scholarly journals An autonomous vehicle sequencing problem at intersections: A genetic algorithm approach

2013 ◽  
Vol 23 (1) ◽  
pp. 183-200 ◽  
Author(s):  
Fei Yan ◽  
Mahjoub Dridi ◽  
Abdellah El Moudni
Keyword(s):  
Genetic Algorithm ◽  
Traffic Control ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Control Methods ◽  
Traffic Condition ◽  
Sequencing Problem ◽  
Genetic Algorithm Approach ◽  
Short Time ◽  
Intersection Management

This paper addresses a vehicle sequencing problem for adjacent intersections under the framework of Autonomous Intersection Management (AIM). In the context of AIM, autonomous vehicles are considered to be independent individuals and the traffic control aims at deciding on an efficient vehicle passing sequence. Since there are considerable vehicle passing combinations, how to find an efficient vehicle passing sequence in a short time becomes a big challenge, especially for more than one intersection. In this paper, we present a technique for combining certain vehicles into some basic groups with reference to some properties discussed in our earlier works. A genetic algorithm based on these basic groups is designed to find an optimal or a near-optimal vehicle passing sequence for each intersection. Computational experiments verify that the proposed genetic algorithms can response quickly for several intersections. Simulations with continuous vehicles are carried out with application of the proposed algorithm or existing traffic control methods. The results show that the traffic condition can be significantly improved by our algorithm.

scholarly journals Performance Analysis of NDT-based Graph SLAM for Autonomous Vehicle in Diverse Typical Driving Scenarios of Hong Kong

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3928 ◽  
Author(s):  
Weisong Wen ◽  
Li-Ta Hsu ◽  
Guohao Zhang
Keyword(s):  
New York ◽  
Hong Kong ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Tall Buildings ◽  
Point Clouds ◽  
Reliability Estimation ◽  
Traffic Condition ◽  
Localization And Mapping ◽  
Graph Slam

Robust and lane-level positioning is essential for autonomous vehicles. As an irreplaceable sensor, Light detection and ranging (LiDAR) can provide continuous and high-frequency pose estimation by means of mapping, on condition that enough environment features are available. The error of mapping can accumulate over time. Therefore, LiDAR is usually integrated with other sensors. In diverse urban scenarios, the environment feature availability relies heavily on the traffic (moving and static objects) and the degree of urbanization. Common LiDAR-based simultaneous localization and mapping (SLAM) demonstrations tend to be studied in light traffic and less urbanized area. However, its performance can be severely challenged in deep urbanized cities, such as Hong Kong, Tokyo, and New York with dense traffic and tall buildings. This paper proposes to analyze the performance of standalone NDT-based graph SLAM and its reliability estimation in diverse urban scenarios to further evaluate the relationship between the performance of LiDAR-based SLAM and scenario conditions. The normal distribution transform (NDT) is employed to calculate the transformation between frames of point clouds. Then, the LiDAR odometry is performed based on the calculated continuous transformation. The state-of-the-art graph-based optimization is used to integrate the LiDAR odometry measurements to implement optimization. The 3D building models are generated and the definition of the degree of urbanization based on Skyplot is proposed. Experiments are implemented in different scenarios with different degrees of urbanization and traffic conditions. The results show that the performance of the LiDAR-based SLAM using NDT is strongly related to the traffic condition and degree of urbanization. The best performance is achieved in the sparse area with normal traffic and the worse performance is obtained in dense urban area with 3D positioning error (summation of horizontal and vertical) gradients of 0.024 m/s and 0.189 m/s, respectively. The analyzed results can be a comprehensive benchmark for evaluating the performance of standalone NDT-based graph SLAM in diverse scenarios which is significant for multi-sensor fusion of autonomous vehicle.

scholarly journals Novel Routing Algorithm for Autonomous Vehicles in Smart Transportation System

2021 ◽  
Vol 3 (3) ◽  
pp. 164-179
Author(s):  
Haoxiang Wang
Keyword(s):  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Intelligent Transportation System ◽  
Autonomous Vehicle ◽  
Routing Algorithm ◽  
Transportation System ◽  
Traffic Condition ◽  
Smart Transportation ◽  
Centralized Management ◽  
The City

In recent times Automation is emerging every day and bloomed in every sector. Intelligent Transportation System (ITS) is one of the important branches of Automation. The major constrain in the transportation system is traffic congestion. This slurps the individual’s time and consequently pollutes the environment. A centralized management is required for optimizing the transportation system. The current traffic condition is predicted by evaluating the historical data and thereby it reduces the traffic congestion. The periodic update of traffic condition in each and every street of the city is obtained and the data is transferred to the autonomous vehicle. These data are obtained from the simulation results of transportation prediction tool SUMO. It is proved that our proposed work reduces the traffic congestion and maintains ease traffic flow and preserves the fleet management.

Optimal Placement of Reservation-Based Intersections in Urban Networks

2019 ◽  
Vol 2673 (10) ◽  
pp. 781-792
Author(s):  
Rahul Patel ◽  
Prashanth Venkatraman ◽  
Stephen D. Boyles
Keyword(s):  
Genetic Algorithm ◽  
Traffic Control ◽  
Autonomous Vehicles ◽  
Large City ◽  
Ranking Method ◽  
Optimal Placement ◽  
Total System ◽  
Travel Times ◽  
Urban Networks ◽  
High Performing

Reservation-based traffic control is a revolutionary intersection management system which involves the communication of autonomous vehicles and an intersection to request space-time trajectories through the intersection. Although previous studies have found congestion and throughput benefits of reservation-based control that surpass signalized control, other studies have found negative impacts at peak travel times. The main purpose of this paper is to find and characterize favorable mixed configurations of reservation-based controls and signalized controls in a large city network which minimize total system travel times. As this optimization problem is bi-level and challenging, three different methods are proposed to heuristically find effective mixed configurations. The first method is an intersection ranking method that uses simulation to assign a score to each intersection in a network based on localized potential benefit to system travel time under reservation control and then ranks all intersections accordingly. The second is another ranking method; however, it uses linear regression to predict an intersection’s localized score. Finally, a genetic algorithm is presented that iteratively approaches high-performing network configurations yielding minimal system travel times. The methods were tested on the downtown Austin network and configurations found that are less than half controlled by reservation intersections that improve travel times beyond an all-reservation controlled network. Overall, the results show that the genetic algorithm finds the best performing configurations, with the initial score-assigning ranking method performing similarly but much more efficiently. It was finally find that favorable reservation placement is in consecutive chains along highly trafficked corridors.

scholarly journals Intelligently managing mixed traffic flows at intersections Proposal of a platoon-based round-robin algorithm with priorities

2021 ◽  
Author(s):  
Hossein Moradi ◽  
Sara Sasaninejad ◽  
Sabine Wittevrongel ◽  
Joris Walraevens
Keyword(s):  
Traffic Control ◽  
Autonomous Vehicles ◽  
State Of The Art ◽  
Control Methods ◽  
Mixed Traffic ◽  
Traffic Flows ◽  
Traffic Conditions ◽  
Advisory System ◽  
Intersection Control ◽  
Integration Effort

<p>The importance of addressing the complexities of mixed traffic conditions by providing innovative approaches, models, and algorithms for traffic control has been well highlighted in the state-of-the-art literature. Accordingly, the first aim of this study has been to enhance the traditional intersection control methods for the incorporation of autonomous vehicles and wireless communications. For this purpose, we have introduced a novel framework labeled by “PRRP-framework”. The PRRP-framework also enables flexible preferential treatments for some special vehicles within an implementable range of complexity while it addresses the stochastic nature of traffic flow. Moreover, the PRRP-framework has been coupled with a speed advisory system that brings complementary strengths leading to even better performance. Further simulations reported in this manuscript, confirmed that such an integration effort is a prerequisite to move towards sustainable results.<br></p> <p> </p>

scholarly journals Combining a Genetic Algorithm and a Fuzzy System to Optimize User Centricity in Autonomous Vehicle Concept Development

Systems ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 25
Author(s):  
Ferdinand Schockenhoff ◽  
Maximilian Zähringer ◽  
Matthias Brönner ◽  
Markus Lienkamp
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy System ◽  
Autonomous Vehicles ◽  
Methodological Approach ◽  
Autonomous Vehicle ◽  
Concept Development ◽  
User Needs ◽  
Vehicle Concept ◽  
Entire Vehicle ◽  
User Centered

The megatrends of individualization and sharing will dramatically change our consumer behavior. The needs of a product’s users will be central input for its development. Current development processes are not suitable for this product development; thus, we propose a combination of a genetic algorithm and a fuzzy system for user-centered development. We execute our new methodological approach on the example of autonomous vehicle concepts to demonstrate its implementation and functionality. The genetic algorithm minimizes the required number of vehicle concepts to satisfy the mobility needs of a user group, and the fuzzy system transfers user needs into vehicle-related properties, which are currently input for vehicle concept development. To present this method, we use a typical family and their potential mobility behavior. Our method optimizes their minimal number of vehicle concepts to satisfy all mobility needs and derives the properties of the vehicle concepts. By integrating our method into the entire vehicle concept development process, autonomous vehicles can be designed user-centered in the context of the megatrends of individualization and sharing. In summary, our method enables us to derive an optimized number of products for qualitatively described, heterogeneous user needs and determine their product-related properties.

scholarly journals The Autonomous Shopping-Guide Robot in Cashier-Less Convenience Stores

2020 ◽  
Vol 14 ◽  
pp. 09-15
Author(s):  
Po-Han Lin ◽  
Cheng-Yi Lin ◽  
Chen-Ting Hung ◽  
Jen-Jee Chen ◽  
Jia-Ming Liang
Keyword(s):  
Genetic Algorithm ◽  
Traffic Control ◽  
Route Planning ◽  
Tag Identification ◽  
Traffic Condition ◽  
Shopping Cart ◽  
Shopping List ◽  
Convenience Stores ◽  
Shopping Experience ◽  
Dynamic Route

In recent years, several cashier-less convenience stores have appeared, including Amazon’s. A store without cashiers will become a trend in the near future. To substitute the employee in traditional stores, this research proposes and designs an autonomous shopping cart robot to guide customers’ purchase according to the requested shopping list to enhance their shopping experience. The core techniques of the system are the autonomous driving robot, the traffic control center for robots and the dynamic route planning algorithm. The robot is a self-propelled vehicle developed by ROS (Robot Operating System), in which we achieve the automatic driving via image recognition, April tag identification and driving direction guidance from the path planning and traffic control services. This enables the robot to lead customers to find their commodities following the preplanned route. In conjunction with the vocal service, the robot can notify the customer when arriving at each commodity, he or she plans to buy. We also design a light APP for customers to easily set up and manage their shopping list, call for the robotic shopping cart’s help, and interact with the shopping cart robot. To enhance the shopping experience of customers, we design the dynamic route planning genetic algorithm to dynamically plan the shopping route according to the customer’s request and the traffic condition. Experiments show that our genetic algorithm can provide the most stable performance and always get efficient shopping route planning in a limited time compared to other methods.

scholarly journals Intelligently managing mixed traffic flows at intersections Proposal of a platoon-based round-robin algorithm with priorities

2021 ◽  
Author(s):  
Hossein Moradi ◽  
Sara Sasaninejad ◽  
Sabine Wittevrongel ◽  
Joris Walraevens
Keyword(s):  
Traffic Control ◽  
Autonomous Vehicles ◽  
State Of The Art ◽  
Control Methods ◽  
Mixed Traffic ◽  
Traffic Flows ◽  
Traffic Conditions ◽  
Advisory System ◽  
Intersection Control ◽  
Integration Effort

<p>The importance of addressing the complexities of mixed traffic conditions by providing innovative approaches, models, and algorithms for traffic control has been well highlighted in the state-of-the-art literature. Accordingly, the first aim of this study has been to enhance the traditional intersection control methods for the incorporation of autonomous vehicles and wireless communications. For this purpose, we have introduced a novel framework labeled by “PRRP-framework”. The PRRP-framework also enables flexible preferential treatments for some special vehicles within an implementable range of complexity while it addresses the stochastic nature of traffic flow. Moreover, the PRRP-framework has been coupled with a speed advisory system that brings complementary strengths leading to even better performance. Further simulations reported in this manuscript, confirmed that such an integration effort is a prerequisite to move towards sustainable results.<br></p> <p> </p>

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