scholarly journals Safety Evaluation for Connected and Autonomous Vehicles’ Exclusive Lanes considering Penetrate Ratios and Impact of Trucks Using Surrogate Safety Measures

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Jian Zhang ◽  
Kunrun Wu ◽  
Min Cheng ◽  
Min Yang ◽  
Yang Cheng ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Safety Evaluation ◽  
Driver Model ◽  
Microscopic Simulation ◽  
Safety Measures ◽  
Traffic Efficiency ◽  
Safety Improvement ◽  
Demand Scenario ◽  
Surrogate Safety Measures

Plenty of studies on exclusive lanes for Connected and Autonomous Vehicle (CAV) have been conducted recently about traffic efficiency and safety. However, most of the previous research studies neglected comprehensive consideration of the safety impact on different market penetration rates (MPRs) of CAVs, traffic demands, and proportion of trucks in mixture CAVs with human’s driven vehicle environment. On this basis, this study is to (1) identify the safety impact on exclusive lanes for CAVs under different MPRs with different traffic demands and (2) investigate the safety impact of trucks for CAV exclusive lanes on mixture environment. Based on the Intelligent Driver Model (IDM), a CAV platooning control algorithm is proposed for modeling the driving behaviors of CAVs. A calibrated 7-kilometer freeway section microscopic simulation environment is built by VISSIM. Four surrogate safety measures, including both longitudinal and lateral safety risk indexes, are employed to evaluate the overall safety impacts of setting exclusive lanes. Main results indicate that (1) setting one exclusive lane is capable to improve overall safety environment in low demand, and two exclusive lanes are more suitable for high-demand scenario; (2) existence of trucks worsens overall longitudinal safety environment, and improper setting of exclusive lanes in high trucks, low MPR scenario has adverse effect on longitudinal safety; and (3) setting exclusive lanes have better longitudinal and lateral safety improvement in high-truck proportion scenarios. Setting one or two exclusive lanes led to [+42.4% to −52.90%] and [+45.7% to −55.2%] of longitudinal risks while [−1.8% to −87.1%] and [−2.1% to −85.3%] of lateral conflicts compared with the base scenario, respectively. Results of this study provide useful insight for the setting of exclusive lanes for CAVs in a mixture environment.

scholarly journals Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Mark Mario Morando ◽  
Qingyun Tian ◽  
Long T. Truong ◽  
Hai L. Vu
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Assessment Model ◽  
Traffic Crashes ◽  
Safety Measures ◽  
High Penetration ◽  
Simulation Based ◽  
Car Following Model ◽  
Surrogate Safety Measures ◽  
Signalised Intersection

Autonomous vehicle (AV) technology has advanced rapidly in recent years with some automated features already available in vehicles on the market. AVs are expected to reduce traffic crashes as the majority of crashes are related to driver errors, fatigue, alcohol, or drugs. However, very little research has been conducted to estimate the safety impact of AVs. This paper aims to investigate the safety impacts of AVs using a simulation-based surrogate safety measure approach. To this end, safety impacts are explored through the number of conflicts extracted from the VISSIM traffic microsimulator using the Surrogate Safety Assessment Model (SSAM). Behaviours of human-driven vehicles (HVs) and AVs (level 4 automation) are modelled within the VISSIM’s car-following model. The safety investigation is conducted for two case studies, that is, a signalised intersection and a roundabout, under various AV penetration rates. Results suggest that AVs improve safety significantly with high penetration rates, even when they travel with shorter headways to improve road capacity and reduce delay. For the signalised intersection, AVs reduce the number of conflicts by 20% to 65% with the AV penetration rates of between 50% and 100% (statistically significant at p<0.05). For the roundabout, the number of conflicts is reduced by 29% to 64% with the 100% AV penetration rate (statistically significant at p<0.05).

scholarly journals PEDESTRIAN SAFETY EVALUATION OF SIGNALIZED INTERSECTIONS USING SURROGATE SAFETY MEASURES

Transport ◽  
2020 ◽  
Vol 35 (1) ◽  
pp. 48-56
Author(s):  
Sankaran Marisamynathan ◽  
Perumal Vedagiri
Keyword(s):  
Safety Evaluation ◽  
Pedestrian Safety ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Mixed Traffic ◽  
Model Framework ◽  
Safety Measures ◽  
Severity Level ◽  
Traffic Conditions ◽  
Surrogate Safety Measures

The large proportions of pedestrian fatalities led researchers to make the improvements of pedestrian safety at intersections. Thus, this paper proposes a methodology to evaluate crosswalk safety at signalized intersections using Surrogate Safety Measures (SSM) under mixed traffic conditions. The required pedestrian, traffic, and geometric data were extracted based on the videographic survey conducted at signalized intersections in Mumbai (India). Post Encroachment Time (PET) for each pedestrian were segregated into three categories for estimating pedestrian–vehicle interactions and Cumulative Frequency Distribution (CDF) was plotted to calculate the threshold values for each interaction severity level. The Cumulative Logistic Regression (CLR) model was developed to predict the pedestrian mean PET values in the cross-walk at signalized intersections. The proposed model was validated with a new signalized intersection and the results were shown that the proposed PET ranges and model appropriate for Indian mixed traffic conditions. To assess the suitability of model framework, model transferability was carried out with data collected at signalized intersection in Kolkata (India). Finally, this study can be helpful to rank the severity level of pedestrian safety in the crosswalk and improve the existing facilities at signalized intersections.

scholarly journals Assessment of the Speed Management Impact on Road Traffic Safety on the Sections of Motorways and Expressways Using Simulation Methods

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5057
Author(s):  
Jacek Oskarbski ◽  
Tomasz Kamiński ◽  
Kyandoghere Kyamakya ◽  
Jean Chamberlain Chedjou ◽  
Karol Żarski ◽  
...  
Keyword(s):  
Road Safety ◽  
Driving Simulator ◽  
Intelligent Transport System ◽  
Variable Speed ◽  
Speed Limits ◽  
Safety Measures ◽  
Traffic Models ◽  
Traffic Efficiency ◽  
Variable Speed Limits ◽  
Surrogate Safety Measures

Methods used to evaluate the impact of Intelligent Transport System (ITS) services on road safety are usually based on expert assessments or statistical studies. However, commonly used methods are challenging to apply in the planning process of ITS services. This paper presents the methodology of research using surrogate safety measures calculated and calibrated with the use of simulation techniques and a driving simulator. This approach supports the choice of the type of ITS services that are beneficial for traffic efficiency and road safety. This paper presents results of research on the influence of selected scenarios of variable speed limits on the efficiency and safety of traffic on the sections of motorways and expressways in various traffic conditions. The driving simulator was used to estimate the efficiency of lane-keeping by the driver. The simulation traffic models were calibrated using driving simulator data and roadside sensor data. The traffic models made it possible to determine surrogate safety measures (number of conflicts and their severity) in selected scenarios of using ITS services. The presented studies confirmed the positive impact of Variable Speed Limits (VSLs) on the level of road safety and traffic efficiency. This paper also presents recommendations and plans for further research in this area.

Modeling and Characterization of Driving Styles for Adaptive Cruise Control in Personalized Autonomous Vehicles

2017 ◽  
Author(s):  
Drew Bolduc ◽  
Longxiang Guo ◽  
Yunyi Jia
Keyword(s):  
Autonomous Vehicles ◽  
Adaptive Cruise Control ◽  
Research Effort ◽  
Autonomous Vehicle ◽  
Individual Preference ◽  
Driver Model ◽  
Cruise Control ◽  
Critical Function ◽  
Driving Style ◽  
Safety And Reliability

For autonomous vehicles to gain widespread customer acceptance, safety and reliability are not nearly enough. Comfort and familiarity of the ride is also of essential importance. Because these are highly subjective factors, autonomous vehicles must be able to adopt personal driving styles to meet individual preference. The adaptive cruise control (ACC) system is a critical function performed by the autonomous vehicle and much research effort has been devoted to the development of a system that acts as a human driver. However, studies which investigate ACC models capable of learning a driving style are limited. In this paper, we propose a method to extract quantifiable parameters which represent a drivers’ driving style and apply these parameters to personalize the longitudinal control of an autonomous vehicle. We then develop a longitudinal driver model that integrates those parameters to enable the ACC system to mimic the driving style of the driver. Finally, the effectiveness of the extraction method and the driver model are obtained through simulation.

Optimization of lane-changing advisory of connected and autonomous vehicles at a multi-lane work zone

2021 ◽  
pp. 2250020
Author(s):  
Wenjing Wu ◽  
Yongbin Zhan ◽  
Lili Yang ◽  
Renchao Sun ◽  
Anning Ni
Keyword(s):  
Autonomous Vehicles ◽  
Control Strategies ◽  
Autonomous Vehicle ◽  
Heterogeneous Traffic ◽  
Work Zone ◽  
Lane Changing ◽  
The Road ◽  
Traffic Efficiency ◽  
Traffic Distribution ◽  
Traffic Performance

The work zone with lane closure will be an active bottleneck due to vehicles’ mandatory lane-changing conflicts. The emerging Connected Autonomous Vehicle (CAV) technology provides opportunities for vehicle motion planning to improve traffic performance. However, the literature using CAV technology mainly focuses on single-lane lane-changing control in the merging area. The algorithm dealing with multi-lane lane-changing control is absent. In this paper, a simulation system with a lane-changing optimal strategy embedded for the multi-lane work zone is presented under the heterogeneous traffic flow. First, the road upstream of the work zone is divided into several segments, and an optimal multi-lane lane-changing algorithm is designed. It is recommended that CAVs, on the closure lane and the merged lane, change lanes on each segment to balance traffic distribution and minimize traffic delay. Second, to validate the algorithm proposed, a typical three-lane freeway with one-lane closed for the work zone is researched, and the simulation platform based on cellular automata is developed. Third, the advantages of multi-lane control strategies are studied and discussed in traffic efficiency improvement and collision risk reduction by comparing previous lane-changing control algorithms.

Traffic Safety Evaluation of Uncontrolled Intersections using Surrogate Safety Measures under Mixed Traffic Conditions

2015 ◽  
Vol 2512 (1) ◽  
pp. 81-89 ◽  
Author(s):  
P. Vedagiri ◽  
Deepak V. Killi
Keyword(s):  
Traffic Safety ◽  
Safety Evaluation ◽  
Mixed Traffic ◽  
Safety Measures ◽  
Traffic Conditions ◽  
Management Measures ◽  
Large Populations ◽  
Accident Data ◽  
Surrogate Safety Measures ◽  
The Impact

In the developing world, with increases in population, the number of vehicles is increasing tremendously. Traffic safety on roads has become a major concern even with advancements in technology and infrastructure. Traffic safety assessments and accident prediction based on accident data is a reactive approach. There are known drawbacks related to the reliability of accident data, especially in developing countries with large populations, such as India. It is, however, unethical to wait for accidents to occur before drawing statistically accurate conclusions regarding safety impacts. To overcome this impediment, one needs to develop accurate models that rely on surrogate safety measures (SSMs) for effective safety evaluations. The main advantage associated with the use of these models is that they can model crashes more frequently than in the real world and thereby imply an efficient and more statistically reliable proximal measure of traffic safety. The objective of this study is to examine the impact of management measures on traffic safety at a three-arm uncontrolled intersection with the use of microsimulation modeling under mixed traffic conditions. This examination was done by developing a unique methodology of measuring one SSM, postencroachment time (PET). This paper describes improvement in the accuracy of crash predictions by proposing a methodology to calculate PET.

scholarly journals System, Design and Experimental Validation of Autonomous Vehicle in an Unconstrained Environment

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 5999
Author(s):  
Shoaib Azam ◽  
Farzeen Munir ◽  
Ahmad Muqeem Sheri ◽  
Joonmo Kim ◽  
Moongu Jeon
Keyword(s):  
Motion Planning ◽  
Obstacle Avoidance ◽  
Autonomous Vehicles ◽  
Experimental Validation ◽  
Autonomous Vehicle ◽  
Cost Effective ◽  
Longitudinal Control ◽  
Sensor Layer ◽  
Traffic Efficiency ◽  
Control Layer

In recent years, technological advancements have made a promising impact on the development of autonomous vehicles. The evolution of electric vehicles, development of state-of-the-art sensors, and advances in artificial intelligence have provided necessary tools for the academia and industry to develop the prototypes of autonomous vehicles that enhance the road safety and traffic efficiency. The increase in the deployment of sensors for the autonomous vehicle, make it less cost-effective to be utilized by the consumer. This work focuses on the development of full-stack autonomous vehicle using the limited amount of sensors suite. The architecture aspect of the autonomous vehicle is categorized into four layers that include sensor layer, perception layer, planning layer and control layer. In the sensor layer, the integration of exteroceptive and proprioceptive sensors on the autonomous vehicle are presented. The perception of the environment in term localization and detection using exteroceptive sensors are included in the perception layer. In the planning layer, algorithms for mission and motion planning are illustrated by incorporating the route information, velocity replanning and obstacle avoidance. The control layer constitutes lateral and longitudinal control for the autonomous vehicle. For the verification of the proposed system, the autonomous vehicle is tested in an unconstrained environment. The experimentation results show the efficacy of each module, including localization, object detection, mission and motion planning, obstacle avoidance, velocity replanning, lateral and longitudinal control. Further, in order to demonstrate the experimental validation and the application aspect of the autonomous vehicle, the proposed system is tested as an autonomous taxi service.

scholarly journals Unravelling the Impacts of Parameters on Surrogate Safety Measures for a Mixed Platoon

2020 ◽  
Vol 12 (23) ◽  
pp. 9955
Author(s):  
Fan Ding ◽  
Jiwan Jiang ◽  
Yang Zhou ◽  
Ran Yi ◽  
Huachun Tan
Keyword(s):  
Traffic Safety ◽  
Feedforward Control ◽  
Safety Evaluation ◽  
Evaluation Framework ◽  
Active Safety ◽  
Automated Vehicles ◽  
Safety Measures ◽  
Car Following ◽  
Surrogate Safety Measures ◽  
Connected Automated Vehicles

With the precedence of connected automated vehicles (CAVs), car-following control technology is a promising way to enhance traffic safety. Although a variety of research has been conducted to analyze the safety enhancement by CAV technology, the parametric impact on CAV technology has not been systematically explored. Hence, this paper analyzes the parametric impacts on surrogate safety measures (SSMs) for a mixed vehicular platoon via a two-level analysis structure. To construct the active safety evaluation framework, numerical simulations were constructed which can generate trajectories for different kind of vehicles while considering communication and vehicle dynamics characteristics. Based on the trajectories, we analyzed parametric impacts upon active safety on two different levels. On the microscopic level, parameters including controller dynamic characteristics and equilibrium time headway of car-following policies were analyzed, which aimed to capture local and aggregated driving behavior’s impact on the vehicle. On the macroscopic level, parameters incorporating market penetration rate (MPR), vehicle topology, and vehicle-to-vehicle environment were extensively investigated to evaluate their impacts on aggregated platoon level safety caused by inter-drivers’ behavioral differences. As indicated by simulation results, an automated vehicle (AV) suffering from degradation is a potentially unsafe component in platoon, due to the loss of a feedforward control mechanism. Hence, the introduction of connected automated vehicles (CAVs) only start showing benefits to platoon safety from about 20% CAV MPR in this study. Furthermore, the analysis on vehicle platoon topology suggests that arranging all CAVs at the front of a mixed platoon assists in enhancing platoon SSM performances.

scholarly journals Establishment and tracking control of trapezoidal steering wheel angle model for autonomous vehicles

2020 ◽  
Vol 17 (6) ◽  
pp. 172988142098278
Author(s):  
Haobin Jiang ◽  
Aoxue Li ◽  
Xinchen Zhou ◽  
Yue Yu
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Steering System ◽  
Free Play ◽  
Driver Model ◽  
Steering Wheel ◽  
Feature Points ◽  
Steering Control ◽  
Power Steering ◽  
Nonlinear Vehicle Model

Human drivers have rich and diverse driving characteristics on curved roads. Finding the characteristic quantities of the experienced drivers during curve driving and applying them to the steering control of autonomous vehicles is the research goal of this article. We first recruited 10 taxi drivers, 5 bus drivers, and 5 driving instructors as the representatives of experienced drivers and conducted a real car field experiment on six curves with different lengths and curvatures. After processing the collected driving data in the Frenet frame and considering the free play of a real car’s steering system, it was interesting to observe that the shape enclosed by steering wheel angles and the coordinate axis was a trapezoid. Then, we defined four feature points, four feature distances, and one feature steering wheel angle, and the trapezoidal steering wheel angle (TSWA) model was developed by backpropagation neural network with the inputs were vehicle speeds at four feature points, and road curvature and the outputs were feature distances and feature steering wheel angle. The comparisons between TSWA model and experienced drivers, model predictive control, and preview-based driver model showed that the proposed TSWA model can best reflect the steering features of experienced drivers. What is more, the concise expression and human-like characteristic of TSWA model make it easy to realize human-like steering control for autonomous vehicles. Lastly, an autonomous vehicle composed of a nonlinear vehicle model and electric power steering (EPS) system was established in Simulink, the steering wheel angles generated by TSWA model were tracked by EPS motor directly, and the results showed that the EPS system can track the steering angles with high accuracy at different vehicle speeds.

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