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Zijia Zhong

Publications and source records attributed to Zijia Zhong.

12 recordsLinked to original sources

Location-aware Verification for Autonomous Truck Platooning Based on Blockchain and Zero-knowledge Proof

Platooning technologies enable trucks to drive cooperatively and automatically, which bring benefits including less fuel consumption, more road capacity and safety. In order to establish trust during dynamic platoon formation, ensure vehicular data integrity, and guard platoons against potential attackers, it is pivotal to verify any given vehicle's identity information before granting it access to join a platoon. To address this concern in dynamic truck platooning, we present a novel location-aware and privacy-preserving verification protocol based on zero-knowledge proof and permissioned blockchain. By performing the verification process within the spatially-local area defined by a given platoon, our system can provide lower latency and communication overhead compared to a location-agnostic blockchain system. We prototype the proposed system and perform benchmark tests on the Hyperledger platform. The experimental results show that our system is suitable for real-world truck platooning.

cs.NI↗

Assessing Connected Vehicle Data Coverage on New Jersey Roadways

The connected vehicle data (CVD) is one of the most promising emerging mobility data that greatly increases the ability to effectively monitor transportation system performance. A commercial vehicle trajectory dataset was evaluated for market penetration and coverage to establish whether it represents a sufficient sample of the vehicle volumes across the statewide roadway network of New Jersey. The dataset (officially named Wejo Vehicle Movement data) was compared to the vehicle volumes obtained from 46 weight-in-motion (WIM) traffic count stations during the corresponding two-month period. The observed market penetration rates of the Movement data for the interstate highways, non-interstate expressways, major arterials, and minor arterials are 2.55% (std. dev. 0.76%), 2.31% (std. dev. 1.07%), 3.25% (standard deviation 1.48%), and 4.39% (standard deviation 2.65%), respectively. Additionally, the temporal resolution of the dataset (i.e., the time interval between consecutive Wejo vehicle trips captured at a given roadway section, time-of-day variation, day-of-month variation) was also found to be consistent among the evaluated WIM locations. Although relatively low (less than 5%), the consistent market penetration, combined with uniform spatial distribution of equipped vehicles within the traffic flow, could enable or enhance a wide range of traffic analytics applications.

cs.CY↗

Framework for Highway Traffic Profiling using Connected Vehicle Data

The connected vehicle (CV) data could potentially revolutionize the traffic monitoring landscape as a new source of CV data that are collected exclusively from original equipment manufactures (OEMs) have emerged in the commercial market in recent years. Compared to existing CV data that are used by agencies, the new-generation of CV data have certain advantages including nearly ubiquitous coverage, high temporal resolution, high spatial accuracy, and enriched vehicle telematics data (e.g., hard braking events). This paper proposed a traffic profiling framework that target vehicle-level performance indexes across mobility, safety, riding comfort, traffic flow stability, and fuel consumption. The proof-of-concept study of a major interstate highway (i.e., I-280 NJ), using the CV data, illustrates the feasibility of going beyond traditional aggregated traffic metrics. Lastly, potential applications for either historical analysis and even near real-time monitoring are discussed. The proposed framework can be easily scaled and is particularly valuable for agencies that wish to systemically monitoring regional or statewide roadways without substantial investment on infrastructure-based sensing (and the associated on-going maintenance costs)

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Influence of CAV Clustering Strategies on Mixed Traffic Flow Characteristics: An Analysis of Vehicle Trajectory Data

Being one of the most promising applications enabled by connected and automated vehicles (CAV) technology, Cooperative Adaptive Cruise Control (CACC) is expected to be deployed in the near term on public roads.} Thus far, the majority of the CACC studies have been focusing on the overall network performance with limited insights on the potential impacts of CAVs on human-driven vehicles (HVs).This paper aims to quantify such impacts by studying the high-resolution vehicle trajectory data that are obtained from microscopic simulation. Two platoon clustering strategies for CACC- an ad hoc coordination strategy and a local coordination strategy-are implemented. Results show that the local coordination outperforms the ad hoc coordination across all tested market penetration rates (MPRs) in terms of network throughput and productivity. According to the two-sample Kolmogorov-\textcolor{re}{Smirnov} test, however, the distributions of the hard braking events (as a potential safety impact) for HVs change significantly under local coordination strategy. For both of the clustering strategy, CAVs increase the average lane change frequency for HVs. The break-even point for average lane change frequency between the two strategies is observed at 30% MPR, which decreases from 5.42 to 5.38 per vehicle. The average lane change frequency following a monotonically increasing pattern in response to MPR, and it reaches the highest 5.48 per vehicle at 40% MPR. Lastly, the interaction state of the car-following model for HVs is analyzed. It is revealed that the composition of the interaction state could be influenced by CAVs as well. One of the apparent trends is that the time spent on approaching state declines with the increasing presence of CAVs.

cs.MA↗

Traffic Flow Characteristics and Lane Use Strategies for Connected and Automated Vehicle in Mixed Traffic Conditions

Managed lanes, such as a dedicated lane for connected and automated vehicles (CAVs), can provide not only technological accommodation but also desired market incentives for road users to adopt CAVs in the near future. In this paper, we investigate traffic flow characteristics with two configurations of the managed lane across different market penetration rates and quantify the benefits from the perspectives of lane-level headway distribution, fuel consumption, communication density, and overall network performance. The results highlight the benefits of implementing managed lane strategies for CAVs: 1) a dedicated CAV lane significantly extends the stable region of the speed-flow diagram and yields a greater road capacity. As the result shows, the highest flow rate is 3,400 vehicles per hour per lane at 90% market penetration rate with one CAV lane; 2) the concentration of CAVs in one lane results in a narrower headway distribution (with smaller standard deviation) even with partial market penetration; 3) a dedicated CAV lane is also able to eliminate duel-bell-shape distribution that is caused by the heterogeneous traffic flow; and 4) a dedicated CAV lane creates a more consistent CAV density, which facilitates communication activity and decreases the probability of packet dropping.

eess.SY↗

Autonomous and Semi-Autonomous Intersection Management: A Survey

Intersection is a major source of traffic delays and accidents within modern transportation systems. Compared to signalized intersection management, autonomous intersection management (AIM) coordinates the intersection crossing at an individual vehicle level with additional flexibility. AIM can potentially eliminate stopping in intersection crossing due to traffic lights while maintaining a safe separation among conflicting movements. In this paper, the state-of-the-art AIM research among various disciplines (e.g., traffic engineering, control engineering) is surveyed from the perspective of three hierarchical layers: corridor coordination layer, intersection management layer, and vehicle control layer. The key aspects of AIM designs are discussed in details, including conflict detection schemes, priority rules, control centralization, computation complexity, etc. The potential improvements for AIM evaluation with the emphasis of realistic scenarios are provided. This survey serves as a comprehensive review of AIM design and provides promising directions for future research.

cs.MA↗

Clustering Strategies of Cooperative Adaptive Cruise Control: Impacts on Human-driven Vehicles

As a promising application of connected and automated vehicles (CAVs), Cooperative Adaptive Cruise Control (CACC) is expected to be deployed on the public road in the near term. Thus far the majority of the CACC studies have been focusing on the overall network performance with limited insight on the potential impact of CAVs on human-driven vehicles (HVs). This paper aims to quantify the influence of CAVs on HVs by studying the high-resolution vehicle trajectory data that is obtained from microscopic simulation. Two clustering strategies for CACC are implemented: an ad hoc coordination one and a local coordination one. Results show that the local coordination outperforms the ad hoc coordination across all tested market penetration rates (MPRs) in terms of network throughput and productivity. The greatest performance difference between the two strategies is observed at 30% and 40% MPR for throughput and productivity, respectively. However, the distributions of the hard braking observations (as a potential safety impact) for HVs change significantly under local coordination strategy. Regardless of the clustering strategy, CAVs increase the average lane change frequency for HVs. 30% MPR is the break-even point for local coordination, after which the average lane change frequency decreases from the peak 5.42 to 5.38. Such inverse relationship to MPR is not found in the ah hoc case and the average lane change frequency reaches the highest 5.48 at 40% MPR.

cs.MA↗

Virtual Guide Dog: Next Generation Pedestrian Signal for the Visually Impaired

Accessible pedestrian signal (APS) was proposed as a mean to achieve the same level of service that is set forth by the American with Disability Act (ADA) for the visually impaired. One of the major issues of existing APSs is the failure to deliver adequate crossing information for the visually impaired. This paper presents a mobile-based APS application, namely Virtual Guide Dog (VGD). Integrating intersection information and onboard sensors (e.g., GPS, compass, accelerometer, and gyroscope sensor) of modern smartphones, the VGD application can notify the visually impaired: 1) the close proximity of an intersection and 2) the street information for crossing. By employing a screen tapping interface, VGD can remotely place a pedestrian crossing call to the controller, without the need of using a push button. In addition, VGD informs VIs the start of a crossing phase by using text-to-speech technology. The proof-of-concept test shows that VGD keeps the users informed about the remaining distance as their approaching the intersection. It was also found that the GPS-only mode is accompanied by greater distance deviation compared to the mode jointly operating with both GPS and cellular positioning.

cs.HC↗

The Effectiveness of Managed Lane Strategies for the Near-term Deployment of Cooperative Adaptive Cruise Control

Traffic simulation is a cost-effective way to test the deployment of Cooperative Adaptive Cruise Control (CACC) vehicles in a large-scale transportation network. By using a previously developed microscopic simulation testbed, this paper examines the impacts of four managed lane strategies for the near-term deployment of CACC vehicles under mixed traffic conditions. Network-wide performance measures are investigated from the perspectives of mobility, safety, equity, and environmental impacts. In addition, the platoon formation performance of CACC vehicles is evaluated with platoon-orientated measures, such as the percentage of platooned CACC vehicles, average platoon depth, and vehicle-hour-platooned that is proposed in this paper under the imperfect DSRC communication environment. Moreover, managed lane score matrices are developed to incorporate heterogeneous categories of performance measures, aiming to provide a more comprehensive picture for stakeholders. The results show that mixing CACC traffic along with non-CACC traffic across all travel lanes is an acceptable option when the market penetration (MP) is lower than 30% for roadways where a managed lane is absent. Providing CACC with priority access to an existing managed lane, if available, is also a good strategy for improving the overall traffic performance when the MP is lower than 40%. When the MP reaches above 40%, a dedicated lane for CACC vehicles is recommended, as it provides greater opportunity for CACC vehicles to form platoons. The facilitation of homogeneous CACC traffic flow could make further improvements possible in the future.

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Unconventional Arterial Intersection Designs under Connected and Automated Vehicle Environment: A Survey

Signalized intersections are major sources of traffic delay and collision within the modern transportation system. Conventional signal optimization has revealed its limitation in improving the mobility and safety of an intersection. Unconventional arterial intersection designs (UAIDs) are able to improve the performance of an intersection by reducing phases of a signal cycle. Furthermore, they can fundamentally alter the number and the nature of the conflicting points. However, the driver's confusion, as a result of the unconventional geometric designs, remains one of the major barriers for the widespread adoption of UAIDs. Connected and Automated Vehicle (CAV) technology has the potential to overcome this barrier by eliminating the driver's confusion of a UAID. Therefore, UAIDs can play a significant role in transportation networks in the near future. In this paper, we surveyed UAID studies and implementations. In addition, we present an overview of intersection control schemes with the emergence of CAV and highlight the opportunity rises for UAID with the CAV technology. It is believed that the benefits gained from deploying UAIDs in conjunction with CAV are significant during the initial rollout of CAV under low market penetration.

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Alternative Intersection Designs with Connected and Automated Vehicle

Alternative intersection designs (AIDs) can improve the performance of an intersection by not only reducing the number of signal phases but also change the configuration of the conflicting points by re-routing traffic. However the AID studies have rarely been extended to Connected and Automated Vehicle (CAV) which is expected to revolutionize our transportation system. In this study, we investigate the potential benefits of CAV to two AIDs: the diverging diamond interchange (DDI) and the restricted crossing U-turn intersection. The potential enhancements of AID, CAV, and the combination of both are quantified via microscopic traffic simulation. We found that CAV is able to positively contribute to the performance of an intersection. However, converting an existing conventional diamond interchange (CDI) to a diverging one is a more effective way according to the simulation results. DDI improves the throughput of a CDI by 950 vehicles per hour, a near 20% improvement; whereas with full penetration of CAV, the throughput of a CDI is increased only by 300 vehicles per hour. A similar trend is observed in the average delay per vehicle as well. Furthermore, we assess the impact for the driver's confusion, a concern for deploying AIDs, on the traffic flow. According to the ANOVA test, the negative impacts of driver's confusion are of statistical significance.

cs.MA↗

Simulation Framework for Cooperative Adaptive Cruise Control with Empirical DSRC Module

Wireless communication plays a vital role in the promising performance of connected and automated vehicle (CAV) technology. This paper proposes a Vissim-based microscopic traffic simulation framework with an analytical dedicated short-range communication (DSRC) module for packet reception. Being derived from ns-2, a packet-level network simulator, the DSRC probability module takes into account the imperfect wireless communication that occurs in real-world deployment. Four managed lane deployment strategies are evaluated using the proposed framework. While the average packet reception rate is above 93\% among all tested scenarios, the results reveal that the reliability of the vehicle-to-vehicle (V2V) communication can be influenced by the deployment strategies. Additionally, the proposed framework exhibits desirable scalability for traffic simulation and it is able to evaluate transportation-network-level deployment strategies in the near future for CAV technologies.

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