An Empirical Study on V2X Enhanced Low-Cost GNSS Cooperative Positioning in Urban Environments

Abstract

High-precision and lane selective position estimation is of fundamental importance for prospective advanced driver assistance systems (ADAS) and automated driving functions, as well as for traffic information and management processes in intelligent transportation systems (ITS). User and vehicle positioning is usually based on Global Navigation Satellite System (GNSS), which, as stand-alone positioning, does not meet the necessary requirements in terms of accuracy. Furthermore, the rise of connected driving offers various possibilities to enhance GNSS positioning by applying cooperative positioning (CP) methods. Utilizing only low-cost sensors, especially in urban environments, GNSS CP faces several demanding challenges. Therefore, this contribution presents an empirical study on how Vehicle-to-Everything (V2X) technologies can aid GNSS position estimation in urban environments, with the focus being solely on positioning performance instead of multi-sensor data fusion. The performance of CP utilizing common positioning approaches as well as CP integration in state-of-the-art Vehicular Ad-hoc Networks (VANET) is displayed and discussed. Additionally, a measurement campaign, providing a representational foundation for validating multiple CP methods using only consumer level and low-cost GNSS receivers, as well as commercially available IEEE 802.11p V2X communication modules in a typical urban environment is presented. Evaluating the algorithm’s performance, it is shown that CP approaches are less accurate compared to single positioning in the given environment. In order to investigate error influences, a skyview modelling seeking to identify non-line-of-sight (NLoS) effects using a 3D building model was performed. We found the position estimates to be less accurate in areas which are affected by NLoS effects such as multipath reception. Due to covariance propagation, the accuracy of CP approaches is decreased, calling for strategies for multipath detection and mitigation. In summary, this contribution will provide insights on integration, implementation strategies and accuracy performances, as well as drawbacks for local area, low-cost GNSS CP in urban environments.

Comprehensive Survey of Radio Resource Allocation Schemes for 5G V2X Communications

“…Depending on the ITS services, the collected data are sent to other vehicles or humans for road safety or autonomous driving. Each vehicle locates its position within the network using global navigation, e.g., the Global Navigation Satellite System or existing infrastructure based such as Wi-Fi access points and a cellular base station (BS) [12], [13].…”

“…In parallel to the V2X communications presented in [1] and the V2X application use cases presented in [7], 3GPP Release 16 groups the main services of V2X into four areas according to the critical requirements of scalability, reliability, throughput, and latency [12], [15]. To ensure road safety, V2X communications require high reliability, high throughput, network scalability, and low latency.…”

“…Figure 1 shows the full network scenario of V2X communication, which includes different V2X connections and V2X services. The V2X services are described in detail below [12], [15].…”

“…These messages are categorized into two types: cooperative awareness messages (CAMs) and decentralized environmental notification messages (DENMs) [1]. According to the messages transmitted among the vehicles, the applications can be considered as "Critical" or "Non-Critical" [12], [14]. V2Xs services can be categorized into many groups of applications with regard to different criteria of QoS.…”

Addressing the Potential of GNSS Moving Base Station Technique for Vehicular C-ITS Applications: Preliminary Tests and Results

“…Today, the provision of low-cost, accurate and robust positioning is a key requirement for many urban mobility applications, especially those supporting emerging Intelligent Transportation Systems (ITS) (Gikas et al, 2019). With the evolution of connected vehicles and the gradual shift towards fully autonomous transport systems in the coming years, the need of reliable vehicle positioning forms an integral part of the deployment of cooperative ITS (C-ITS) services (Schwarzbach et al, 2019), (GSA-MKD-RD- UREQ-250283, 2019). However, the variable vehicular environment, the motion dynamics and the adoption of low-cost grade technology pose various restrictions on positioning systems performance (Clausen et al, 2017), (Antoniou et al, 2018).…”