## 1 Introduction  
As it is well known, the California Program on Advanced Technology for the Highway (PATH), a collaboration between the Institute of Transportation Studies at the University of California at Berkeley and the California Department of Transportation (Caltrans), with funding provided by Caltrans and the U.S. Department of Transportation, has done pioneering work on Automatic Vehicle Control (AVC) since 1986 and provided an outstanding stream of new ideas, methods and developments [1]. It is worth mentioning also that at Ohio State University (OSU), a program running from 1964-1980 included studies on headway safety policy, longitudinal control, lateral control and highway system operations [2]. Moreover, the interest in the Intelligent Vehicle Highway System (IVHS) was emphasized by the 1973-1979 projects funded by the Ministry of International Trade and Industry (MITI) of Japan [3]. Early considerations concerning safety implications of vehicle automation using the drive-by-wire concept and the driver workload with respect to the transformation from Cruise Control (CC) to Adaptive Cruise Control (ACC) were presented in [4]. More recently, the problems of adaptive cruise control, stop and go [5], as well as the overtaking maneuvers [6] have been investigated, and solutions based on artificial intelligence have been proposed and experimentally tested by researchers of the AUTOPIA Group at the Centre for Automation and Robotics (CAR) of the Consejo Superior de Investigaciones Cientificas (CSIC), Spain. In addition to these works, a vehicle of AUTOPIA (Spanish research project) ran driverless 100 km, in 2012, from El Escorial to Arganda del Rey (Madrid). A leading vehicle, which was driven manually, dynamically generated a high accuracy map to be tracked by the fully-autonomous following car. The journey covered a wide range of driving scenarios, including urban zones, secondary roads and highways, in standard traffic conditions ([[https://www.car.upm-csic.es/autopia/](https://www.car.upm-csic.es/autopia/)]([https://www.car.upm-csic.es/autopia/](https://www.car.upm-csic.es/autopia/))). In a motivating survey paper [7] published in 2000, a substantial increment of research in intelligent vehicles and their application areas was acknowledged, where sectors of interest and key supporting technologies were considered. Applications related to passenger cars, heavy trucks, bus and public transport applications, as well as special vehicle applications were analyzed, and relevant functionalities/requirements were identified (collision warning, collision avoidance and driver assistance, driver impairment monitoring intelligent speed adaptation, automated operation, industrial automation, military operations). Nowadays, especially in urban/suburban areas, there is a clear conflict among collective transportation (high occupancy vehicle) and individual transportation, which results in overcrowding that makes transportation uncomfortable, lengthy, polluting and more expensive than needed. This situation decreases substantially the quality of collective transportation services. Because of this general concern, the development of new concepts and technology for urban/suburban transportation is of major importance. In these circumstances, the interest in Intelligent Transportation Systems (ITS) and Intelligent Vehicles (IV) is increasing because the wide range of possible applications [8]. Among several current developments for urban/suburban transportation, the concepts of Light Rail or Light Rail Transit (LRT) and Bus Rapid Transit (BRT) are some of the most attractive. LRT is a kind of urban public transport using rolling stock quite similar to a tramway, but operating at a higher capacity, while BRT aims to provide a high-quality bus-based transit system with the main advantages of being a flexible and cost-effective urban mobility transit system [9; 10].