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Journal of Intelligent and Connected Vehicles
Number of Followers: 1

This is an Open Access Journal

Open Access journal
ISSN (Online) 2399-9802
Published by Emerald

[360 journals]

Investigating safety and liability of autonomous vehicles: Bayesian random
parameter ordered probit model analysis
- Authors: Quan Yuan , Xuecai Xu , Tao Wang , Yuzhi Chen
  Abstract: This study aims to investigate the safety and liability of autonomous vehicles (AVs), and identify the contributing factors quantitatively so as to provide potential insights on safety and liability of AVs. The actual crash data were obtained from California DMV and Sohu websites involved in collisions of AVs from 2015 to 2021 with 210 observations. The Bayesian random parameter ordered probit model was proposed to reflect the safety and liability of AVs, respectively, as well as accommodating the heterogeneity issue simultaneously. The findings show that day, location and crash type were significant factors of injury severity while location and crash reason were significant influencing the liability. The results provide meaningful countermeasures to support the policymakers or practitioners making strategies or regulations about AV safety and liability.
  Citation: Journal of Intelligent and Connected Vehicles
  PubDate: 2022-06-30
  DOI: 10.1108/JICV-04-2022-0012
  Issue No: Vol. ahead-of-print , No. ahead-of-print (2022)
SOTIF risk mitigation based on unified ODD monitoring for autonomous
vehicles
- Authors: Wenhao Yu , Jun Li , Li-Ming Peng , Xiong Xiong , Kai Yang , Hong Wang
  Abstract: The purpose of this paper is to design a unified operational design domain (ODD) monitoring framework for mitigating Safety of the Intended Functionality (SOTIF) risks triggered by vehicles exceeding ODD boundaries in complex traffic scenarios. A unified model of ODD monitoring is constructed, which consists of three modules: weather condition monitoring for unusual weather conditions, such as rain, snow and fog; vehicle behavior monitoring for abnormal vehicle behavior, such as traffic rule violations; and road condition monitoring for abnormal road conditions, such as road defects, unexpected obstacles and slippery roads. Additionally, the applications of the proposed unified ODD monitoring framework are demonstrated. The practicability and effectiveness of the proposed unified ODD monitoring framework for mitigating SOTIF risk are verified in the applications. First, the application of weather condition monitoring demonstrates that the autonomous vehicle can make a safe decision based on the performance degradation of Lidar on rainy days using the proposed monitoring framework. Second, the application of vehicle behavior monitoring demonstrates that the autonomous vehicle can properly adhere to traffic rules using the proposed monitoring framework. Third, the application of road condition monitoring demonstrates that the proposed unified ODD monitoring framework enables the ego vehicle to successfully monitor and avoid road defects. The value of this paper is that the proposed unified ODD monitoring framework establishes a new foundation for monitoring and mitigating SOTIF risks in complex traffic environments.
  Citation: Journal of Intelligent and Connected Vehicles
  PubDate: 2022-06-28
  DOI: 10.1108/JICV-04-2022-0015
  Issue No: Vol. ahead-of-print , No. ahead-of-print (2022)
Optimal control of automated left-turn platoon at contraflow left-turn
lane intersections
- Authors: Hanyu Yang , Jing Zhao , Meng Wang
  Abstract: This study aims to propose a centralized optimal control model for automated left-turn platoon at contraflow left-turn lane (CLL) intersections. The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness. The proposed model is cast into a mixed-integer linear programming problem and then solved by the branch-and-bound technique. The proposed model has a promising control effect under different geometric controlled conditions. Moreover, the proposed model performs robustly under various safety time headways, lengths of the CLL and green times of the main signal. This study proposed a centralized optimal control model for automated left-turn platoon at CLL intersections. The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness
  Citation: Journal of Intelligent and Connected Vehicles
  PubDate: 2022-06-02
  DOI: 10.1108/JICV-03-2022-0007
  Issue No: Vol. ahead-of-print , No. ahead-of-print (2022)
Optimal charging plan for electric bus considering time-of-day electricity
tariff
- Authors: Yuhan Liu , Linhong Wang , Ziling Zeng , Yiming Bie
  Abstract: The purpose of this study is to develop an optimization method for charging plans with the implementation of time-of-day (TOD) electricity tariff, to reduce electricity bill. Two optimization models for charging plans respectively with fixed and stochastic trip travel times are developed, to minimize the electricity costs of daily operation of an electric bus. The charging time is taken as the optimization variable. The TOD electricity tariff is considered, and the energy consumption model is developed based on real operation data. An optimal charging plan provides charging times at bus idle times in operation hours during the whole day (charging time is 0 if the bus is not get charged at idle time) which ensure the regular operation of every trip served by this bus. The electricity costs of the bus route can be reduced by applying the optimal charging plans. This paper produces a viable option for transit agencies to reduce their operation costs.
  Citation: Journal of Intelligent and Connected Vehicles
  PubDate: 2022-05-10
  DOI: 10.1108/JICV-04-2022-0008
  Issue No: Vol. 5 , No. 2 (2022)
Battery electric buses charging schedule optimization considering
time-of-use electricity price
- Authors: Jia He , Na Yan , Jian Zhang , Yang Yu , Tao Wang
  Abstract: This paper aims to optimize the charging schedule for battery electric buses (BEBs) to minimize the charging cost considering the time-of-use electricity price. The BEBs charging schedule optimization problem is formulated as a mixed-integer linear programming model. The objective is to minimize the total charging cost of the BEB fleet. The charge decision of each BEB at the end of each trip is to be determined. Two types of constraints are adopted to ensure that the charging schedule meets the operational requirements of the BEB fleet and that the number of charging piles can meet the demand of the charging schedule. This paper conducts numerical cases to validate the effect of the proposed model based on the actual timetable and charging data of a bus line. The results show that the total charge cost with the optimized charging schedule is 15.56% lower than the actual total charge cost under given conditions. The results also suggest that increasing the number of charging piles can reduce the charging cost to some extent, which can provide a reference for planning the number of charging piles. Considering time-of-use electricity price in the BEBs charging schedule will not only reduce the operation cost of electric transit but also make the best use of electricity resources.
  Citation: Journal of Intelligent and Connected Vehicles
  PubDate: 2022-05-05
  DOI: 10.1108/JICV-03-2022-0006
  Issue No: Vol. 5 , No. 2 (2022)
Longitudinal control for person-following robots
- Authors: Liang Wang , Jiaming Wu , Xiaopeng Li , Zhaohui Wu , Lin Zhu
  Abstract: This paper aims to address the longitudinal control problem for person-following robots (PFRs) for the implementation of this technology. Nine representative car-following models are analyzed from PFRs application and the linear model and optimal velocity model/full velocity difference model are qualified and selected in the PFR control. A lab PFR with the bar-laser-perception device is developed and tested in the field, and the results indicate that the proposed models perform well in normal person-following scenarios. This study fills a gap in the research on PRFs longitudinal control and provides a useful and practical reference on PFRs longitudinal control for the related research.
  Citation: Journal of Intelligent and Connected Vehicles
  PubDate: 2022-04-11
  DOI: 10.1108/JICV-01-2022-0003
  Issue No: Vol. 5 , No. 2 (2022)
Merging control strategies of connected and autonomous vehicles at freeway
on-ramps: a comprehensive review
- Authors: Jie Zhu , Said Easa , Kun Gao
  Abstract: On-ramp merging areas are typical bottlenecks in the freeway network since merging on-ramp vehicles may cause intensive disturbances on the mainline traffic flow and lead to various negative impacts on traffic efficiency and safety. The connected and autonomous vehicles (CAVs), with their capabilities of real-time communication and precise motion control, hold a great potential to facilitate ramp merging operation through enhanced coordination strategies. This paper aims to present a comprehensive review of the existing ramp merging strategies leveraging CAVs, focusing on the latest trends and developments in the research field. The review comprehensively covers 44 papers recently published in leading transportation journals. Based on the application context, control strategies are categorized into three categories: merging into sing-lane freeways with total CAVs, merging into sing-lane freeways with mixed traffic flows and merging into multilane freeways. Relevant literature is reviewed regarding the required technologies, control decision level, applied methods and impacts on traffic performance. More importantly, the authors identify the existing research gaps and provide insightful discussions on the potential and promising directions for future research based on the review, which facilitates further advancement in this research topic. Many strategies based on the communication and automation capabilities of CAVs have been developed over the past decades, devoted to facilitating the merging/lane-changing maneuvers at freeway on-ramps. Despite the significant progress made, an up-to-date review covering these latest developments is missing to the authors’ best knowledge. This paper conducts a thorough review of the cooperation/coordination strategies that facilitate freeway on-ramp merging using CAVs, focusing on the latest developments in this field. Based on the review, the authors identify the existing research gaps in CAV ramp merging and discuss the potential and promising future research directions to address the gaps.
  Citation: Journal of Intelligent and Connected Vehicles
  PubDate: 2022-04-11
  DOI: 10.1108/JICV-02-2022-0005
  Issue No: Vol. 5 , No. 2 (2022)
FPGA accelerated model predictive control for autonomous driving
- Authors: Yunfei Li , Shengbo Eben Li , Xingheng Jia , Shulin Zeng , Yu Wang
  Abstract: The purpose of this paper is to reduce the difficulty of model predictive control (MPC) deployment on FPGA so that researchers can make better use of FPGA technology for academic research. In this paper, the MPC algorithm is written into FPGA by combining hardware with software. Experiments have verified this method. This paper implements a ZYNQ-based design method, which could significantly reduce the difficulty of development. The comparison with the CPU solution results proves that FPGA has a significant acceleration effect on the solution of MPC through the method. Due to the limitation of practical conditions, this paper cannot carry out a hardware-in-the-loop experiment for the time being, instead of an open-loop experiment. This paper proposes a new design method to deploy the MPC algorithm to the FPGA, reducing the development difficulty of the algorithm implementation on FPGA. It greatly facilitates researchers in the field of autonomous driving to carry out FPGA algorithm hardware acceleration research.
  Citation: Journal of Intelligent and Connected Vehicles
  PubDate: 2022-03-28
  DOI: 10.1108/JICV-03-2021-0002
  Issue No: Vol. 5 , No. 2 (2022)
Subjective assessment for an advanced driver assistance system: a case
study in China
- Authors: Di Ao , Jialin Li
  Abstract: This study aims to propose a novel subjective assessment (SA) method for level 2 or level 2+ advanced driver assistance system (ADAS) with a customized case study in China. The proposed SA method contains six dimensions, including perception, driveability and stability, riding comfort, human–machine interaction, driver workload and trustworthiness and exceptional operating case, respectively. And each dimension subordinates several subsections, which describe the corresponding details under this dimension. Based on the proposed SA, a case study in China is conducted. Six drivers with different driving experiences are invited to give their subjective ratings for each subsection according to a predefined rating standard. The rating results show that the ADAS from Tesla outperforms the upcoming electric vehicle in most cases. The proposed SA method is beneficial for the original equipment manufacturers developing related technologies in the future.
  Citation: Journal of Intelligent and Connected Vehicles
  PubDate: 2022-03-28
  DOI: 10.1108/JICV-11-2021-0017
  Issue No: Vol. 5 , No. 2 (2022)
Traffic signal coordination control for arterials with dedicated CAV lanes
- Authors: Liang Xu , Sheng Jin , Bolin Li , Jiaming Wu
  Abstract: This study aims to make full use of the advantages of connected and autonomous vehicles (CAVs) and dedicated CAV lanes to ensure all CAVs can pass intersections without stopping. The authors developed a signal coordination model for arteries with dedicated CAV lanes by using mixed integer linear programming. CAV non-stop constraints are proposed to adapt to the characteristics of CAVs. As it is a continuous problem, various situations that CAVs arrive at intersections are analyzed. The rules are discovered to simplify the problem by discretization method. A case study is conducted via SUMO traffic simulation program. The results show that the efficiency of CAVs can be improved significantly both in high-volume scenario and medium-volume scenario with the plan optimized by the model proposed in this paper. At the same time, the progression efficiency of regular vehicles is not affected significantly. It is indicated that full-scale benefits of dedicated CAV lanes can only be achieved with signal coordination plans considering CAV characteristics. To the best of the authors’ knowledge, this is the first research that develops a signal coordination model for arteries with dedicated CAV lanes.
  Citation: Journal of Intelligent and Connected Vehicles
  PubDate: 2022-03-16
  DOI: 10.1108/JICV-08-2021-0015
  Issue No: Vol. 5 , No. 2 (2022)
Evaluating the moderating effect of in-vehicle warning information on
mental workload and collision avoidance performance
- Authors: Chen Chai , Ziyao Zhou , Weiru Yin , David S. Hurwitz , Siyang Zhang
  Abstract: The presentation of in-vehicle warnings information at risky driving scenarios is aimed to improve the collision avoidance ability of drivers. Existing studies have found that driver’s collision avoidance performance is affected by both warning information and driver’s workload. However, whether moderation and mediation effects exist among warning information, driver’s cognition, behavior and risky avoidance performance is unclear. This purpose of this study is to examine whether the warning information type modifies the relationship between the forward collision risk and collision avoidance behavior. A driving simulator experiment was conducted with waring and command information. Results of 30 participants indicated that command information improves collision avoidance behavior more than notification warning under the forward collision risky driving scenario. The primary reason for this is that collision avoidance behavior can be negatively affected by the forward collision risk. At the same time, command information can weaken this negative effect. Moreover, improved collision avoidance behavior can be achieved through increasing drivers’ mental workload. The proposed model provides a comprehensive understanding of the factors influencing collision avoidance behavior, thus contributing to improved in-vehicle information system design. The significant moderation effects evoke the fact that information types and mental workloads are critical in improving drivers’ collision avoidance ability. Through further calibration with larger sample size, the proposed structural model can be used to predict the effect of in-vehicle warnings in different risky driving scenarios.
  Citation: Journal of Intelligent and Connected Vehicles
  PubDate: 2022-03-10
  DOI: 10.1108/JICV-03-2021-0003
  Issue No: Vol. 5 , No. 2 (2022)
Journal of Intelligent and Connected Vehicles