVs, but also the characteristics of the surrounding traffic. A high-resolution data-driven traffic sensing framework is proposed, which estimates the fundamental traffic state characteristics, namely, flow, density and speed in high spatio-temporal resolutions and of each lane on a general road, and it is developed under different levels of AV perception capabilities and for any AV market penetration rate. Experimental results show that the proposed method achieves high accuracy even with a low AV market penetration rate. This study would help policymakers and private sectors (e.g., Waymo) to understand the values of massive data collected by AVs in traffic operation and management.

scholarly journals Analysis of highway performance under mixed connected and regular vehicle environment

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhao Zhang ◽  
Xianfeng (Terry) Yang
Keyword(s):  
Penetration Rate ◽  
Evaluation Criteria ◽  
Speed Control ◽  
Operational Performance ◽  
Connected Vehicle ◽  
Mixed Traffic ◽  
Highway Capacity ◽  
Content Type ◽  
Traffic Demand ◽  
Traffic Pattern

Purpose This study aims to study the connected vehicle (CV) impact on highway operational performance under a mixed CV and regular vehicle (RV) environment. Design/methodology/approach The authors implemented a mixed traffic flow model, along with a CV speed control model, in the simulation environment. According to the different traffic characteristics between CVs and RVs, this research first analyzed how the operation of CVs can affect highway capacity under both one-lane and multi-lane cases. A hypothesis was then made that there shall exist a critical CV penetration rate that can significantly show the benefit of CV to the overall traffic. To prove this concept, this study simulated the mixed traffic pattern under various conditions. Findings The results of this research revealed that performing optimal speed control to CVs will concurrently benefit RVs by improving highway capacity. Furthermore, a critical CV penetration rate should exist at a specified traffic demand level, which can significantly reduce the speed difference between RVs and CVs. The results offer effective insight to understand the potential impacts of different CV penetration rates on highway operation performance. Originality/value This approach assumes that there shall exist a critical CV penetration rate that can maximize the benefits of CV implementations. CV penetration rate (the proportion of CVs in mixed traffic) is the key factor affecting the impacts of CV on freeway operational performance. The evaluation criteria for freeway operational performance are using average travel time under different given traffic demand patterns.

scholarly journals Impacts of Autonomous Vehicles on Traffic Flow Characteristics under Mixed Traffic Environment: Future Perspectives

2021 ◽  
Vol 13 (19) ◽  
pp. 11052
Author(s):  
Mohammed Al-Turki ◽  
Nedal T. Ratrout ◽  
Syed Masiur Rahman ◽  
Imran Reza
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Penetration Rate ◽  
Flow Characteristics ◽  
Driving Behavior ◽  
Mixed Traffic ◽  
Traffic Characteristics ◽  
Traffic Environment ◽  
Traffic Flow Characteristics ◽  
The Impact

Vehicle automation and communication technologies are considered promising approaches to improve operational driving behavior. The expected gradual implementation of autonomous vehicles (AVs) shortly will cause unique impacts on the traffic flow characteristics. This paper focuses on reviewing the expected impacts under a mixed traffic environment of AVs and regular vehicles (RVs) considering different AV characteristics. The paper includes a policy implication discussion for possible actual future practice and research interests. The AV implementation has positive impacts on the traffic flow, such as improved traffic capacity and stability. However, the impact depends on the factors including penetration rate of the AVs, characteristics, and operational settings of the AVs, traffic volume level, and human driving behavior. The critical penetration rate, which has a high potential to improve traffic characteristics, was higher than 40%. AV’s intelligent control of operational driving is a function of its operational settings, mainly car-following modeling. Different adjustments of these settings may improve some traffic flow parameters and may deteriorate others. The position and distribution of AVs and the type of their leading or following vehicles may play a role in maximizing their impacts.

Driver Behavior at a Freeway Merge to Mixed Traffic of Conventional and Connected Autonomous Vehicles

2020 ◽  
Vol 2674 (11) ◽  
pp. 867-874
Author(s):  
Sneha Chityala ◽  
John O. Sobanjo ◽  
Eren Erman Ozguven ◽  
Thobias Sando ◽  
Richard Twumasi-Boakye
Keyword(s):  
Autonomous Vehicles ◽  
Driving Simulator ◽  
The Elderly ◽  
Market Penetration ◽  
Mixed Traffic ◽  
Traffic Operations ◽  
Freeway Traffic ◽  
Elderly Drivers ◽  
Young Drivers ◽  
The Subject

Freeway merge ramps serve as one of the most challenging areas in traffic operations. This paper primarily focuses on creating a mixed traffic of conventional and connected/autonomous vehicles (CAVs) on freeways, and capturing driver behaviors both for the merging vehicle on the ramp and the freeway vehicles. The mixed distribution of vehicle headways of the freeway vehicles, developed based on various market penetration rates of the CAVs, was used to randomly generate vehicles through Monte Carlo simulation, and assigned as headways in a driving simulator. Based on perception, young drivers on the merge ramp were observed to choose critical headway gaps of 2.9 s, 1.8 s, and 1.7 s for freeway traffic of 0%, 50%, 75% penetration rates, respectively. For similar CAV penetration rates, the critical gaps observed for elderly drivers were 3.5 s, 2.0 s, and 1.9 s, respectively. When actually driving in the simulator, for the scenarios of 0% CAVs and 50% CAVs on the freeway, the values of average headway gaps accepted by young drivers were estimated as 2.36 s and 1.53 s, respectively. For the elderly drivers driving the simulator, the average headway gap values accepted were estimated as 2.72 s and 1.55 s, respectively, in the 0% and 50% penetration rates on the freeway traffic. Analyses of the speed profiles of the vehicles showed the effects of the acceleration/deceleration of merging vehicles, for both young and older drivers, on the freeway vehicles, including a few cases of collision. Overall, it was observed that the subject drivers accepted shorter headway gaps for increased CAV penetration levels.

scholarly journals Traffic Equilibrium for Mixed Traffic Flows of Human-Driven Vehicles and Connected and Autonomous Vehicles in Transportation Networks under Tradable Credit Scheme

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Fang Zhang ◽  
Jian Lu ◽  
Xiaojian Hu
Keyword(s):  
Autonomous Vehicles ◽  
Network Performance ◽  
Penetration Rate ◽  
User Equilibrium ◽  
Unit Price ◽  
Mixed Traffic ◽  
Traffic Flows ◽  
Stochastic User Equilibrium ◽  
Tradable Credit Scheme ◽  
Tradable Credit

In this paper, the traffic equilibriums for mixed traffic flows of human-driven vehicles (HDV) and connected and autonomous vehicles (CAV) under a tradable credit scheme (TCS) are established and formulated as two variational inequality (VI) problems with exogenous and endogenous CAV penetration rate, respectively. A modified Lagrangian dual (MLD) method embedded with a revised Smith’s route-swapping (RSRS) algorithm is proposed to solve the problems. Based on the numerical analysis, the impacts of CAV penetration and the extra expense of using a CAV on network performance are investigated. A novel driveway management, autonomous vehicle/credit charge (AVCC) link, is put forward to improve the efficiency of TCS. Under the TCS with exogenous CAV penetration rate, a logit-based model is applied to describe the stochastic user equilibrium for mixed traffic flow. It is found that the penetration of CAV gives rise to a better network performance and it can be further improved by the deployment of AVCC link. Under the TCS with endogenous penetration rate, a nested-logit model is applied to describe travelers’ choices of vehicle types and routes. It is found that the deployment of AVCC links can slow down the decline rate of CAV penetration with increasing expense and thus ensure a lower average travel time for CAVs. In both cases, the deployment of AVCC links can stimulate credit trading and drop down its unit price.

scholarly journals Freeway Traffic Speed Estimation of Mixed Traffic Using Data from Connected and Autonomous Vehicles with a Low Penetration Rate

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Shanglu He ◽  
Xiaoyu Guo ◽  
Fan Ding ◽  
Yong Qi ◽  
Tao Chen
Keyword(s):  
Small Proportion ◽  
Autonomous Vehicles ◽  
Penetration Rate ◽  
Estimation Accuracy ◽  
Distribution Data ◽  
Speed Estimation ◽  
Mixed Traffic ◽  
Fundamental Diagram ◽  
Using Data ◽  
The Impact

Connected and autonomous vehicles (CAVs) are on the way to the field application. In the beginning stage, there will be a mixed traffic flow, containing the regular human-driven vehicles and CAVs with a low penetration rate. Recently, the discussion about the impact of a small proportion of CAVs in the mixed traffic is controversial. This paper investigated the possibility of applying the limited data from these lowly penetrated CAVs to estimate the average freeway link speeds based on the Kalman filtering (KF) method. First, this paper established a VISSIM-based microsimulation model to mimic the mixed traffic with different CAV penetration rates. The characteristics of this mixed traffic were then discussed based on the simulation data, including the sample size distribution, data-missing rate, speed difference, and fundamental diagram. Accordingly, the traditional KF-based method was introduced and modified to adapt data from CAVs. Finally, the evaluations of the estimation accuracy and the sensitive analysis of the proposed method were conducted. The results revealed the possibility and applicability of link speed estimation using data from a small proportion of CAVs.

scholarly journals City-Wide Eco-Routing Navigation Considering Vehicular Communication Impacts

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 290 ◽  
Author(s):  
Ahmed Elbery ◽  
Hesham Rakha
Keyword(s):  
System Performance ◽  
Large Scale ◽  
Penetration Rate ◽  
Transportation Systems ◽  
Pollutant Emissions ◽  
Market Penetration ◽  
Vehicular Communication ◽  
Traffic Demand ◽  
Realistic Communication ◽  
The Impact

Intelligent Transportation Systems (ITSs) utilize Vehicular Ad-hoc Networks (VANETs) to collect, disseminate, and share data with the Traffic Management Center (TMC) and different actuators. Consequently, packet drop and delay in VANETs can significantly impact ITS performance. Feedback-based eco-routing (FB-ECO) is a promising ITS technology, which is expected to reduce vehicle fuel/energy consumption and pollutant emissions by routing drivers through the most environmentally friendly routes. To compute these routes, the FB-ECO utilizes VANET communication to update link costs in real-time, based on the experiences of other vehicles in the system. In this paper, we study the impact of vehicular communication on FB-ECO navigation performance in a large-scale real network with realistic calibrated traffic demand data. We conduct this study at different market penetration rates and different congestion levels. We start by conducting a sensitivity analysis of the market penetration rate on the FB-ECO system performance, and its network-wide impacts considering ideal communication. Subsequently, we study the impact of the communication network on system performance for different market penetration levels, considering the communication system. The results demonstrate that, for market penetration levels less than 30%, the eco-routing system performs adequately in both the ideal and realistic communication scenarios. It also shows that, for realistic communication, increasing the market penetration rate results in a network-wide degradation of the system performance.

Estimating Pedestrian Impact on Coordination of Urban Corridors

2019 ◽  
Vol 2673 (7) ◽  
pp. 265-280 ◽  
Author(s):  
Sharmin-E-Shams Chowdhury ◽  
Aleksandar Stevanovic ◽  
Nikola Mitrovic
Keyword(s):  
Cycle Length ◽  
Network Performance ◽  
Traffic Signals ◽  
High Fidelity ◽  
Vehicular Traffic ◽  
Traffic Demand ◽  
Advantages And Disadvantages ◽  
Street Traffic ◽  
Pedestrian Impact ◽  
Signal Operations

Pedestrian walk timings at most U.S. traffic signals are run in concurrence with relevant signal phases for vehicular traffic. This usually means that signal operations coordinated for the major street can be interrupted by a pedestrian call. Such an interruption may in practice last for a few minutes, thus causing increased delays and stops for major traffic flows. An alternative to this design is to increase the cycle length and embed pedestrian timings within the ring-barrier structure of the prevailing coordination plan. Both approaches have advantages and disadvantages. A fresh approach offered by this study is a comprehensive experimental design and holistic performance evaluation perspectives. The study examines the two abovementioned treatments of pedestrian timings for a small corridor of five intersections in Utah. The experiments have been done in a high-fidelity microsimulation environment with the Software-in-the-Loop version of the field controller (Econolite ASC/3). Findings show that either approach works well for very low traffic demands. When the traffic demand increases findings cannot be generalized as they differ for major coordinated movements versus overall network performance. While major-street traffic prefers no interruption of the coordinated operations, the overall network performance is better in the other case. This can be explained by the fact that avoiding interruptions is usually achieved at the expense of longer cycle length, which increases delay for everyone in the network.

Pricing of Connected and Autonomous Vehicles in Mixed-Traffic Networks

2021 ◽  
pp. 036119812098585
Author(s):  
Paolo Delle Site
Keyword(s):  
Autonomous Vehicles ◽  
Marginal Cost ◽  
User Behavior ◽  
Social Planner ◽  
Traffic Networks ◽  
Mixed Traffic ◽  
The Third ◽  
First Case ◽  
Marginal Cost Pricing ◽  
The Social

For networks with human-driven vehicles (HDVs) only, pricing with arc-specific tolls has been proposed to achieve minimization of travel times in a decentralized way. However, the policy is hardly feasible from a technical viewpoint without connectivity. Therefore, for networks with mixed traffic of HDVs and connected and autonomous vehicles (CAVs), this paper considers pricing in a scenario where only CAVs are charged. In contrast to HDVs, CAVs can be managed as individual vehicles or as a fleet. In the latter case, CAVs can be routed to minimize the travel time of the fleet of CAVs or that of the entire fleet of HDVs and CAVs. We have a selfish user behavior in the first case, a private monopolist behavior in the second, a social planner behavior in the third. Pricing achieves in a decentralized way the social planner optimum. Tolls are not unique and can take both positive and negative values. Marginal cost pricing is one solution. The valid toll set is provided, and tolls are then computed according to two schemes: one with positive tolls only and minimum toll expenditure, and one with both tolls and subsidies and zero net expenditure. Convergent algorithms are used for the mixed-behavior equilibrium (simplicial decomposition algorithm) and toll determination (cutting plane algorithm). The computational experience with three networks: a two-arc network representative of the classic town bypass case, the Nguyen-Dupuis network, and the Anaheim network, provides useful policy insight.

Sign in / Sign up

Export Citation Format

Share Document