Optimal GPS Integrity-Constrained Path Planning for Ground Vehicles

Path planning for a ground vehicle in an urban environment is considered. The vehicle is equipped with a GPS receiver and a road map. The vehicle desires to take the shortest path to reach a target destination, while guaranteeing that integrity monitoring-based measures are satisfied along its traversed path. A path planning algorithm is proposed that yields the optimal path to follow as well as suboptimal feasible paths. The integrity monitoring-based measure considered in this paper is the horizontal protection level (HPL), which refers to the statistical bound around the vehicle that guarantees the probability of the absolute position error exceeding a desired threshold is not larger than the integrity risk. Experimental results are presented showing that choosing the optimal path from the proposed algorithm reduces the average and maximum HPL by 2 m and 20.2 m, respectively, compared to choosing the shortest-time path, while introducing a negligible additional path length.

[1]  Grace Xingxin Gao,et al.  Predicting State Uncertainty for GNSS-based UAV Path Planning using Stochastic Reachability , 2019 .

[2]  Mahdi Maaref,et al.  Robust Vehicular Localization and Map-Matching in Urban Environments with IMU, GNSS, and Cellular Signals , 2019 .

[3]  Grace Xingxin Gao,et al.  Integrity for GPS/LiDAR Fusion Utilizing a RAIM Framework , 2018 .

[4]  Chun Yang,et al.  Tracking and Relative Positioning with Mixed Signals of Opportunity , 2015 .

[5]  Z. Kassas,et al.  LTE receiver design and multipath analysis for navigation in urban environments , 2018, NAVIGATION.

[6]  Fulvio Babich,et al.  Vehicular Position Tracking Using LTE Signals , 2017, IEEE Transactions on Vehicular Technology.

[7]  Zaher M. Kassas,et al.  Exploiting LTE Signals for Navigation: Theory to Implementation , 2018, IEEE Transactions on Wireless Communications.

[8]  T.A. Mazzuchi,et al.  Addressing uncertainty in UAV navigation decision-making , 2008, IEEE Transactions on Aerospace and Electronic Systems.

[9]  Li-Ta Hsu,et al.  A New Path Planning Algorithm Using a GNSS Localization Error Map for UAVs in an Urban Area , 2018, Journal of Intelligent & Robotic Systems.

[10]  Lei Wang,et al.  Multi-Constellation GNSS Performance Evaluation for Urban Canyons Using Large Virtual Reality City Models , 2012 .

[11]  Todd E. Humphreys,et al.  Receding horizon trajectory optimization in opportunistic navigation environments , 2015, IEEE Transactions on Aerospace and Electronic Systems.

[12]  Marc C. Alban,et al.  Ranger: A ground-facing camera-based localization system for ground vehicles , 2016, 2016 IEEE/ION Position, Location and Navigation Symposium (PLANS).

[13]  Zaher M. Kassas,et al.  Enhanced Safety of Autonomous Driving by Incorporating Terrestrial Signals of Opportunity , 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[14]  Zaher M. Kassas,et al.  Measurement Characterization and Autonomous Outlier Detection and Exclusion for Ground Vehicle Navigation With Cellular Signals , 2020, IEEE Transactions on Intelligent Vehicles.

[15]  Kimia Shamaei,et al.  I Hear, Therefore I Know Where I Am: Compensating for GNSS Limitations with Cellular Signals , 2017, IEEE Signal Processing Magazine.

[16]  Michael S. Braasch,et al.  Gravity model error considerations for high-integrity GNSS-aided INS operations , 2018, 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS).

[17]  David Lubinski,et al.  An Opportunity for "Accuracy". , 1995 .

[18]  Andrey Soloviev,et al.  Tight Coupling of GPS and INS for Urban Navigation , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[19]  Zaher M. Kassas,et al.  Lane-Level Localization and Mapping in GNSS-Challenged Environments by Fusing Lidar Data and Cellular Pseudoranges , 2019, IEEE Transactions on Intelligent Vehicles.

[20]  Ali H. Al-Bayatti,et al.  GPS integrity monitoring for an intelligent transport system , 2013, 2013 10th Workshop on Positioning, Navigation and Communication (WPNC).

[21]  Otman A. Basir,et al.  A Low-Cost Lane-Determination System Using GNSS/IMU Fusion and HMM-Based Multistage Map Matching , 2017, IEEE Transactions on Intelligent Transportation Systems.

[22]  Juliette Marais,et al.  GNSS Position Integrity in Urban Environments: A Review of Literature , 2018, IEEE Transactions on Intelligent Transportation Systems.

[23]  Todd E. Humphreys,et al.  Greedy Motion Planning for Simultaneous Signal Landscape Mapping and Receiver Localization , 2015, IEEE Journal of Selected Topics in Signal Processing.

[24]  Aleksander Nowak,et al.  Dynamic GNSS Mission Planning Using DTM for Precise Navigation of Autonomous Vehicles , 2016, Journal of Navigation.

[25]  Zaher M. Kassas,et al.  Power matching approach for GPS coverage extension , 2006, IEEE Transactions on Intelligent Transportation Systems.

[26]  Per Enge,et al.  Evaluation of Signal in Space Error Bounds to Support Aviation Integrity , 2009 .

[27]  Zaher M. Kassas,et al.  Autonomous Integrity Monitoring for Vehicular Navigation With Cellular Signals of Opportunity and an IMU , 2022, IEEE Transactions on Intelligent Transportation Systems.

[28]  Abigail L. Bristow,et al.  Map-Aided Integrity Monitoring of a Land Vehicle Navigation System , 2012, IEEE Transactions on Intelligent Transportation Systems.

[29]  Donald B. Johnson,et al.  A Note on Dijkstra's Shortest Path Algorithm , 1973, JACM.

[30]  Upamanyu Madhow,et al.  Bayesian localization and mapping using GNSS SNR measurements , 2014, 2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014.

[31]  Upamanyu Madhow,et al.  GPS-optimal micro air vehicle navigation in degraded environments , 2014, 2014 American Control Conference.

[32]  Joe Khalife,et al.  Opportunistic Integrity Monitoring for Enhanced UAV Safety , 2019 .

[33]  M. Spenko,et al.  Experimental Integrity Evaluation of Tightly-Integrated IMU/LiDAR Including Return-Light Intensity Data , 2019, Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019).

[34]  Denis Fernando Wolf,et al.  Feature Detection for Vehicle Localization in Urban Environments Using a Multilayer LIDAR , 2016, IEEE Transactions on Intelligent Transportation Systems.

[35]  Rafael Toledo-Moreo,et al.  Lane-Level Integrity Provision for Navigation and Map Matching With GNSS, Dead Reckoning, and Enhanced Maps , 2010, IEEE Transactions on Intelligent Transportation Systems.

[36]  Zaher M. Kassas,et al.  Multipath-Optimal UAV Trajectory Planning for Urban UAV Navigation with Cellular Signals , 2019, 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall).

[37]  Zaher M. Kassas,et al.  Autonomous Ground Vehicle Path Planning in Urban Environments Using GNSS and Cellular Signals Reliability Maps: Models and Algorithms , 2021, IEEE Transactions on Aerospace and Electronic Systems.

[38]  Ilaria Martini,et al.  Snapshot residual and Kalman Filter based fault detection and exclusion schemes for robust railway navigation , 2017, 2017 European Navigation Conference (ENC).

[39]  Demoz Gebre-Egziabher,et al.  Kalman filter–based RAIM for GNSS receivers , 2015, IEEE Transactions on Aerospace and Electronic Systems.