This thesis investigates the effect of a feedback-reward system on speeding and tailgating behaviours. Data utilized in this study were collected from 37 participants through a field trial commissioned by Transport Canada. In this trial, a feedback-reward system was investigated, which provided feedback and rewards to the drivers based on speed limit compliance and safe headway maintenance. The trial consisted of three phases: baseline, intervention, and post-intervention. During the intervention phase, real-time feedback was provided on an in-vehicle display. Participants also accumulated reward points and could view related information on a website. Results indicate that the intervention resulted in a significant increase in speed limit compliance, and this positive effect, although dampened, was still apparent after system removal. Similarly, results on headway compliance rate indicate a positive intervention effect, however, this effect did not sustain after system removal. These findings have implications for developing better aids to improve driving behaviour.

This thesis investigates the effect of a feedback-reward system on speeding and tailgating behaviours. Data utilized in this study were collected from 37 participants through a field trial commissioned by Transport Canada. In this trial, a feedback-reward system was investigated, which provided feedback and rewards to the drivers based on speed limit compliance and safe headway maintenance. The trial consisted of three phases: baseline, intervention, and post-intervention. During the intervention phase, real-time feedback was provided on an in-vehicle display. Participants also accumulated reward points and could view related information on a website. Results indicate that the intervention resulted in a significant increase in speed limit compliance, and this positive effect, although dampened, was still apparent after system removal. Similarly, results on headway compliance rate indicate a positive intervention effect, however, this effect did not sustain after system removal. These findings have implications for developing better aids to improve driving behaviour.

DTN(Delay Tolerant Networks)是一種缺乏網路基礎設備的網路架構，在這類的網路架構下，無線節點之間的通訊連線並非同時存在，而是間歇式建立的。因為節點的移動、或是裝置省電模式運作與環境因素的影響，造成連線可能不定時的失效。有不保證連線特性的網路，在DTN網路中節點間相遇的機會很少，節點間利用 Store-Carry-Forward 的方式傳遞訊息，且有相當長的傳遞延遲(Propagation Delay)。在這樣的網路特性下，傳統的文獻中，都是假設所有節點都會幫忙傳遞。但不幸的，在現實生活中有自私節點(Selfish Nodes)的存在，因自己本身設備資源有限，如電力資源、網路資源...等，節點不願意幫忙傳送訊息，這些自私節點的存在，會對DTN網路架構造成破壞，導致無法傳送訊息到目的地。為了解決自私節點的問題，我們提出了MTBIS(Mobile Trusted Bank of Incentive Strategies)，當發送節點(Source Node)要求傳送訊息時，給予回饋給幫忙轉傳訊息的節點，來鼓勵節點間互相幫忙傳送訊息，我們稱這些回饋為Incentive Credit。而節點也可利用Incentive Credit來要求別的節點幫忙轉傳訊息。另外也加入SI(Social Incentive)機制，與DGT(Dynamic Grudger Threshold) ，吸引自私節點願意幫忙轉傳訊息，改進了 MTBIS 在自私節點環境下的不足， 利用經濟學的角度來解決節點運用Credit的問題，借此提高訊息的傳遞率(Delivery Ratio)。 本篇研究也注重於自私節點的模擬，利用四種不同特性的節點： Sucker(傻瓜)、Cheater (騙子)、Grudger(小氣鬼)、Ecci(投機者)， 這些自私節點會照成DTN在設計上無法使用，甚至降低訊息的傳達率，因此我們模擬了這些自私節點的行為，並且使用我們所提出的獎勵機制，來解決這些自私節點的問題，實驗結果也證明，Grudger可以有效的抑制自私節點對效能大幅降低的問題，與傳統的演算法相較，效能高出34%。 / DTN (Delay Tolerant Networks) is a network structure without need to use any infrastructure. In DTNs, wireless connections between nodes do not always exist, i.e., nodes are connected intermittently. Due to the mobility, power issues, or surrounding environment of nodes, connections between nodes may be disruptive occasionally or randomly. In a DTN, nodes usually transfer the message to the encountering nodes. By this way, the messages are stored, carried, and forwarded to the next nodes, possibly the destination. However, in reality, nodes may not be willing to help each other for the message forwarding. More specifically, there are “Selfish nodes” which refuse to forward messages due to issues such as energy and network bandwidth. Thus it will prevent messages from being forwarded to its destination. In order to solve the problem of message forwarding failure caused by selfish nodes, we proposed an Incentive Strategy called “MTBIS (Mobile Trusted Bank and Incentive Strategies)”. We construct a rewarding scheme called “Incentive Credit” for nodes who forward the messages for the source node. In addition, to increase the intention of the selfish nodes for forwarding messages, we add two more mechanism called SI(Social Incentive) and DGT(Dynamic Grudger Threshold). The DGT uses credits to solve selfish node problems from an economics point of view to enhance MTBIS to work with existence of selfish nodes. In this thesis, we emphasis on the simulation of the behaviors of selfish nodes, using four different types of nodes: the “Sucker”, the “Cheater”, the “Grudger”, and the “Ecci”. These selfish nodes will decrease the success rate of message forwarding, and even make the DTN unusable. We simulated the behaviors of these selfish nodes, using the rewarding scheme we proposed. From the results of our experiment, we see that the Grudger can effectively deal with performance issues caused by selfish nodes, and the system can gain 34% in performance compared to the traditional algorithms.

Thesis (PhD) - Swinburne University of Technology, 2006. / Submitted for the degree of Doctor of Philosophy, Swinburne University of Technology - 2006. Typescript. Includes bibliographical references (p. 193-207).

Thesis equivalent (M.P.H.)--University of Michigan, 1945.

Thesis (Ph. D.)--University of Michigan, 1997. / Includes bibliographical references.

Thesis equivalent (M.P.H.)--University of Michigan, 1945.

Thesis (Ph. D.)--State University of New York at Binghamton, Department of Psychology, 2008. / Includes bibliographical references.

Thesis (Ph. D.)--Stanford University, 2002. / Includes bibliographical references (leaves 109-115).

Thesis (M.S. in Leadership and Policy Studies)--Vanderbilt University, Aug. 2006. / Title from title screen. Includes bibliographical references.