SHRI KRISHNA EDUCATIAL & CULTURAL MANDAL’S
SHRI SURESHDADA JAIN COLLEGE OF ENGINEERING,
SHIRSOLI ROAD. JALGAON [M.S.]
A SEMINAR REPORT ON
AUTOMATED HIGHWAY SYSTEM
Submitted By:
Shimpi Tanmay R.
Guided by:
Department of Automobile Engineering
Academic year
2009-2010
Affiliated to North Maharashtra University, Jalgaon
(NAAC Accredited ****)
Certificate
Shrikrishna Educational & Cultural Mandal’s
Shri Sureshdada Jain College of Engineering,
Shirsoli Road, Jalgaon (M.S.)
DEPARTMENT OF AUTOMOBILE ENGINEERING
This is certify that Mr. Shimpi Tanmay R
has successfully presented the Seminar report on
AUTOMATED HIGHWAY SYSTEM
And submitted in satisfactory manner.
This Seminar report is submitted in partial fulfillment for the Final year in Automobile Engineering affiliated to North Maharashtra University, Jalgaon (M.S.)
SEMINAR GUIDE HOD
Prof. M.S.Singh Prof. S. J. Chaudhari
PRINCIPAL
Dr. A. J. Patil
INDEX
1. Introduction
2. Background
3. Objectives of Automated highway systems
4. How it Works
5. Theory
i) Implementation
ii) Methodology
6. ADVANTAGES
7. Future scope
8. Conclusion
Figure
Figure no 1
Figure no 2
Figure no 3
Figure no 4
Figure no 5
Figure no 6
Figure no 7
Figure no 8
Figure no 9
Introduction:-
An automated highway system (AHS) or Smart Road is a proposed intelligent transportation system technology designed to provide for driverless cars on specific rights-of-way. It is most often touted as a means of traffic congestion relief, since it drastically reduces following distances and thus allows more cars to occupy a given stretch of road.
Background
Every major city suffers from the problems that are related to increasing mobility demands. Cities have to deal with pollution, congestion and safety problems caused by increasing traffic. Traditional transport systems are not sufficient anymore to cope with these increasing problems.
With the exception of some automatically operated metro systems (Paris, London and Lille) and some recently introduced automated buses and people-movers (Clermont-Ferrand, Eindhoven and Capelle aan de IJssel), transport systems in the present-day European city are mostly of a traditional type.
automated highway system will contribute to innovative solutions that will allow increased mobility in a well-controlled manner, using technologies with low pollution, high safety levels and a much increased efficiency, using either a separate infrastructure or existing roads. In future mobility scenarios, such new transport systems will be part of the urban environment. These new transport systems will be the answer to the new mobility demands of the future society. In our vision, the urban mobility will be greatly supported by new transport system concepts, which are able to improve the efficiency of road transport in dense areas while at the same time help to reach the zero accident target and minimize nuisances.
Objectives
Automated highway system’s ambitious goals can be achieved by:
v Developing advanced concepts for advanced road vehicles for passengers and goods. Most of the earlier projects addressed isolated aspects of the mobility problems of cities, whereas AUTOMATED HIGHWAY SYSTEM focuses on the overall urban transportation problem
v Introducing new tools for managing urban transport. AUTOMATED HIGHWAY SYSTEM will develop tools that can help cities to cross the thresholds that are preventing them from introducing innovative systems. For instance, the absence of certification procedures and the lack of suitable business models will be addressed.
v Taking away barriers that are in the way of large-scale introduction of automated systems. Some of these barriers are of a technological nature, some are of a legal or administrative nature: for example, the legal requirement for vehicles using public roads where the driver is responsible for the vehicle at all times, which effectively prohibits driverless vehicles from using public roads.
v Validating and demonstrating the concepts, methods and tools developed in AUTOMATED HIGHWAY SYSTEM in European cities. In a number of other cities, studies will be carried out to show that an automated transport system is not only feasible, but will also contribute to a sustainable solution for the city’s mobility problems, now and in the future.
v To survey and document automated highway system with pedestrian safety systems on roads. These systems include crossing control arms, video cameras, radar and acoustic detection systems, skirts, and collision avoidance systems.
How it works
In one scheme, the roadway has magnetized stainless-steel spikes driven one meter apart in its center The car senses the spikes to measure its speed and locate the center of the lane. Furthermore, the spikes can have either magnetic north or magnetic south facing up. The roadway thus has small amounts of digital data describing interchanges, recommended speeds, etc.
The cars have power steering and automatic speed controls, which are controlled by a computer.
The cars organize themselves into platoons of eight to twenty-five cars. The platoons drive themselves a meter apart, so that air resistance is minimized. The distance between platoons is the conventional braking distance. If anything goes wrong, the maximum number of harmed cars should be one platoon.
Fig no.1 intelligent vehicle with sensors and actuators
Theory
In order to achieve an optimal utilization of the existing transportation system, the authorities strive to alleviate the prevailing car-caused problems by means of coordinating physical flows of road traffic. In addition, they take into account preserving accessibility and environment as well as enhancing road safety. These processes take place at a given demand for road traffic that is assumed to be fixed in time and place (i.e., no demand management). As far as the above- mentioned aims are concerned, we distinguish two classes of involved information systems
· Advanced Traffic Management Systems (ATMS) and
· Advanced Traffic Control Systems (ATCS).
Advanced Traffic Management Systems (ATMS)
The class of Advanced Traffic Management Systems (ATMS) is area-oriented and concentrates on a (certain part of a) road network (e.g. congregated sections of the freeway network or parts of the urban or the rural network). The traffic performance on the remaining (parts of the) road networks are considered to be of less interest for ATMS. For the concerning area, ATMS aim at an optimal traffic performance at system level, which might be expressed as serving as many cars on the concerning road network, dissipating a minimum total travel time. In this way, ATMS strive for a system optimum.
To achieve a system optimum, ATMS require relevant information about the actual system performance on the entire road infrastructure under consideration. Only in this way, ATMS can dynamically adjust or distribute the actually offered traffic to or over the available infrastructural capacity by means of traffic management measures. The information about the actual status of the traffic (and the infrastructure) should be available in real-time (e.g. in time intervals of 1 to 5 minutes) and concerns traffic data that is aggregated to a certain extent. An important characteristic of ATMS applications is that decisions are made and measures are (seen to be) implemented by traffic managers in the traffic center, which complete the collected external data collections with know-how gathered by training and experience.
Since the administrators of ATMS applications are the road authorities, which are also responsible for the road infrastructure, an ATMS monitoring system is obviously based on fixed traffic detectors that are mounted in, above or along the road infrastructure. We will refer to this type of detectors as infrastructure based traffic detectors. As a consequence of the network-wide oriented nature of ATMS, an ATMS monitoring system using fixed, infrastructure based traffic detectors (e.g. inductive loops) is characterized by rather large detector spacing’s (typically of 5 to 10 kilometers. Shorter distances between the detectors would make such a network-wide monitoring system financially prohibitive.
A typical example of an ATMS application is Incident Management, which deals with swiftly detecting disturbances in the traffic flows, estimating expected delay, determining spare capacity of the remaining road links and proportionally distributing traffic over the entire network.
Advanced Traffic Control Systems (ATCS)
Advanced Traffic Control Systems (ATCS) serves as 'executive complement' to the class of Advanced Traffic Management Systems (ATMS). ATCS are local-oriented and concentrate on certain parts of the road infrastructure (i.e., critical or notorious bottlenecks, such as bridges, tunnels and on/off ramps). For these local sites, ATCS aim at an optimal traffic performance at local level. This might be expressed as serving as many of the offered cars as possible in a time period that is as short as possible, so dissipating a minimum total time loss. In this way, ATCS strive for a local optimum.
The instruments belonging to the class of ATCS are more or less rigid standard operations, which can be fully automated and need no human intervention. Hence, according to the definition of information systems given before, ATCS constitute no true information system (the component 'persons' is not involved). The exact objectives of the particular ATCS can be modified by the corresponding ATMS, for instance by adjusting certain parameters. The complexity of computer models and the calculation speed of computers restrict area-wide application of ATCS, because computations and actions need to be performed in real-time. The data collections for ATCS should be very accurate, possibly relate to individual vehicles and be directly available in real-time (e.g. in intervals of several seconds to 1 minute).
As a consequence of the local oriented nature of ATCS, an ATCS monitoring system exclusively concerns the direct vicinity of the corresponding (ATCS) traffic control system and basically only provides traffic data for this control system. Moreover, only fixed, infrastructure based traffic detectors (e.g. inductive loops) with very small detector spacings (typically of some hundreds of meters) will be suitable. Since ATCS applications concern only a very limited geographical area, these detector spacings are financially affordable. Longer distances between the detectors, or utilization of non-infrastructure based traffic detectors is not eligible as this can only provide data with a accuracy and a reliability that will be too low for ATCS.
A typical example of an ATC system application is ramp metering, which deals with gradually allowing vehicles on the on-ramp to enter the freeway, depending on the proportion between the actual flow and capacity of the freeway. Almost all traffic systems that are currently employed belong to the class of ATCS applications.
Advanced Traveler Information Systems (ATIS)
Where the road authorities aim at achieving an optimal utilization of 'their' transportation system, in general, road users may be assumed to be predominantly interested in accomplishing an optimal route from their origin to their destination over this infrastructure (user optimum). This might be expressed in a minimal travel time (or a minimal generalized time, so comprising the actual or perceived travel time, traveled distance, et cetera) for their entire trip. The third class of applications of transportation telematics that we distinguish, the class of Advanced Traveler Information Systems (ATIS), supports the road user in achieving this task. Hence, the core objective of ATIS is to provide each road user with the information he or she needs to achieve his or her specific travel objectives, within the limiting conditions dictated by the various ATMS and ATCS applications. In this way, ATIS strive for several individual users optima.
For the purpose of supporting and achieving several individual users' optima, ATIS require information about complete routes from origin to destination, about delays on the regular route, about the travel time on alternative routes and about alternative ways of available transport, at the moment of passage. This implies that specific parts of different networks (urban, rural and state) that are relevant during a specific trip are of interest, with information about delays on routes at the moment they will actually be used (requiring short term predictions) instead of instantaneous information. Hence, the regular traffic information to be obtained for ATIS purposes may become available every rather long time interval of for instance 5 to 15 minutes (incidents should be reported more swiftly). These characteristics are in sharp contradiction to the information requirements of ATMS applications, which demand predominantly actual (i.e. real-time) information about one, but entire network.
As a consequence of the established characteristics of ATIS information, i.e. both area-wide and concerning several networks that cover each entire route, an ATIS monitoring system can not always practically be based on fixed, infrastructure based traffic detectors. In particular installing fixed traffic detectors in an entire urban road network, requiring extremely short detector spacing’s due to the close-meshed urban road infrastructure, would be unrealistic. Furthermore, in consideration of the opposite objectives of ATMS and ATIS, an ATIS monitoring system should preferably be independent of an ATMS monitoring system and preferably be based on anything but infrastructure based traffic detectors exploited by government or state. For these specific ATIS purposes, one can use a monitoring system based on non-infrastructure based detectors, such as probe vehicles. These are normal vehicles that participate in the traffic flow, are equipped with a location and communication device and accordingly transmit experienced traffic data to a traffic center.
1) Implementation:-
We are set to begin testing an intelligent transportation system in Japan that allows vehicle- infrastructure communication to help reduce traffic accidents and ease congestion. The system uses information obtained from nearby vehicles and roadside optical beacons to wirelessly alert drivers to potential danger from approaching vehicles. It also provides drivers with fastest-route information with Nissan’s probe server collecting city –wide traffic data from the mobile phones of Nissan’s CARWINGS navigation service subscribers, taxi services, and vehicle data collected by mobile phone operator NTT DoCoMo. This information is then sent to the driver’s navigation screen where it is displayed as real-time maps showing the traffic flow and density. Screen shots and diagrams here.
Fig no.2.Actual Smart vehicle system
The test, which is being conducted to evaluate the receptivity of drivers to such a system, run from Oct. 1, 2006 until the end of March 2009 in Kanagawa Prefecture, about 25 kilometers southwest of Tokyo. About 10,000 drivers, who must be subscribers to Nissan’s CARWINGS navigation service, participated in the test.